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ACTA FACULTATIS XYLOLOGIAE ZVOLEN

VEDECKÝ ČASOPIS SCIENTIFIC JOURNAL

67 2/2025

Vedecký časopis Acta Facultatis Xylologiae Zvolen uverejňuje pôvodné recenzované vedecké práce z oblastí: štruktúra a vlastnosti dreva, procesy spracovania, obrábania, sušenia, modifikácie a ochrany dreva, termickej stability, horenia a protipožiarnej ochrany lignocelulózových materiálov, konštrukcie a dizajnu nábytku, drevených stavebných konštrukcií, ekonomiky a manažmentu drevospracujúceho priemyslu. Poskytuje priestor aj na prezentáciu názorov formou správ a recenzií kníh domácich a zahraničných autorov. Scientific journal Acta Facultatis Xylologiae Zvolen publishes peer-reviewed scientific papers covering the fields of wood: structure and properties, wood processing, machining and drying, wood modification and preservation, thermal stability, burning and fire protection of lignocellulosic materials, furniture design and construction, wooden constructions, economics and management in wood processing industry. The journal is a platform for presenting reports and reviews of books of domestic and foreign authors. VEDECKÝ ČASOPIS DREVÁRSKEJ FAKULTY, TECHNICKEJ UNIVERZITY VO ZVOLENE 67 2/2025 SCIENTIFIC JOURNAL OF THE FACULTY OF WOOD SCIENCES AND TECHNOLOGY, TECHNICAL UNIVERSITY IN ZVOLEN 67 2/2025 Redakcia (Publisher and Editor’s Office): Technická univerzity vo Zvolene (Technical university in Zvolen); TUZVO Drevárska fakulta (Faculty of Wood Sciences and Technology) T. G. Masaryka 2117/24, SK-960 01 Zvolen, Slovakia Redakčná rada (Editorial Board): Predseda (Chairman): prof. Ing. Mariana Sedliačiková, PhD. TUZVO (SK) Vedecký redaktor (Editor-in-Chief): prof. Ing. Ladislav Dzurenda, PhD, TUZVO (SK) Členovia (Members): prof. RNDr. František Kačík, DrSc. TUZVO (SK) prof. RNDr. Danica Kačíková, MSc. PhD., TUZVO (SK) prof. Ing. Ivan Klement, CSc. TUZVO (SK) prof. Ing. Ján Sedliačik, PhD, TUZVO (SK) doc. Ing. Richard Kminiak, PhD. TUZVO (SK) doc. Ing. Rastislav Lagaňa, PhD. et PhD. TUZVO (SK) doc. Ing. Miroslava Mamoňová, PhD. TUZVO (SK) doc. Ing. Hubert Paluš, PhD. TUZVO (SK) doc. Ing. Zuzana Tončíková, ArtD. TUZVO (SK) Jazykový editor (Proofreader): Mgr. Žaneta Balážová, PhD. Technický redaktor (Production Editor): Ing. Michal Dudiak, PhD.

Medzinárodný poradný zbor (International Advisory Editorial Board):

Antov Petar Yordanov (Univ of Forestry, BG), Bekhta Pavlo (Ukrainian Nat Forestry Univ, UA), Deliiski Nencho (Univ of Forestry, BG), Hua Lee Seng (UiTM Cawangan Pahang, MY), Jelačić Denis (Univ Zagreb, HR), Kasal Bohumil (Tech Univ Carolo Wilhelmina Braunschweig, DE), Lubis Muhammad Adly Rahandi (Kyungpook Nat Univ, ID), Marchal Remy (Arts & Metiers ParisTech, FR), Németh Róbert (Univ Sopron, HU), Niemz Peter (Bern Univ Appl Sci, Architecture Wood & Civil Engn, CH), Orlowski Kazimierz A.(Gdansk Univ Technol, PL), Pohleven Franc (Univ Ljubljana, SI), Rogoziński Tomasz (Poznań Univ of Life Sci, PL), Teischinger Alfréd (Univ Nat Res & Life Sci, BOKU, AT), Smardzewski Jerzy (Poznań Univ of Life Sci, PL), Vlosky Richard P. (Louisiana State Univ, USA), Wimmer Rupert (Univ Nat Res & Life Sci, AT). Vydala (Published by): Technická univerzita vo Zvolene, T. G. Masaryka 2117/24, 960 01 Zvolen, IČO 00397440, 2023 Náklad (Circulation) 80 výtlačkov, Rozsah (Pages) 154 strán, 9,94 AH, 12,04 VH Tlač (Printed by): Vydavateľstvo Technickej univerzity vo Zvolene Vydanie I. – december 2025 Periodikum s periodicitou dvakrát ročne Evidenčné číslo: 3860/09 Acta Facultatis Xylologiae Zvolen je registrovaný v databázach (Indexed in): Web of Science, SCOPUS, ProQuest, AGRICOLA, Scientific Electronic Library (Russian Federation), China National Knowledge Infrastructure (CNKI) Za vedeckú úroveň tejto publikácie zodpovedajú autori a recenzenti. Rukopis neprešiel jazykovou úpravou. Všetky práva vyhradené. Nijaká časť textu ani ilustrácie nemôžu byť použité na ďalšie šírenie akoukoľvek formou bez predchádzajúceho súhlasu autorov alebo vydavateľa. © Copyright by Technical university in Zvolen, Slovak Republic. ISSN (print) 1336–3824, ISSN (online): 2730-1176

CONTENTS 01. SERGIY KULMAN – OLEKSANDRA HORBACHOVA – ANATOLII VYSHNEVSKYI – JÁN SEDLIAČIK: KINETICS AND MODELLING OF WATER ABSORPTION PROCESSES IN DIFFERENT TREE SPECIES .........................................................................................................

02. CK MUTHUMALA – KKIU ARUNAKUMARA – DE SILVA SUDHIRA – PLAG ALWIS – FMMT MARIKAR: ASSESSMENT OF THE RELATIONSHIPS BETWEEN FIBER AND MECHANICAL PROPERTIES OF TREE SPECIES ..............................................................

03. BEKIR CIHAD BAL: EVALUATION OF THE MECHANICAL PROPERTIES OF POPLAR LAMINATED VENEER LUMBER (LVL) REINFORCED WITH OAK, BEECH, AND EUCALYPTUS VENEERS ...

04. VILIAM PÚČEK – RICHARD HRČKA: MEASUREMENT BOUND WATER MAXIMUM MOISTURE CONTENT AND DIFFUSION COEFFICIENT DETERMINATION OF BLOWN CELLULOSIC INSULATION MATERIAL IN LABORATORY CONDITIONS ................

05. ANDRII SPIROCHKIN – OLENA PINCHEVSKA – YURIY LAKYDA – DENIS ZAVYALOV – ROSTISLAV OLIYNYK – JÁN SEDLIAČIK: MOISTURE CONDUCTIVITY AND DENSITY OF INDUSTRIAL WOODS: A STUDY FOR EFFECTIVE DRYING ..............

06. LUKÁŠ ŠTEFANČIN – RASTISLAV IGAZ – IVAN KUBOVSKÝ – IVAN RUŽIAK – RICHARD KMINIAK: ENERGY DOSE AND SPECIFIC CUTTING ENERGY IN CO₂ LASER CUTTING OF SOLID AND ENGINEERED WOOD MATERIALS ................................................

07. GEORGI KOVATCHEV – VALENTIN ATANASOV: BEARINGS LOAD ON A CIRCULAR SAW MILL DURING CUTTING BEECH WOODS ..........................................................................................................

08. KRASIMIRA ATANASOVA – DIMITAR ANGELSKI – DOBRIYAN DOBRIYANOV: PROPERTIES OF WOOD SURFACE COATED WITH OIL WAX ...............................................................................................................

09. MIKHAIL CHERNYKH – ALINA KOREPANOVA – EKATERINA MAKSIMOVA – MAXIM GILFANOV – VLADIMIR STOLLMANN: COLORISTIC SOLUTION FOR COMPLEX MOSAIC IMAGES LASERENGRAVED ON WOOD ..............................................................................

10. ĽUDMILA TEREŇOVÁ – DARIA MOKRENKO – MÁRIA KOZLOVSKÁ: INNOVATIVE COMPOSITIONS OF STRUCTURAL ELEMENTS AND THEIR ESTIMATED FIRE RESISTANCE ...................

101

11. ANNA VILHANOVÁ – NADEŽDA LANGOVÁ – MAREK VOJTKULIAK: THE INFLUENCE OF SEWING THREAD FINENESS AND STITCH LENGTH ON SEWN JOINT STRENGTH .............................

117

12. DENIS PINKA – MARIANA SEDLIAČIKOVÁ – MARTIN SYNÁKVARGA: INTERPERSONAL RELATIONSHIPS, CONFLICTS, AND NEPOTISM IN WOOD-PROCESSING BUSINESSES .................................

127

13. MAREK POTKÁNY – JARMILA SCHMIDTOVÁ – PETRA LESNÍKOVÁ: CONTROLLING IN WOODWORKING AND FURNITURE MANUFACTURING ENTERPRISES: DOES PERFORMANCE INFLUENCE ITS ESSENCE AND APPLICATION? ....

141

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 5−18, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.01

KINETICS AND MODELLING OF WATER ABSORPTION PROCESSES IN DIFFERENT TREE SPECIES Sergiy Kulman – Oleksandra Horbachova – Anatolii Vyshnevskyi – Ján Sedliačik ABSTRACT A novel two-stage kinetic model for simulating water absorption in wood is presented, explicitly accounting for simultaneous absorption and evaporation in the longitudinal direction and addressing limitations of prior models focused primarily on drying or radial sorption. Water absorption was investigated by partial immersion of samples from three tree species – paulownia (Paulownia in vitro), alder (Alnus glutinosa), and pine (Pinus sylvestris). A computational experiment was conducted using parameter sensitivity analysis of the developed mathematical model. The model demonstrates high fidelity in describing sorption kinetics, with correlation coefficients reaching 85% for absorption (logarithmic dependence) and over 90% for dehydration (exponential reliance). At 20 °C, the paulownia absorption rate exceeded alder by 8% and pine by 23%. These findings enhance understanding of moisture transport mechanisms and offer practical insights for optimizing impregnation processes in wood processing. Keywords: wood; water absorption; saturation kinetics; parameter sensitivity analysis; mathematical model.

INTRODUCTION There is a global trend towards the cultivation of fast-growing species (crop rotation from 5 to 10 years). Their primary purpose is the production of wood fibers and biomass. But these species certainly have potential in the manufacturing of solid wood products. One of the fast-growing species is paulownia (Paulownia in vitro), a species under cultivation in plantations that is steadily increasing in Ukraine. However, there is still insufficient information on wood properties, and therefore doubts arise regarding the scope of use (Barbu et al., 2023; Huber et al., 2023). The behavior of wood and wood-based materials in interaction with water is crucial during material preparation for production and during the operation of the finished product. Water in wood is present in two primary forms: as cell wall water, which interacts with polymer components (cellulose, hemicellulose, and lignin), and as capillary water, which fills the cavities in the porous structure of wood. Understanding the difference between these types of water is critically important, as each has a different impact on the physical, mechanical, and chemical properties of wood and wood-based materials (Kulman et al., 2019а; Kulman et al., 2019b; Báder and Németh, 2019; Thybring and Fredriksson, 2023). Cell wall water affects the hygroscopicity, expansion, and contraction of wood, while 5

capillary water determines the water absorption and resistance of wood to decay and other biological processes. These shortcomings need to be solved. The study of fluid flow (bulk and molecular) through wood has become the basis for many woodworking processes (Avramidis, 2007; Kulman et al., 2021а; Tsapko et al., 2022; Vaziri et al., 2023). The results confirm that wood impregnation is an effective method. The principle of impregnation processes is to treat wood with an agent that, under certain conditions, diffuses into the cell walls, where it subsequently polymerizes to obtain the desired properties. Wood of various species has been impregnated with thermosetting resins (Yusof et al., 2019; Manabendra et al., 2000; Luo et al., 2021), waxes and oils (Wang et al., 2017; Shiny et al., 2017), monomers and polymers (Broda and Mazela, 2017; Nguyen et al., 2019), acids and anhydrides (Augustina et al., 2022; Horbachova et al., 2024). For example, thermosetting resins, such as phenolformaldehyde, impart wood greater rigidity and water resistance. On the contrary, waxes can reduce water absorption by forming a protective film on the surface. Oils such as linseed or tung oil penetrate the wood structure, providing additional protection against moisture and rot. The main difficulty in modeling moisture movement in wood is that multiple mechanisms may contribute to the overall flow, and their relative contributions may vary. Modeling is also complicated by the fact that wood is a porous, anisotropic material. In these models, wood is treated as a porous medium with multiphase flow and heat transfer. The equations are derived from fundamental mathematical models of multiphase flow and heat transfer in porous media, based on conservation principles. However, such models are primarily used to quantitatively describe moisture removal from wood during drying (Ciegis and Starikovicius, 2002; Ciegis et al., 2004; Avramidis et al., 2023). Existing models often overlook simultaneous absorption and evaporation during partial immersion, focusing instead on drying or non-longitudinal directions, leading to incomplete predictions for impregnation processes. This work overcomes these limitations by introducing a two-stage first-order kinetic model that explicitly accounts for both methods, thereby providing a more accurate simulation for anisotropic wood species such as paulownia. A deep understanding of the interaction between water and wood is necessary to optimize technologies for processing, storing, and using wood in various applications. It is especially true for new species, such as paulownia. This knowledge can also serve as the basis for further research in the field of wood modification (including low-density), improving performance properties, and expanding its scope of use. The purpose of this study is to develop and improve mathematical models for the simulation of moisture movement in wood, in particular under conditions of anisotropy and the multiphase nature of this material. The study involves analyzing and optimizing mechanisms that affect moisture flux, with a focus on identifying and quantifying each mechanism’s contribution to the overall process.

MATERIALS AND METHODS The base material, lumber, was provided by Paulownia Energy Ukraine (Lutsk, Ukraine). Three species of wood were used in this study – paulownia (Paulownia in vitro), (density 300 kg/m3), pine (Pinus sylvestris), (450 kg/m3) and alder (Alnus glutinosa), (470 kg/m3). Samples measuring 300 × 20 × 20 mm were cut from each species (Fig. 1). The areas of the radial and tangential sections are equivalent, since radially cut boards were used. 6

Samples were conditioned at 20°C and 65% relative humidity until reaching an equilibrium moisture content of approximately 10% (measured with an electronic moisture meter, accuracy ± 0.1%). No oven-drying was performed before experiments to simulate natural conditions. Six replicates per species were used, with measurements taken at 1-hour intervals for the first 8 hours, then every 4 hours, and statistical analysis included mean values ± standard deviation. Paulownia is a deciduous, ring-vascular species. It has clearly defined large vessels in the early wood of the annual ring, which gradually decrease to the late wood. The main feature of paulownia is the size of the vessels – from 100 to 300 microns and beyond (especially in the early zone), which affects the low density of the wood. The walls of the vessels are thin, the rays are wide, and the parenchyma is well developed, especially the axial one, which also contributes to diffusion. Alder is also a deciduous species, but it is diffusely vascular. The conducting elements (vessels) are small, usually 30 to 80 microns in diameter. They are evenly distributed throughout the annual ring. The vessels occupy a smaller volume than in paulownia, but are the main conducting elements. The walls of the vessels are relatively thin; the parenchyma is developed but less pronounced than in paulownia; the rays are wide. The presence of numerous small vessels provides a high diffusion rate. The smaller lumen diameter creates greater resistance to water flow than in paulownia. Pine is a coniferous species in which the conducting elements are tracheids. Their diameter is much smaller than that of the vessels, from 20 to 50 microns. Water transport between tracheids occurs through bordered pores of a complex membrane structure with a torus, which can regulate the flow of water and prevent the spread of air emboli, but also limits the flow rate. Tracheids make up 90–95% of the volume of wood. The thickness of the cell walls is usually greater than that of the vessels, especially in late wood. The parenchyma is limited, mainly around the resin ducts; the rays are less pronounced than in hardwoods.

Fig. 1 Samples and measuring instruments.

The humidity and temperature in the room were 65% and 20°C, respectively. An electronic caliper (measurement accuracy 0.01 mm) and a thermometer (± 0.1°C) were also used. An electronic moisture meter (± 0.1%) was used to determine moisture content. Water absorption measurements were performed by immersing one end of the sample in water. The tests were conducted in accordance with EN ISO 15148. During the tests, periodic moisture measurements were made along the fibers of the samples at a step of 19 mm, equal to the distance between the moisture meter's measuring needles. It amounted to 12 measurements per sample. 7

Since the speed of capillary movement directly depends on the capillary radius, wood water absorption should occur in two stages. In the first, all microcapillaries (bound water) and part of the macrocapillaries are filled, and in the second, all macrocapillaries (free water) are filled. The transition between stages is defined quantitatively as the point at which the absorption rate equals the evaporation rate, as derived from the kinetic equation (Eq. 1) as dM/dt_absorption = dM/dt_evaporation. The total mass of water in wood, which is constantly changing due to water absorption and evaporation, was taken as the phase variable. The model describes the increase in moisture content, with a constant change in the total moisture content of the wood over time. In this case, the change in total humidity will be determined by the basic kinetic equation, which reflects the law of conservation of mass: 𝑑𝑊(𝑡) = 𝑑𝑊 + (𝑡) − 𝑑𝑊 − (𝑡)

(1)

Where: 𝑑𝑊 + (𝑡) – increase in the total mass of water due to impregnation, that is, in the general case, it is diffusion (arrival), over a period of time 𝑑(𝑡), kg; 𝑑𝑊 − (𝑡) – reduction in the total mass of water in wood, due to evaporation (loss) over time 𝑑(𝑡), kg. To better understand the trend of the process, it is worth using dimensionless quantities, as they are the most informative and are not tied to reference systems (Kulman et al., 2021b). To be able to compare and study the saturation kinetics of several different species (simultaneously observed) with different initial weights, we introduce new dimensionless moisture content measurements, namely, dimensionless moisture content (concentration): 𝑊(𝑡)

𝐶𝐵(𝑡) = 𝑊

(2)

Given the initial conditions t = 0, the introduced dimensionless quantities can be written in the form: 𝐶𝐵(0) = 1; 𝐶𝐴(𝑡) = 0; 𝐶𝐶(𝑡) = 0

(3)

The dimensionless moisture content was calculated as C = (Mt - M0)/(Mmax - M0), where Mt is moisture at time t, M0 is the initial moisture, and Mmax is the equilibrium moisture, justified by its ability to normalize data across species for comparative analysis. Previously conducted water absorption experiments led to the conclusion that the wood impregnation process can be considered an analogue of a first-order chemical reaction. Therefore, the kinetic scheme of a sequential process with two elementary stages of the first order will have the form: 𝑘1

𝑘2

𝐶𝐴(𝑡) → 𝐶𝐵(𝑡) → 𝐶𝐶(𝑡)

(4)

Where: CB(t) – current average water concentration in wood at time t; CA(t) – maximum water concentration inside the wood at time t, «moisture source»; CC(t) – minimum water concentration on the wood surface at this point in time t; k1 – rapidity of increase in water concentration in wood due to diffusion and other impregnation mechanisms (diffusion coefficient), g·sm-2·s-1; k2 – rapidity of reduction in water concentration in wood by evaporation from the surface of the detail, g·sm-2·s-1. 8

Using the new notation, we can write the basic governing equation (1) in the form: 𝑑𝐶𝐵(𝑡) 𝑑𝑡

= 𝑘1 (𝐶𝐴(𝑡) − 𝐶𝐵(𝑡)) − 𝑘2 (𝐶𝐵(𝑡) − 𝐶𝐶(𝑡))

(5)

This differential equation can be solved using the standard method of separation of variables. 𝑑𝐶 = 𝑘1 (𝐶𝑚 − 𝐶) − 𝑘2 (𝐶 − 𝐶0 ) 𝑑𝑡 𝐶

1 ln[(−𝐶)𝑘1 − 𝐶𝑘2 + 𝑘1 𝐶𝑚 + 𝑘2 𝐶0 ] 𝑑𝐶 → 𝑘1 + 𝑘2 𝐶0 𝑘1 (𝐶𝑚 − 𝐶) − 𝑘2 (𝐶 − 𝐶0 ) ln[(−𝑘1 )(𝐶0 − 𝐶𝑚 )] + 𝑘1 + 𝑘2

∫

𝑡

∫ ln 𝑑𝑡 → 𝑡 → 𝑡0 𝑡0

𝑡 ∶=

(ln(𝑘1 𝐶𝑚 − 𝑘1 𝐶 − 𝑘2 𝐶 + 𝑘2 𝐶0 )) + ln[(−𝑘1 )(𝐶0 − 𝐶𝑚 )] 𝑘2 + 𝑘2

𝐶𝑚 ∶= 45

𝐶 ∶= 41,82

𝐶0 ∶= 10

𝑘1 ∶= 0,15

𝑘2 ∶= 0,015

(− ln(𝑘1 𝐶𝑚 − 𝑘1 𝐶 − 𝑘2 𝐶 + 𝑘2 𝐶0 )) + ln[(−𝑘1 )(𝐶0 − 𝐶𝑚 )] 𝑓𝑙𝑜𝑎𝑡, 3 → 59,2 − 19,0𝑖 𝑘1 + 𝑘2 (59,22 + 192 )0,5 → 62,174271206022190092

(6)

The degree of hydration was assessed by measuring the gradual saturation of the samples with water, that is, the concentration of water in the wood («moisture source»): СA(t) = M(t)/M0

(7)

Where: CA(t) – water concentration in the sample at a point in time t, g/g; M(t) – weight of the impregnated sample at a point in time t, g; M0 – sample weight at the start of testing, that is, t = 0. New dimensionless quantities for measuring the degree of hydration were introduced, such as the dimensionless moisture content (moisture concentration): 𝐶𝐴(𝑡) = 𝑀(𝑡)⁄𝑀0 ; 𝐶𝐵(𝑡) = (𝑀𝐵(𝑡) − 𝑀0 )⁄𝑀0 ; 𝐶𝐶(𝑡) = (𝑀𝐶(𝑡) − 𝑀0 )⁄𝑀0

(8)

Where: CA(t) – maximum water concentration in the sample at a point in time t, g/g; CВ(t) – water concentration at a point in time t, g/g; MВ(t) – weight of water at a point in time t, g; CС(t) – minimum water concentration at a point in time t, g/g; MС(t) – weight of water in microcapillaries at a point in time t, g.

The computational experiment is conducted using a parametric analysis of the constructed mathematical model.

RESULTS AND DISCUSSION

Сhanges in the dynamic phase variable

A so-called parametric analysis was applied to qualitatively assess the model's ability to describe the processes occurring during hydration. To determine the logical connection between changes in parameters and the dynamics of phase variables over time, it is necessary to assess how the shape of the integral curves changes as the model parameters are varied. Since the parameters of the studied system are hydration rates, it is necessary to determine how the hydration process changes with the ratio of the process rates. Fig. 2a shows the kinetic scheme of the model under specific initial conditions. Fig. 2b shows graphs of changes in the dynamic phase variables (integral curves) in time from 0 to 62 hours.

Observation period, h. а

Fig. 2 Processes during hydration under conditions of changing parameters over time: a – kinetic scheme of the model at the model time of 62 h.; b – water concentration at a point time CВ(t) (creation of a «moisture source» in the wood).

The average results of six series of experiments on the impregnation of the studied wood species are given in Tab. 1, which characterizes the dependence of changes in moisture content on time and distance (measurement number) from the «moisture source». Tab. 1. Average moisture values (%) depending on time during impregnation of wood samples. Measurement number

Time [h]

22/20.8/19

13/11/12

27/24.8/22

15/13/14

31/29/26

16/14/15

34/33/30

17/15/16

39/35.7/31

19/17/17

12/12/11

41/37.4/33

21/19/19

13/13/12

11/10/10

120

41/38.6/34

22/22/20

17/17/16

14/14/13

12/11/11

144

42/39.7/35

23/21/21

18/18/17

15/15/14

13/11/11

11/10/10

168

44/40.5/35

24/22/23

19/19/18

16/16/15

14/11/12

12/11/11

11/11/10

192

44/41.6/36

26/24/24

19/20/19

17/17/16

15/12/13

13/11/11

11/11/11

216

45/42.5/37

30/28/26

22/22/20

19/19/17

17/14/14

15/12/12

13/12/11

12/11/11

11/10/10

Note: The moisture content values (%) are given for the studied species in the following order: paulownia/alder/pine.

A graphical presentation of all the results of fluid diffusion along the fibers is shown in Figure 3. %

50 40

10 0

1 2 3 4

168 96 24

144 48

1 5 6 7 8 9 10 11

1 2 3 4

1 5 6 7 8 9 10 11

b -10-10

10-30

30-50

50 30 144

10 -10 1 2 3 4 1 5 6 7 8 9 10 11

c Fig. 3 Three-dimensional gradient diagrams of the dependence of the change in moisture content on the time of moistening the moisture source and the impregnation time: a – paulownia; b – alder; c – pine.

Figure 4 presents the results of the saturation kinetics of a part immersed in water (creation of a «moisture source» inside the wood). 50 Moisture content, %

Moisture content, %

50 40 30

y = 6.4845ln(x) + 10.415 R² = 0.995

20 10 0

100 Saturation time, h.

200

40 30

y = 5.9997ln(x) + 9.9608 R² = 0.9998

20 10 0

100 Saturation time, h.

200

Moisture content, %

40 30 y = 4.9868ln(x) + 10.016 R² = 0.9983

20 10 0

100 Saturation time, h.

200

Fig. 4 Kinetics of hydration of a piece of wood immersed in water (formation of a moisture source): a – paulownia; b – alder; c – pine.

Figure 4 also shows the trend lines (regression equations) with the highest correlation coefficients. The general nature of all regression equations can be represented as a logarithmic dependence in the coordinates M(t): (9)

𝑀(𝑡) = 𝑎 ln 𝑡 + 𝑏

The nature of the regression line, with logarithmic dependence, reflects the rate of change in the sample's weight, that is, the intensity of hydration. This means that the coefficient before the logarithm of time indicates the hydration rate. By actually differentiating the left and right sides of equation (9), it is possible to determine the rate of change of the sample weight over time: 𝑑(𝑀(𝑡)) 𝑑𝑡

𝑑(𝑎 ln 𝑡+𝑏) 𝑑𝑡

𝑎 𝑡

(10)

At the same time, the constant b does not characterize the kinetics of the process, but depends only on the coordinate system in which the humidity value (moisture content) is determined. That is, it depends on the formula used to determine humidity (absolute or relative). This understanding of the regression equation as a mathematical model of the hydration process enables comparison of impregnation processes under different conditions and across different species. Based on the analysis of regression equations, it can be concluded that the hydration rate in paulownia is greater than in alder and pine, and is comparable: Vpl = 6.48; Va = 5.99 and Vpn = 4.99, respectively, at a water temperature of 20 °C. The results of the analysis of the impregnation process, that is, the movement of water inside the wood (diffusion) along the fibers from the source of moisture to the opposite section of the sample located in the air, are presented in Fig. 5.

Moisture content, %

y = 39.35e-0.144x R² = 0.8689

30 20 10 0

y = 34.69e-0.136x R² = 0.8609

30 20

10 0

Measurement number

40 30

Moisture content, %

y = 30.702e-0.124x R² = 0.8558

20 10 0

5 Measurement number

216 h. 192 h. 168 h. 144 h. 120 h. 96 h. 72 h. 48 h. 24 h. 12 h. 6 h. 1 h.

Fig. 5 Kinetics (rapidity) of water movement inside wood (diffusion) along the fibers from the source of moisture to the opposite part of the part located in the air: a – paulownia; b – alder; c – pine.

Figure 5 shows the dependence of moisture content along the fibers at different initial moisture contents of the moisture source. The regression equations and correlation coefficients are shown for the curves with the maximum initial humidity, that is, for time t = 216 h. The curves for the three species show an exponential decrease in moisture content over time (as indicated by the presence of exponential regression equations), a pattern typical of diffusion processes. However, there are notable differences in the rate and efficiency of diffusion between species. The exponent coefficient (k = 0.144) for paulownia is the highest among the others. This indicates the fastest decrease in moisture content, i.e., the fastest rate of water diffusion along the fibers. For alder, k = 0.136, which is slightly lower than for paulownia, but higher than for pine. The lowest exponent coefficient (k = 0.124) among the three species was found in pine, which indicates the slightest decrease in moisture content and, accordingly, the lowest rate of water diffusion along the fibers. The regression equation that most fully describes this curve is the exponential one, the equation of which, in general form, can be represented as follows: 𝑀(𝑡) = 𝑀0 𝑒 𝑘𝑡

(11)

In this case, k can be both greater and less than zero. Moreover, the pre-exponential factor M0 is equal to the value at t = 0, that is, the beginning of the process. The value of M0 depends on the choice of the coordinate system in which the humidity value is determined 13

and does not characterize the kinetics (speed) of the process in any way, but only determines its initial conditions. In this case, the process rapidity will be: 𝑑(𝑀(𝑡)) 𝑑𝑡

𝑑(𝑀0 𝑒 𝑘𝑡 ) 𝑑𝑡

= 𝑀0 𝑘𝑒 𝑘𝑡

(12)

The coefficient k characterizes the rate of wood impregnation along the fibers. In our case, the highest impregnation rate is in paulownia, the lowest is in pine, and is kpl = 0.144; ka = 0.136; kpn = 0.124. The dehydration rates of paulownia and alder differ slightly at 20 °C, which may be a strong argument in favor of simultaneous drying of both species in the same chamber. It allows for improved production logistics. High correlation coefficients for the regression equations for both hydration and dehydration confirm the hypothesis that these processes are first-order kinetics. That is, the processes can be described (modeled) in the form of ordinary first-order differential equations: 𝑑(𝑀(𝑡)) 𝑑𝑡

= 𝑘𝑀(𝑡)

(13)

Analysis of the research results (Fig. 3) allows obtaining reliable data on the kinetics of physicochemical processes occurring during impregnation. From the point of view of chemistry, we can talk about the speed of chemical reactions (macrokinetics), and from the point of view of physics, we can talk about how water penetrates into wood due to diffusion, capillary or other pressure (Hill, 2006). To date, there is a lot of research devoted to the interaction between wood and water (Tamme et al., 2013; Glass and Zelinka, 2021). However, these works reveal certain contradictions and incompatibility of individual statements. This can be explained by the fact that the physical system consisting of water and wood is extremely complex. Analysis of the research results (Fig. 3) allows obtaining reliable data on the kinetics of physicochemical processes occurring during impregnation. From the point of view of chemistry, we can discuss the rate of chemical reactions (macrokinetics), and from the point of view of physics, we can discuss how water penetrates wood through diffusion, capillary pressure, or other forces (Hill, 2006). To date, much research has focused on the interaction between wood and water (Tamme et al., 2013; Glass and Zelinka, 2021). However, these works reveal certain contradictions and incompatibility of individual statements. This can be explained by the fact that the physical system consisting of water and wood is highly complex. Based on the obtained regression equations (Figs. 4 and 5), it was established that when the coordinate system for moisture estimation is changed, the equations for the same species differ only in the values of the constant coefficients, which do not affect the nature of the hydration kinetics at all. However, the structure of the conductive elements of wood has a significant effect on the rate of water diffusion along the fibers. Paulownia, with its large vessels, exhibits the fastest diffusion, alder, with its smaller vessels, is in between, and pine, which contains tracheids, has the lowest diffusion rate. This is an essential factor to consider when selecting wood species for various applications where moisture content control is critical. At the same time, it is known that during the impregnation of wood along the fibers, provided it is partially immersed in water, three kinetic processes co-occur. Hydration of the part that is in water – creation of a source of moisture inside the wood; diffusion (movement) of water inside the wood towards the free end under the action of a concentration gradient; evaporation (dehydration) of liquid from the surface of the sample 14

depending on the temperature gradient and the speed of thermal convection of air around the sample (Kulman et al., 2019c; Augustina et al., 2023). The model's plausibility is assessed by comparing the experimental absorption (Figs. 3 and 4) with the theoretical results of the kinetic parameters (Equations 7 and 8). Under these conditions, the analytical solution and the numerical model yield the same curves. A high degree of correlation between theoretical and experimental kinetics was observed, confirming the validity of the model. Fig. 3 shows the profiles of water saturation in the samples as a function of wetting time and distance from the moisture source. These concentration profiles are intended to provide qualitative information about the water within the wood, depending on the species at each sample point. This result is consistent with other studies (Amardo et al., 2013; Mahhate et al., 2014). Species differences in absorption and diffusion behavior can be attributed to anatomical features: Paulownia has numerous small vessels (30-80 μm), which provide moderate resistance, while pine tracheids (20-50 μm) with bordered pits limit flow, accounting for its slower rates. The knowledge gained can serve as a basis for optimizing wood processing, storage, and use technologies, as well as for further research into wood modification techniques to obtain a material with planned properties. In addition, the measurement results enabled us to model the wood-drying process, which can serve as a direction for further research. In future studies, it is worth analyzing the dimensional changes in axial deformation of wood under different immersion conditions in the solution. Acetylation and impregnation of wood with salt solutions also remain promising from the perspective of process kinetics. After all, improved wood processing and storage technologies can reduce material and energy costs, which, in turn, will have a positive impact on the environment and the economy, ensuring more efficient use of natural resources.

CONCLUSION A novel two-stage kinetic model for longitudinal water absorption in wood is introduced, marking the first application of a first-order sequential scheme that simultaneously accounts for absorption, diffusion, and evaporation during partial immersion. Model verification using computational and experimental data confirms its accuracy in describing the dynamics of paulownia, alder, and pine, with correlation coefficients of 85% for absorption (logarithmic) and >90% for dehydration (exponential). Alder exhibits intermediate absorption rates, 8% slower than paulownia but faster than pine, with dehydration kinetics similar to paulownia, suggesting potential for co-drying these species to optimize processes. Compared to existing models (e.g., those in Ciegis et al., 2004), our approach better handles anisotropy by quantifying stage transitions using rate-equality criteria, yielding superior predictions of impregnation duration. In practice, these insights enable optimized impregnation for fast-growing species like paulownia, thereby enhancing product quality in wood-based materials. Limitations include single-temperature testing (20 °C) and a fixed initial moisture content (10%); future work should explore temperature dependence, alternative liquids (e.g., salts), and associated dimensional changes to broaden applicability.

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Kulman, S., Boiko, L., Bugaenko, Y., Sedliačik, J., 2021a. Creep life prediction by the basic models of deformation-destruction kinetics of wood-based composites. Acta Facultatis Xylologiae Zvolen 63(2), 39–53. https://doi.org/doi:10.17423/afx.2021.63.2.04 Kulman, S., Boiko, L., Sedliačik, J., 2021b. Long-term strength prediction of wood based composites using the kinetic equations. Scientific Horizons 24(3), 9–18. https://doi.org/doi:10.48077/scihor.24(3).2021.9-18 Luo, J., Zhao, Y., Guo, J., Wang, H., 2021. Impregnating low-molecular-weight phenol formaldehyde resin into Chinese fir wood under different compression ratio. J Northwest Agric For Univ 49, 50–58. Mahhate, Z., Bouamrani, M., Kouail, M., Atmani, R., Yousfi, S., Talbi, M., Brouzi, A., Kenz, A., 2014. Study of transfer process of moisture by wood below the fibersaturation point. IOSR Journal of Applied Chemistry 7(7). 53–56. Manabendra, D., Saikia, C.N., Baruah, K.K., 2000. Treatment of wood with thermosetting resins: eﬀect on dimensional stability, strength and termite resistance. Indian Journal of Chemical Technology 7, 312–317. Nguyen, T.T., Xiao, Z., Che, W., Trinh, H.M., Xie, Y., 2019. Effects of Modification with a Combination of Styrene-Acrylic Copolymer Dispersion and Sodium Silicate on the Mechanical Properties of Wood. Journal of Wood Science 65, 1–11. https://doi.org/doi:10.1186/s10086019-1783-7 Vaziri, M., Dreimol, C., Abrahamsson, L., Niemz, P., Sandberg, D., 2023. Parameter estimation and model selection for water vapour sorption of welded bond-line of European beech and Scots pine. Holzforschung 77(7), 515–526. https://doi.org/10.1515/hf-2022-0013 Shiny, K.S., Sundararaj, R., Vijayalakshmi, G., 2017. Potential use of coconut shell pyrolytic oil distillate (CSPOD) as wood protectant against decay fungi. European Journal of Wood and Wood Products 76 (2), 767–773. https://doi.org/10.1007/s00107-017-1193-8 Tamme, V., Muiste, P., Tamme, H., 2013. Experimental study of resistance type wood moisture sensors for monitoring wood drying process above ﬁbre saturation point, Forestry Studies 59, 28–44. https://doi.org/10.2478/fsmu-2013-0009 Thybring, E.E., Fredriksson, M., 2023. Wood and moisture. In: Niemz P, Teischinger A, Sandberg D (eds) Springer handbook of wood science and technology. Springer International Publishing, Cham, 355–397. https://doi. org/10.1007/978-3-030-81315-4_7 Tsapko, Y., Horbachova, O., Mazurchuk, S., Tsapko, A., Sokolenko, K., Matviichuk, A., 2022. Establishing regularities of wood protection against water absorption using a polymer shell. Eastern-European Journal of Enterprise Technologies 1/10(115), 48–54. https://doi.org/10.15587/1729-4061.2022.252176 Yusof, N., Tahir, P., Seng, H., Khan, M., James, R., 2019. Mechanical and physical properties of cross-laminated timber made from Acacia mangium wood as function of adhesive types. Journal of Wood Science 65(1). https://doi.org/10.1186/s10086-019-1799-z Wang, W., Huang, Y., Cao, J., Zhu, Y., 2017. Penetration and distribution of paraffin wax in wood of loblolly pine and scots pine studied by time domain NMR spectroscopy. Holzforschung 72(2), 12–131. https://doi.org/10.1515/hf-2017-0030 ACKNOWLEDGMENT

This work was supported by the Ukrainian Ministry of Education and Science under Program No. 2201040: “The research, scientific and technological development, works for the state target programs for public order, training of scientific personnel, financial support scientific infrastructure, scientific press, scientific objects, which are national treasures, support of the State Fund for Fundamental Research”. The authors are grateful to Ministry of Education and Science of Ukrainian for financial support of this study. This work was supported by the grant agency VEGA under the projects No. 1/0450/25. This work was supported by the Slovak Research and Development Agency under the contract No. APVV-22-0238. 17

AUTHOR’S ADDRESS Assoc. Prof. Sergiy Kulman, PhD. Assoc. Prof. Anatolii Vyshnevskyi, PhD. Polissia National University Department of Forestry, Forest Crops and Forest Taxation Blvd Stary 7 10008 Zhytomyr, Ukraine Sergiy.Kulman@gmail.com vishnev.tolik@ukr.net Assoc. Prof. Oleksandra Horbachova, PhD. National University of Life and Environmental Sciences of Ukraine Department of Technology and Design of Wood Products Heroiv Oborony str. 15 03041 Kyiv, Ukraine gorbachova.sasha@ukr.net Prof. Ing. Ján Sedliačik, PhD. Technical University in Zvolen Department of Furniture and Wood Products T. G. Masaryka 24 960 01 Zvolen,Slovakia sedliacik@tuzvo.sk

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 19−28, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.02

ASSESSMENT OF THE RELATIONSHIPS BETWEEN FIBER AND MECHANICAL PROPERTIES OF TREE SPECIES CK Muthumala – KKIU Arunakumara – De Silva Sudhira – PLAG Alwis – FMMT Marikar ABSTRACT The variations in mechanical and fiber properties and wood density of seven commonly used timber species in the furniture industry of Sri Lanka were studied. Wood density, compressive strength (parallel to grain and perpendicular to grain), and static bending proportional limit properties were measured. Specifications stated in BS 373: 1957 were used as the standards for the tests. The mechanical property test was performed using a Universal Testing Machine (UTM 100 PC). Fiber analysis was done according to modified Franklin’s method. Regarding density, all fiber properties decreased according to the trend graph. Similarly, no significant correlations were found among fiber properties (fiber length, fiber diameter, and fiber wall thickness) and bending proportional limit, MOR, and MOE. A higher Runkel ratio in high-density timber species was associated with higher strength values. Keywords: density; fiber properties; mechanical test; timber.

INTRODUCTION The history of wood architecture reveals that architects and artisans with natural creative skills have existed from the beginning of civilization. Due to the low quality and strength of the wood used by these ancestral architects and artisans, some of their creations have not lasted long (Ruwanpathirana and Muthumala, 2010). The wood is an excellent material for roofs and other construction works, furniture, interior decorations, doors and window frames, paneling, partition borders, floorings, wood carvings, musical instruments, etc. Mechanical properties are fundamental in determining the suitability of timbers for both structural and non-structural purposes. However, these properties vary with species and other factors, such as moisture content, defect number, and degree. In hardwood, the cells that make up the anatomical organization are the vessels, fibers, parenchyma cells, and wood rays. Fibers are the principal element that is responsible for the strength of the wood (Panshin and Zeeuw, 1980). Fiber length, fiber cell wall thickness, lumen diameter, and pit size are characteristics associated with wood properties such as wood density, modulus of rupture, modulus of elasticity, shrinkage, etc. Wood density is a vital wood property for both solid wood and fiber products (De Guth, 1980). Softwood fibers are generally long (2-3 mm) (Bardage, 2001, Brandstrom et al., 2003), while hardwood fibers are shorter (1 mm) and less flexible (Tabarsa, 2001). 19

The Runkel ratio, the ratio between fiber cell wall thickness and lumen, determines the suitability of a fibrous material for pulp and paper production. If a wood species has a high Runkel ratio, its fibers are stiff and less flexible, and have poor bonding abilities. The variations in mechanical and fiber properties of seven timber species commonly used in the furniture industry in Sri Lanka were studied in this experiment.

MATERIALS AND METHODS Commonly used seven tree species for furniture manufacturing were collected from the Southern and Central provinces of Sri Lanka (Table 1). Tab. 1 Selected timber species for identifying the joint efficiencies. Common NameBotanical Name

Family

Grandis Eucalyptus grandis

Myrtaceae

Jack

Timber Class* Collected Province

Artocarpus heterophyllus Moraceae

Class-2 Central Luxury

Southern

Kumbuk Terminalia arjuna

Combretaceae

Special Southern

Mahogany

Swietenia macrophylla

Meliaceae

Luxury

Pine

Pinus caribaea

PinaceaeClass-3 Central

Satin

Chloroxylon swietenia

Rutaceae

Luxury

Southern

Teak

Tectona grandis

Lamiaceae

Super Luxury

Southern

*Source: Timber classification of State Timber Corporation, Sri Lanka

Determination of wood density Each tree species was replicated ten times. Wood density was determined based on green volume and oven-dry weight. The dry weight of the timber samples was taken by placing them in an oven at 105 0C for 48 hours (BS EN 373:1957). The density was calculated using Equation 1. Density = Weight of oven-dried wood (kg)

(1)

Volume of wood (m3) Samples placed at normal room temperature conditions showed better structural performance than those under hot, wet conditions (Vivek et al, 2016). Determination of moisture content The specimens (each 20 x 20 x 20 mm) were first weighed and then oven-dried at 103 0C until constant weight. The moisture content (r) of each sample was determined using Equation 02 given below. 𝑟=

𝑀𝑟 −𝑀0 𝑀0

× 100

(2)

Where: r is the moisture content of the sample (%), Mr is the moist weight of the sample, and M0 is the fully dried mass of the sample. Measuring the fiber dimensions Fiber morphological analysis was done using the modified Franklin’s method (Franklin, 1945). In preparation for the timber slides containing fibers, the matchstick-sized 20

splints were taken from the tangential section of timber samples and put into boiling tubes containing a mixture of glacial acetic acid and 30% hydrogen peroxide (1:1 by volume). The purpose of using hydrogen peroxide was to ensure dehydration and bleaching of the samples. The glacial acetic acid was used to dissolve the lignin, enabling easy separation of the fibers (Fig. 1). The material in the boiling tubes transformed into a pulp when the temperature was maintained at 65°C for 24 h. Then, the remains were rinsed in distilled water and shaken gently to ensure that individual cells of xylem tissue were measurable. Fibers were carefully removed with a paintbrush and mounted on slides with Canada balsam. They were then covered with cover slips, named, and kept in an oven at 30 0C for two days to complete drying. Microscopic views were taken to measure fiber thickness, lumen diameter, and wall thickness. The fiber dimensions were measured subjectively to minimize the possible variations in the fibers, which could occur due to factors such as the age of the tree and the sampling height of the tree, etc. (Smook, 2003; H’ng et al., 2016). Micrometrics SE Premium 4.1 software was used to determine the fiber dimensions. Calculation of Runkel ratio Runkel ratio was calculated using the Equation 3 (Smook, 2003). Runkel ratio= D2-D1 D2 Where: D2- Cell thickness, D1-Lumen diameter; D2-D1=Cell wall thickness.

(3)

Fig.1 Preparation of slides for measuring fiber properties – A, Matchstick size splints taken from timber samples; B, Small timber samples dipped in the mixture; °C, Rack with test tubes kept at 60°C; D, Test tubes after dissolving the lignin; E, Mounting the slides with Canada balsam; F, Determination of fiber dimensions.

Determination of flexural strength Specimens were cut from defect-free, seasoned wood planks (average moisture content 12%). 10 wood specimens were made, one for each tree species. The size of each replicate was 20 x 20 x 300 mm. Specimens were prepared according to the testing methods for small transparent specimens as stated in BS 373:1957.

The Universal Testing Machine (UTM-100), manufactured in Australia, was used for testing (Fig. 2). An assembly pressure of 6 MPa was used in this study (Castro & Paganini, 1997; Min-Chyuan et al., 2011).

Fig. 2 Universal Testing (UTM-100PC-Australia).

Bending proportional limit strength, Modulus of Rupture (MOR), and Modulus of Elasticity (MOE) values were calculated using Equations 4, 5, and 6, respectively, corresponding to the test data. 3𝐹1 𝐿1 Bending proportional limit Strength = 2𝑏𝑑 (4) 2 Where: F1 = Serviceability Force (N); L1 = Length of the span (mm); b = Width of the specimen (mm); d = Depth/Thickness of the specimen (mm). MOR =

3𝐹2 𝐿1 2𝑏𝑑

(5)

Where: F2= Maximum Force (N); L1 = Length of the span (mm); b = Width of the specimen (mm); d = Depth/Thickness of the specimen (mm). F L 3

3 1 MOE = 4δbd 3

Where: F3= Maximum load at proportionate state (N); L1= Length of the beam between supports (mm); b = width of the specimen (mm); d= Depth/ Thickness of the specimen (mm); 𝛿= Deflection of timber specimen (mm); Calculation of Compression Strength Prepared specimen for compression parallel to grain are shown in Fig. 3 (a).

(6)

Fi. 3 Schematic presentation of compression tests (a) Compression parallel to grain (b) Compression perpendicular to grain specimen.

The load was applied to the timber section at a proportional state. Serviceability compressive strength was calculated using Equation 07. The Force direction of the specimen is shown in Fig. 4 and Fig.5. Serviceability compressive strength of the specimen =

Max.Load act on specimen at Proportionate state N/mm2 Load acting area

Compression parallel to grain

Fig. 4 Compression parallel to grain test. (a) Loading setup (b) Load applying direction.

Fig. 5 Loading setup used in Compression perpendicular to grain test.

Joint direction is highlighted in the figure 4 and 5 as above. 23

(7)

RESULTS AND DISCUSSION The fiber properties of six hardwood species and one softwood species were compared as shown in Table 2. Tab. 2 Fiber properties of timber species.

1147.72

Average Fiber diameter (40X) m 20.64

Average Lumen diameter (40X) m 13.47

2070.94

22.35

12.34

756

1613.15

18.43

Mahogany

570

1431.68

Timber species

Density (kg/m3)

Average fiber length (40X) m

Grandis

570

Jack

645

Kumbuk

Fiber wall thickness (40X) m

Runkel Ratio

3.59

0.35

5.00

0.45

11.15

3.64

0.39

20.48

13.82

3.33

0.33

Pine

465

3387.86

44.53

27.79

8.37

0.38

Satin

980

1225.43

11.28

4.92

3.18

0.56

Teak

720

1203.77

22.14

14.12

4.01

0.36

Runkel ratio

The highest average fiber length (3387.86 mm) was recorded in Pine, and the least (1147.72 mm) was from Grandis. Concerning average fiber diameter, the highest value (44.53 mm) was recorded in Pine, and the lowest (11.28 mm) was from Satin. The highest average lumen diameter (27.79 mm) was recorded in Pine, and the least (4.92 mm) was from Satin. For average fiber wall thickness, the highest measurement (8.37 mm) was recorded in Pine, and the lowest (3.18 mm) was in Satin. The thickness of the fiber cell wall is the primary factor governing the density and mechanical strength of hardwood timbers (Wiedenhoeft, 2010). The present study shows a similar trend; the Runkel ratio varies from 0.35 to 0.56. Satin recorded the highest (0.56) Runkel ratio (Figure 6).

Runkel Ratio Lineárna (Runkel Ratio)

Density Fig. 6. Relationship between densities vs. runkel ratio.

Average fiber length

Fiber properties

Average Fiber diameter Average Lumen diameter

Fiber wall thickness Lineárna (Average Lumen diameter ) Lineárna (Average Lumen diameter )

Density (kg/m3)

Fig. 7. Relationship between densities vs. fiber properties.

Average density values of seven tree species varied as Satin (980 kg/m3), Kumbuk (756 kg/m3), Teak (720 kg/m3), Jack (645 kg/m3), Grandis (570 kg/m3), Mahogany (570 kg/m3), and Pine (465 kg/m3) in descending order. As depicted in Figure 6, decreasing trends were observed in the relationships between the fiber properties and the densities. A similar trend was observed in previous research by Kiaei and Moya (2015). The effect of fiber dimension on the wood density of three parts (stem, branch and root wood) of alder wood was determined by Kiaei and Moya in the stem, branch, and root wood of Alnus glutinosa L and results emphasis that a significant differences were not found between fiber length, fiber diameter and lumen diameter with wood density for each of wood samples. In contrast, in the total of wood samples, there is a significantly negative relationship between fiber length, fiber diameter, and lumen diameter with wood oven-dried densities. Mechanical properties of the seven selected tree species are shown in Table 3. Tab. 3 Strength values of the mechanical tests. Timber species

Compression parallel to grain (N/mm2)

Grandis

45.19

Compression perpendicular to grain (N/mm2)

MOR (N/mm2)

Bending (N/mm2)

4.91

71.13

36.56

8203.65

MOE (N/mm2)

Jack

41.02

13.42

64.47

36.55

5765.51

Kumbuk

33.81

7.39

52.86

21.21

4615.56

Mahogany

30.31

8.20

60.16

32.58

5775.78

Pine

45.78

5.53

59.90

28.56

7149.67

Satin

46.36

16.65

106.60

50.85

10819.05

Teak

47.40

9.20

84.36

44.36

8538.29

The proportional limit is the deformation of a material or structural element when a load is applied perpendicular to its length, causing it to curve or deflect. In contrast, Modulus of Rupture (MOR) is a material property that measures the maximum stress a material can withstand in bending, proportional to its proportional limit before it breaks, often determined through a flexural test. While the bending proportional limit describes behavior under load, MOR quantifies the breaking point under that load, making it especially 25

important for assessing the strength of brittle materials like wood, concrete, or ceramics. The highest strength value in the compression parallel to grain test (47.40 N/mm2) was recorded in the Teak specimen, and the lowest (30.31 N/mm2) was in the Mahogany specimen. Satin and Pine, respectively, recorded the highest (16.65 N/mm2) and the lowest (5.53 N/mm2) strength values of the compression perpendicular to grain tests. About the bending proportional limit strength, the highest value (50.85 N/mm2) was recorded in Satin, while the lowest (21.21 N/mm2) was shown in Kumbuk. Satin and Kumbuk recorded the highest (106.6 N/mm2) and the lowest (52.86 N/mm2) modulus of rupture strength values. For the modulus of elasticity, the highest stiffness value (10819.05 N/mm2) was recorded in Satin, and the lowest (4615.56 N/mm2) was shown in Kumbuk. Tab. 4 Regression R-sq. values of fiber properties of test tree species. Mechanical Test

Fiber properties

R-Sq.

R-Sq. (adj)

Sig. P value

MOR

Fiber length

20.6%

4.8%

0.306

bending proportional limit

Fiber length

21.1%

5.4%

0.299

MOE

Fiber length

8.7%

0.0%

0.521

bending proportional limit

Average fiber diameter

19.5%

3.4%

0.321

MOR

Average fiber diameter

23.4 %

8.1 %

0.237

MOE

Average fiber diameter

5.6%

0.0%

0.608

bending proportional limit

Fiber wall thickness

11.2%

0.0%

0.463

MOR

Fiber wall thickness

12.3%

0.0%

0.440

MOE

Fiber wall thickness

2.1%

0.0%

0.754

Com. parallel to grain

Fiber length

1.1%

0.0%

0.821

Com. parallel to grain

Fiber diameter

4.1%

0.0%

0.662

Com. parallel to grain

Fiber wall thickness

9.8%

0.0%

0.493

Com. perpendicular to grain

Fiber length

6.9%

0.0%

0.569

Com. perpendicular to grain

Fiber diameter

31.6%

17.9%

0.189

Com. perpendicular to grain

Fiber wall thickness

10.6%

0.0%

0.477

No significant correlations among fiber properties (fiber length, fiber diameter, and fiber wall thickness) with strength values (compression parallel to grain and compression perpendicular to grain) are observed (Sig. P value > 0.05). Similarly, no significant correlations were found among fiber properties (fiber length, fiber diameter, and fiber wall thickness) vs. bending proportional limit, MOR, and MOE (Sig. P value > 0.05) (See Figure 7). A previous study by Jan Baar et al. in 2014 revealed a weak correlation between density and the MOR. 26

However, according to the research conducted by Bhat et al. (2001), regarding the fiber length of Teak, the wet-site home-garden exhibited shorter fibers (1.16 mm) than the dry and plantation sites, with values of 1.24 mm each (Bhat et al., 2001). Hence, selected sites of the specimens also contributed to these results. Another study showed that nutrient distribution had a significant positive correlation with wood quality, wood density, and fiber length (Rizki and Andrian, 2015).

CONCLUSION The relationships between fiber properties and mechanical properties of seven tree species: Grandis (Eucalyptus grandis) and Jack (Aartocarpus heterphyllus), Kumbuk (Terminalia arjuna), Mahogany (Swietenia macrophylla), Pine (Pinus caribaea), Satin (Chloroxylon swietenia), and Teak (Tectona grandis) were assessed in the study. The highest average fiber length, fiber diameter, lumen diameter, and fiber wall thickness were recorded in Pine (Softwood species). No significant correlations among fiber properties (fiber length, fiber diameter, and fiber wall thickness) and compression tests (compression parallel to grain and compression perpendicular to grain) were observed. Satin shows the highest mechanical strength, the highest runkler ratio, and the highest density value. REFERENCES Baar, J., Tippner, J., Rademacher, P., 2014. Prediction of mechanical properties - modulus of rupture and modulus of elasticity - of five tropical species by nondestructive methods, Maderas. Ciencia y tecnología 17(2): 239 - 252, 2015 Bardage, S.L., 2001. Three-dimensional modeling and visualization of whole Norway spruce latewood tracheids. Wood and Fiber Science, vol. 33, 627-638. Bhat, K. M., Thulasidas, P. K., 2012. Mechanical properties and wood structure characteristics of 35-year old home-garden teak from wet and dry localities of Kerala, India in comparison with plantation tea, J Indian Acad Wood Sci (June 2012) 9(1):23–32, J Indian Acad Wood Sci (June 2012) 9(1):23–32. BSI, 1999., BS 373: 1957; Methods of testing small clear specimens of timber. British Standards Institution. London. pp.1. Brandström, J., Bardage, S.L., Daniel, G., Nilsson, T., 2003. The structural organization of the S1 cell wall layer of Norway spruce tracheids. IAWA Journal, vol. 24, 27-40. Castro1, G. Paganini, F., 1997. Parameters affecting end finger joint performance in poplar wood. International Conference of IUFRO, Copenhagen, Denmark. De Guth, E.B., 1980. Relationship between wood density and tree diameter in Pinus selliottii of Missionnes Argentina. IUFRO Conf. Deiv.5 Oxford. Franklin, G. L., 1945. Preparations of the sections of synthetic resin and wood resin composites, and a new macerating method for wood. Nature 155(3924):51-59. H’ng, P.S., Li,K.L., Cheng, Z. Z., Tang, C. H., Wong, Y. S., Foo, S. L., Aw, T. H., Wan, K.F., 2016. Anatomical Features, Fiber Morphological, Physical and Mechanical Properties of Three Years Old New Hybrid Paulownia: Green Paulownia. Research Journal of Forestry, Res. J. For., 10 (1): 30-35. Kiaei, M., Moya, R., 2015. Physical properties and fiber dimension in stem, branch and root of alder wood, PSP Volume 24 – No 1b. 2015 Fresenius Environmental Bulletin, 24(1B):335-342. Maharani, R., Fernandes, A., 2015. Correlation between wood density and fiber length with essential macro-nutrients on base of stem of Shorea leprosula and Shorea parvifolia, The 3rd International Conference on Biological Science 2013.

Min-ChyuanY., Yu-L., Lin, Yung-Chin H., 2011. Evaluation of the Tensile Strength of structural Finger-Jointed Lumber, Taiwan J for Sci 26(1).www.airtilibrary.com. pp.59-70. Muthumala, C.K., Amarasekara, H.S., 2013. Investigation the Authenticity of Local and Imported timber Species in Sri Lanka, Proceeding of the International Forestry and Environment symposium, Dept. of Forestry and Environmental Science, University of Sri Jayewardenepura, p. 95. Panshin, A.J., De Zeeuw, C., 1980. Textbook of wood technology. 4 ed, NY: McGraw-Hill. Pp. 722. Ruwanpathirana, N.D., Muthumala, C. K., 2010. Wooden Wonders of Sri Lanka, State timber Corporation. Smook, G.A., 2003. Handbook for Pulp and Paper Technologists. 3rd Ed., Angus Wilde Publications, Vancouver, B.C., ISBN-13:978-0969462859. Tabarsa, T., Chui, Y.H., 2001. Characterizing microscopic behavior ofwood under transverse compression. Part II. Effect of species and loading direction, Wood and Fiber Science, vol. 33. pp 223-232. Vievek, S., De Silva, S., De Silva, G.H.M.J., Muthumala, C.K., 2016. Finger Joints and their Structural Performance in Different Exposure Conditions, 7th International Conference on Sustainable Built Environment, Kandy, Sri Lanka. Wiedenhoeft, A., 2010. Structure and Function of Wood, Wood Handbook, 3-1, Forest Products Laboratory, United States Department of Agriculture Forest Service, Forest Products Laboratory, Forest Service, Department of Agriculture, United States.

AUTHORS’ ADDRESSES CK Muthumala PhD, Research, Development and Training Division, State Timber Corporation, Sri Lanka ckmuthu@stc.ac.lk KKIU Arunakumara PhD, Department of Crop Science, Faculty of Agriculture, University of Ruhuna, Sri Lanka kkaruna@ruh.ac.lk De Silva Sudhira PhD, Department of Civil and Environmental Engineering, Faculty of Engineering, University of Ruhuna, Sri Lanka sudhirad@ruh.ac.lk PLAG Alwis PhD, Department of Engineering, Faculty of Agriculture, University of Ruhuna, Sri Lanka alwispl@ruh.ac.lk FMMT Marikar PhD, General Sir John Kotelawala Defence University, Ratmalana, Sri Lanka faiz@kdu.ac.lk

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 29−37, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.03

EVALUATION OF THE MECHANICAL PROPERTIES OF POPLAR LAMINATED VENEER LUMBER (LVL) REINFORCED WITH OAK, BEECH, AND EUCALYPTUS VENEERS Bekir Cihad Bal ABSTRACT Structural composite lumber is produced from various tree species, and numerous laboratory studies have examined its mechanical properties. In this study, LVL boards were produced using poplar, oak, beech, and eucalyptus veneers in the outer layers and poplar veneers in the middle layers. Melamine-urea-formaldehyde adhesive was used in the production of the boards. The modulus of rupture, modulus of elasticity, splitting strength, compression strength perpendicular to the grain, hardness, and screw holding capacity of the produced boards were determined. According to the obtained data, test specimens with oak, beech, and eucalyptus as outer layers had higher mechanical properties than the control group. Furthermore, the modulus of rupture and modulus of elasticity of LVL boards with oak on the top and bottom surfaces were 50% and 99% greater than those of the control group, respectively. However, no significant increase in splitting strength was found. Keywords: LVL; Poplar veneer; Reinforcement; SCL.

INTRODUCTION Solid wood and wood-based materials are widely used in wooden structures. These materials are classified in various ways. Based on its technological composition, structural wood is divided into solid wood, modified wood, and wood composites, including laminated structural wood, veneer-based structural wood, agglomerated structural wood, and combined structural wood (Vaňová and Štefko 2021). Structural composite lumber holds a special place in these classifications. Structural composite lumber consists of four different materials: Laminated Veneer Lumber (LVL), Parallel Strand Lumber (PSL), Oriented Strand Lumber (OSL), and Laminated Strand Lumber (LSL). Today, LVL is the most widely produced and used structural composite lumber. LSL, on the other hand, makes the most efficient use of raw wood materials. These types of lumber are used in structural applications as girders, beams, headers, joists, studs, and columns (Nelson, 1997). LVL is produced under various trade names, such as Micro-Lam, Versa-Lam, and Kerto-LVL. It is primarily used in the construction of wooden houses, wooden commercial buildings, and other wooden structures. LVL has been used as a load-bearing structural composite lumber in wooden structures. However, it is now also being used as a load-bearing panel in wooden structures. For example, the Kerto® LVL Q-panel is produced for this purpose (URL 1, 2025). Numerous scientific studies have examined the physical and mechanical properties of LVL. For example, Bao et al. (2001) investigated some of the mechanical properties of LVL 29

produced from three different poplar clones and also compared LVL with solid wood by calculating the contribution factor. Çolak et al. (2007) investigated the effects of the steaming, aging, and drying conditions on the mechanical properties and durability of LVL and solid lumber from beech and spruce. Erdil et al. (2009) compared the mechanical properties of solid wood and laminated veneer lumber produced from Turkish beech, Scots pine, and Lombardy poplar. The adhesive type and wood species had significant effects on the mechanical properties of the LVL specimens. Kurt et al. (2011) investigated the impact of the pressure duration on some selected properties of LVL. Kurt and Çil (2012) determined the effects of the press pressure on the glue line thickness and some selected properties of LVL. Bal and Bektaş (2012) investigated the impact of hot-setting adhesives on the bending properties of LVL. Hashim et al. (2011) investigated the effects of cold-setting adhesives on the properties of LVL produced from oil palm wood and rubber wood. In addition, De Melo et al. (2015), Bal and Bektaş (2012), and Altınok (2019) investigated the effects of adhesive type on selected properties of LVL. De Melo et al. (2014) investigated the impact of veneer thickness on the physical and mechanical properties of LVL. In addition to studies investigating the effects of factors such as wood type, glue type, press pressure, and press time on selected properties of LVL (some of which were listed above), studies on LVL reinforcement have also been conducted. For example, Larson et al. (1987) investigated the effect of butt joint reinforcement in parallel-laminated veneer lumber (LVL). Wei et al. (2013) investigated the mechanical properties of poplar LVL reinforced with carbon fiber. Bal (2014) produced poplar LVL reinforced with glass fiber fabric and investigated its mechanical properties. Wang et al. (2015) made three types of reinforced LVL, including a carbon fiber-reinforced polymer (CFRP) sheet, glass fiber-reinforced polymer (GFRP) mesh, and a composite of the CFRP sheet and GFRP mesh, and evaluated the mechanical properties of the LVL. Bal (2021) reported some of the mechanical properties of LVL strengthened with a glass fiber net. Perçin (2023) investigated the compression strength parallel to the grains of heat-treated LVL reinforced with carbon fiber. Opazo-Vega et al. (2025) investigated the elastic properties of LVL panels produced from pine veneers reinforced with carbon and basalt fibers. In other studies, researchers investigated the reinforcement effect of using wood veneers with higher mechanical performances. For example, Wong et al. (1996) investigated the properties of rubber wood LVL reinforced with acacia veneers. H’ng et al. (2010) investigated some selected mechanical properties of LVL panels made from low-density wood species reinforced with Keruing veneers. Sulastiningsih et al. (2020) investigated some of the mechanical properties of oil-palm wood-based LVL reinforced with jabon and mahoni wood veneers. A review of the previous studies cited above demonstrates that the effects of factors such as the wood species, veneer thickness, layer composition, adhesive type, press pressure, and press time on the mechanical properties of LVL have been extensively investigated. Furthermore, numerous studies have been conducted on reinforcing LVL with glass, carbon, and natural fibers. However, the reinforcement of low-performance wood species with veneer sheets derived from high-performance wood species has not been sufficiently investigated. Therefore, the aim of this study was to investigate the mechanical properties of poplar LVL faced with oak, beech, and eucalyptus veneers.

MATERIALS AND METHODS Material

In the study, 3 mm-thick veneers were obtained from the following tree species: poplar (Populus spp.), oak (Quercus petraea), beech (Fagus orientalis), and eucalyptus (Eucalyptus 30

grandis). These veneers were obtained using the rotary-cut method. The prepared veneer boards were 30 × 30 cm, and 6 veneers were used for each board. The average density of the poplar, oak, beech, and eucalyptus veneers was 388 kg/m 3, 615 kg/m3, 589 kg/m3, and 572 kg/m3, respectively. Flawless veneers without cracks, knots, and rot were selected. In this study, one control group (with poplar veneer in all layers) and three experimental groups (with surface layers of oak, beech and eucalyptus veneers) were created, as shown in Fig. 1.

Group 1

Poplar Poplar Poplar Poplar Poplar Poplar

Group 2

Group 3

Oak Poplar Poplar Poplar Poplar Oak

Beech Poplar Poplar Poplar Poplar Beech

Group 4

Eucalyptus Poplar Poplar Poplar Poplar Eucalyptus

Fig. 1 LVL groups and veneer lay-up schemes.

MUF resin was used as the adhesive in this study. The adhesive was supplied by Polisan A.Ş. The adhesive had a solid percentage of 55±1%, viscosity (Cps at 20°C) of 150– 350, pH of 9.0–9.2, density (at 20°C) of 1.230 kg/m3, and jel time of 25-35 s (at 100°C). The adhesive was applied to the veneer surfaces without using any additives or fillers. Production of LVL panels To produce LVL boards, the loose surfaces of the veneer boards were first identified, and adhesive was applied with a brush. After gluing the veneer boards, the loose surfaces were positioned toward the center of the board. Almost 200 ± 10 g/m 2 of adhesive was used on the veneer surfaces. After gluing, the boards were placed in a hot press and a pressure of 5.5 kg/cm² was applied at 120°C for 18 min. Five LVL boards were produced for each group. The boards removed from the press were left to stand for one week, stacked, and then test samples were prepared. Method The bending test, splitting strength, compressive strength perpendicular to the grain, Janka hardness, screw holding capacity, and tensile shear strength (TSS) of the LVL test specimens were determined according to standards TS 2474, TS 7613, TS 2473, TS 2479, TS EN 13446, and TS EN 314-1, respectively. Bending test specimens were prepared with a board thickness of 1.5 cm, a width of 2 cm, and a length of 30 cm. Three test specimens were prepared from each board for each test, for a total of 15. Bending tests were conducted on a 10 kN capacity universal testing machine (UTM), as shown in Fig. 2. During the bending test, a force was applied to the side surface in an edgewise position. The test speed was 5 mm/min, the distance between the supports was 24 cm, the preload was 10 N, and the endpoint was 75% of the maximum force. In the splitting strength test, a 50 × 70 mm test specimen was prepared. A 32 mm diameter hole was drilled on one short side, and a tensile force was applied through this hole. A 20 × 20 × 15 cm (length × width × thickness) specimen was prepared to test the compressive strength perpendicular to the grain. The test was terminated when a fracture occurred in the test specimen or when the load decreased to 75% of the maximum force. A Janka test was performed to determine the static hardness. The penetration depth of the test head into the test specimen was set at 2.82 mm. To determine the screw holding capacity, test specimens were prepared with a square cross-section of 50 × 50 mm and a thickness equal to the board thickness. Zinc screws measuring 4 × 50 mm were used in the tests. The screws were screwed into the surface at the midpoint of the test specimen. 31

During the screw holding capacity tests, the preload was 10 N, the test speed was 5 mm/min, and the test endpoint was set at 75% of the maximum force. For the TSS tests, 12 test samples were prepared for each glue line (second, third, and fourth), totaling 72. The TSS tests were conducted on 15 air-dried samples and 15 samples treated with cold water. The treatment with cold water lasted 24 hours. During this time, the test samples were submerged in cold water. The samples were tested immediately after the treatment process was completed.

Fig. 2 Bending test and image of the test machine.

Statistical calculations The data were organized in Excel and analyzed using a one-way ANOVA in SPSS to determine whether there were differences among the groups. The Duncan test was used to determine whether any groups differed significantly from each other in the statistically significant data.

RESULTS AND DISCUSSION The air-dried densities of the LVL boards were calculated and are presented in Table 1. As shown, the average air-dried density values for the groups ranged from 417 to 511 kg/m3. The lowest density was measured in Group 1 (417 kg/m 3), with the highest measured in Group 2 (537.9 kg/m3). An ANOVA test was performed to determine whether there was a statistically significant difference between the air-dried density values of the groups. The difference between the groups was statistically significant (P < 0.001). When the density values given in Table 1 were compared with the mechanical properties shown in the following tables, it could be seen that the LVL groups with higher densities (Groups 2 and 3) exhibited higher mechanical properties. Previous studies reported that LVL density affects its mechanical properties, and that higher mechanical properties are obtained from LVL with higher density (Erdil 2009; Bal 2012). However, this is not true for every mechanical property. In addition to density, the fiber structure, wood type (mature vs. young), the degree of fibrousness, and the distribution of wood cells can also affect the properties. It is particularly evident in the splitting strength test results. Tab. 1 Density test data, ANOVA P value, and Duncan test results. Group 1 Group 2 Group 3 Group 4 P value x̄ 417.6 A* 537.9 C 522.6B C 511.1 B 0.000 sd 29.2 20.5 40.7 19.3 x̄ : arithmetic mean, sd: standard deviation, *: lowest value, with different letters (*A, B, C) indicating significant differences in Duncan test results. Density (kg/m3)

The findings of the bending tests (Modulus of Rupture and Modulus of Elasticity) are given in Table 2. As shown, the modulus of rupture values for the test specimens ranged from 63 to 97 N/mm2. The difference between the groups was statistically significant (P < 0.001). The highest bending strength values were measured in Groups 2 and 3, with the smallest measured in Group 1. Compared with the control group, the increases in bending strength for Groups 2 and 3 were approximately 50%. Similar results were obtained for the modulus of elasticity. The smallest modulus of elasticity was 5310 N/mm 2 in Group 1, and the highest was 10595 N/mm 2 in Group 2. The difference between the groups was statistically significant (P < 0.001). Compared with the control group, the experimental groups showed approximately 97–99% increases in modulus of elasticity. The ratio of the oak, beech, or eucalyptus veneer to the poplar veneer used in the experimental groups was one-third. Of the six veneer panels, four were made of poplar and two of other wood species. Despite this, the bending performance of the experimental groups was statistically significantly better than that of the control group. Similar results have been obtained in previous studies on this subject. For example, Wong et al. (1996) investigated the properties of rubberwood-based LVL reinforced with Mangium veneers. They reported that the bending properties of 5-ply rubberwood LVL reinforced with Mangium were significantly greater than those of unreinforced LVL, while those of 3-ply LVL were not. The MOR value for the 5-ply with reinforcement was 13% higher than that without reinforcement. Sulastiningsih et al. (2020) investigated some of the mechanical properties of oil-palm wood veneer-based LVL reinforced with jabon and mahoni wood veneers, and reported favorable results. In addition, H’ng et al. (2010) investigated the effects of incorporating Keruing veneers into LVL panels made from low-density wood species such as Pulai, Sesendok, and Kekabu Hutan. They reported that the presence of Kruing veneers as surface layers significantly increased the bending strength of the LVL panels. In previous studies on reinforcing LVL boards with glass or carbon fiber, the increase in flexural properties with reinforcement remained below 50% (Larson et al., 1987; Wei et al., 2013; Bal 2014; Bal et al., 2015; Wang et al., 2015; Sokolović, 2023; Opazo-Vega et al., 2025). In this case, reinforcing LVL sheets produced with veneer sheets with lower mechanical performance with veneer sheets with higher mechanical performance yielded better results than reinforcing them with synthetic fibers. Tab. 2 Bending test data, ANOVA P value, and Duncan test results. Modulus of Rupture (N/mm2)

x̄ sd

Group 1 63.6 A* 4.8

Group 2 97.4 C 7.2

Group 3 97.4 C 12.3

Group 4 87.3 B 10.7

P value 0.000 -

Modulus of Elasticity x̄ 5310.9 A 10595.0 B 10117.9 B 10498.9 B 0.000 (N/mm2) sd 358.9 449.3 1003.0 1171.9 x̄ : arithmetic mean, sd: standard deviation, *: lowest value, with different letters (*A, B, C) indicating significant differences in Duncan test results.

The compression strength perpendicular to the grain test data, ANOVA P-values, and Duncan test results are presented in Table 3. As seen, the lowest compressive strength was measured in Group 1, and the highest was found in Group 3. The differences between the groups were statistically significant (P < 0.001). The higher compressive strength in Group 3 was due to the more homogeneous fiber structure of beech veneers compared to oak and eucalyptus veneers. Wood fibers are distributed homogeneously both along the length of the tree and from the pith to the bark. However, the greater presence of core rays in oak veneers affects the compressive strength. LVL material is used for structural members such as 33

girders, beams, headers, and joists, where the load acts perpendicular to the fibers. Therefore, LVL material must have a high perpendicular-to-grain compression strength. In experimental groups, the use of oak, beech, and eucalyptus veneers on the top and bottom surfaces increased the compressive strength. However, this increase was not as significant as the increases in the flexural strength and modulus of elasticity in Groups 2 and 4. Only Group 3 achieved a 48% increase. However, even this increase was better than the increases in compressive strength obtained in reinforcement studies using glass or carbon fiber (Perçin, 2023; Perçin, 2025). Tab. 3 Compression strength test data, ANOVA P value, and Duncan test results. Group 1 Group 2 Group 3 Group 4 P value x̄ 9.0 A 11.1 B 13.3 C 11.0 B 0.000 Compression strength (N/mm2) sd 1.6 1.2 2.0 1.5 x̄ : arithmetic mean, sd: standard deviation, *: lowest value, with different letters (*A, B, C) indicating significant differences in Duncan test results.

The screw holding capacity test data, ANOVA P values, and Duncan test results are given in Table 4. As seen in the table, the screw holding capacities of the control and experimental groups were statistically significantly different (P < 0.001). According to the Duncan test results, there was no difference between the experimental groups. The effects of the veneer types used in the experimental group on screw holding capacity were the same. The increase in screw holding capacity of the experimental groups compared to the control group was approximately 43%. This result was quite striking. In a reinforcement study using glass fiber (Bal, 2021), no such increase was reported, even in the experimental group in which glass fiber was used in all adhesive layers. Glass fiber reinforcement had a small effect on the screw-holding capacity of LVL panels. However, the impact of strengthening using stronger veneer sheets on the top and bottom surfaces, as in the presented study, is greater. Tab. 4 Screw holding capacity test data, ANOVA P value, and Duncan test results. Group 1 Group 2 Group 3 Group 4 P value x̄ 23.5 A 32.8 B 34.5 B 32.6 B 0.000 Screw holding capacity (N/mm2) sd 1.9 4.2 5.5 2.6 x̄ : arithmetic mean, sd: standard deviation, *: lowest value, with different letters (*A, B, C) indicating significant differences in Duncan test results.

The splitting strength test data, ANOVA P-values, and Duncan test results are presented in Table 5. As shown, the lowest splitting strength (0.52 N/mm 2) was observed in Groups 1 and 2, and the highest splitting resistance was observed in Group 3. In fact, the other mechanical performances for the oak veneer used in Group 2 were quite high. However, its splitting resistance was low. This was due to the high number of core rays in oak wood, as shown in Fig. 3. These core rays extend from the pith to the bark, facilitating radial splitting of the wood. It is particularly problematic in veneer boards. For this reason, while the contributions of the oak veneer to the other mechanical properties of LVL boards were quite high, its effect on the splitting resistance was insufficient. Tab. 5 Splitting strength test data, ANOVA P value, and Duncan test results. Group 1 Group 2 Group 3 Group 4 P value x̄ 0.52 A 0.54 A 0.70 C 0.63 B 0.000 sd 0.09 0.07 0.09 0.08 x̄ : arithmetic mean, sd: standard deviation, *: lowest value, with different letters (*A, B, C) indicating significant differences in Duncan test results. Spliting strenght (N/mm2)

Fig. 3 Post-test images of splitting strength test samples (from left to right: Groups 1-4).

The Janka hardness test data, ANOVA P-values, and Duncan test results are presented in Table 6. As shown, the lowest hardness value was measured in Group 1 (21.7 N/mm 2), and the highest was measured in Group 2 (35.8 N/mm 2). The surface hardness of Group 2 increased by 65% compared to the control group. The differences between the groups were statistically significant (P < 0.001). The hardness values of wood samples from oak species are generally higher than those of most other wood species. One study reported a Janka hardness of 62 N/mm2 for the tangential surface of oak (Ayata and Bal, 2019). In other words, the hardness value of the solid wood is much higher. However, in the present study, the hardness value measured only on the top surface of the LVL board, in the 3 mm-thick oak veneer and underlying poplar veneer, was 35.8 N/mm2. Tab. 6 Janka hardness test data, ANOVA P value, and Duncan test results.

Janka hardness (N/mm2)

x̄ sd

Group 1

Group 2

Group 3

Group 4

P value

21.7 A 4.6

35.8 D 5.2

29.5 C 3.6

25.9 B 2.8

0.000

x̄ : arithmetic mean, sd: standard deviation, *: lowest value, with different letters (*A, B, C, D) indicating significant differences in Duncan test results

The adhesion performance of the poplar veneers in the center of the LVL boards was determined in a tensile-shear test and is presented in Table 7. As seen, both the air-dried and wet test samples exceeded the 1 N/mm 2 limit. This adhesion strength indicated good adhesion between the poplar veneers. Therefore, the percentages of wood fracture or glue failure, as specified in the relevant standard, were not determined. Furthermore, the adhesion strengths between the oak, beech, and eucalyptus veneers on the outer surfaces and the poplar veneer were not calculated because these were the outermost portions of the test samples. Furthermore, the primary purpose of this study was not to evaluate the adhesion performance of poplar veneers with other wood veneers. Tab. 7 Adhesion strength test data of group 1. x̄ Adhesion strength (N/mm2) sd x̄ : arithmetic mean, sd: standard deviation.

Air-dried test samples 3.2 5.3

Wet test samples 1.1 3.8

CONCLUSION In this study, the mechanical properties of poplar LVL boards produced by bonding oak, beech, and eucalyptus veneer sheets to their top and bottom surfaces (tension and compression zones) were compared with LVL boards produced with all of the layers made of poplar. The findings indicated that the density, modulus of rupture, modulus of elasticity, screw holding capacity, splitting strength (except for the oak group), compressive strength, and Janka hardness values of the LVL boards with oak, beech, and eucalyptus veneers on their top and bottom surfaces were statistically significantly higher than those of the control group LVL boards. These results indicated that the increase in mechanical performance was greater than that achieved by reinforcing LVL boards with synthetic fibers such as glass or carbon fiber. Although glass or carbon fiber provides some reinforcement, it is clear that the increase in strength is not sufficient. Therefore, based on the results of this study, it is recommended to use veneers from a wood species with higher mechanical performance when reinforcing LVL boards produced from poplar or similar tree species. REFERENCES Ayata, Ü., Bal, B.C., 2019. Sapsız meşe (Quercus petreae l.) odununda statik sertlik tayini ve yüzey pürüzlülüğü parametreleri, ınternatıonal conference on agriculture and rural development-II, Proocedings book P: 22-28, September 27-29, 2019, Kiev, Ukraine. Bal, B. C., Bektaş, İ., 2012. The effects of wood species, load direction, and adhesives on bending properties of laminated veneer lumber. BioResources, 7(3), 3104-3112. Bal, B.C., 2014. Flexural properties, bonding performance and splitting strength of LVL reinforced with woven glass fiber, Construction and Building Materials, 51, 9-14. Bal, B. C., Bektaş, İ., Mengeloğlu, F., Karakuş, K., Demir, H. Ö., 2015. Some technological properties of poplar plywood panels reinforced with glass fiber fabric. Construction and Building Materials, 101, 952-957. Bal, B. C., 2021. Research on some mechanical properties of laminated veneer lumber (LVL) strengthened with glass fiber net. Furniture and Wooden Material Research Journal, 4(2), 174182. https://doi.org/doi:10.33725/mamad.1014198 Bao, F., Fu, F., Choong, E.T., Hse, C., 2001. Contribution factor of wood properties of three poplar clones to strength of laminated veneer lumber. Wood Fiber Sci. 33 (3), 345-352. Çolak, S., Çolakoğlu, G., Aydin, I., 2007. Effects of logs steaming, veneer drying and aging on the mechanical properties of laminated veneer lumber (LVL). Building and Environment, 42(1), 93-98. De Melo, R. R., Del, Menezzi, C.H.S., 2014. Influence of veneer thickness on the properties of LVL from Paricá (Schizolobium amazonicum) plantation trees. European journal of wood and wood products, 72(2), 191-198. De Melo, R.R., Del Menezzi, C.H.S., 2015. Influence of adhesive type on the properties of LVL made from Paricá (Schizolobium amazonicum Huber ex. Ducke) plantation trees. Drvna industrija, 66(3), 205-212. Erdil, Y.Z., Kasal, A., Zhang, J., Efe, H., Dizel, T., 2009. Comparison mechanical properties of solid wood and laminated veneer lumber fabricated from Turkish beech, Scots pine, and Lombardy poplar, Forest Product Journal, 59(6), 55-60. Hashim, R., Sarmin, S. N., Sulaiman, O., Yusof, L. H. M., 2011. Effects of cold setting adhesives on properties of laminated veneer lumber from oil palm trunks in comparison with rubberwood. European Journal of Wood and Wood Products, 69(1), 53-61. H’ng, P.S., Paridah, M.T., Chin, K.L., 2010. Bending properties of laminated veneer lumber produced from Keruing (Dipterocarpus sp.) reinforced with low density wood species. Asian Journal of Scientific Research, 3(2), 118-125.

Kurt, R., Cil, M., Aslan, K., Cavus, V., 2011. Effect of pressure duration on physical, mechanical, and combustibility characteristics of laminated veneer lumber (LVL) made with hybrid poplar clones. BioResources 6(4), 4886-4894. Kurt, R., Cil, M., 2012. Effects of press pressures on glue line thickness and properties of laminated veneer lumber glued with phenol formaldehyde adhesive. BioResources. 7(4), 5346-5354. Larson, D.S., Sandberg, L.B., Laufenberg, T.L., Krueger, G.P., Rowlands, R.E., 1987. Butt joint reinforcement in parallel-laminated veneer (PLV) lumber. Wood and fiber science, 414-429. Nelson, S. 1997. Structural composite lumber. Engineered wood products: A guide for specifiers, designers, and users, 174-152. Opazo-Vega, A., Jara-Cisterna, A., Benedetti, F., Nuñez-Decap, M., 2025. Estimation of the orthotropic elastic properties of reinforced LVL panels through vibration-based model updating techniques. Wood Science and Technology, 59(2), 26. Perçin, O., 2023. Determination of air-dried density and compression strength parallel to the grains of heat-treated laminated veneer lumber (LVL) reinforced with carbon fiber. Furniture and Wooden Material Research Journal, 6(1), 104-114. https://doi.org/doi: 10.33725/mamad.1268729 Perçin, O., 2025. Performance properties of heat treated and reinforced laminated veneer lumber with glass fiber. Furniture and Wooden Material Research Journal, 8(1), 156-171. https://doi.org/doi:10.33725/mamad.1699980 Sokolović, N. M., Gavrilović-Grmuša, I., Zdravković, V., Ivanović-Šekularac, J., Pavićević, D., Šekularac, N., 2023. Flexural Properties in Edgewise Bending of LVL Reinforced with Woven Carbon Fibers. Materials, 16(9), 3346. Sulastiningsih, I. M., Trisatya, D. R., Balfas, J., 2020. Some properties of laminated veneer lumber manufactured from oil palm trunk. In IOP Conference Series: Materials Science and Engineering 935(1), 1, p. 012019. IOP Publishing. URL 1 2025, Metsä Wood, https://www.metsagroup.com, (Last Access: 07.09.2025) Vaňová, R., Štefko, J., 2021. Assessment of selected types of the structural engineered wood production from the environmental point of view. Acta Facultatis Xylologiae Zvolen, 63(2), 117-130. Wei, P., Wang, B. J., Zhou, D., Dai, C., Wang, Q., Huang, S., 2013. Mechanical Properties of Poplar Laminated Veneer Lumber Modified by Carbon Fiber Reinforced Polymer. BioResources, 8(4). Wang, J., Guo, X., Zhong, W., Wang, H., Cao, P., 2015. Evaluation of mechanical properties of reinforced poplar laminated veneer lumber. BioResources, 10(4), 7455-7465. Wong. E.D., Razali, A.K., Kawai. S., 1996. Properties of rubber wood LVL reinforced with acacia veneers. Wood research: Bulletin of the Wood Research Institute, Kyoto Un, 1996; 83:8-16.

AUTHORS’ ADDRESSES Bekir Cihad Bal Kahramanmaraş Sütçü İmam University, Kahramanmaraş/Türkiye, bcbal@hotmail.com; bcbal@yahoo.com; bcbal@ksu.edu.tr

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 39−46, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.04

MEASUREMENT BOUND WATER MAXIMUM MOISTURE CONTENT AND DIFFUSION COEFFICIENT DETERMINATION OF BLOWN CELLULOSIC INSULATION MATERIAL IN LABORATORY CONDITIONS Viliam Púček – Richard Hrčka ABSTRACT Mechanical properties, dimensional stability, and biological durability are affected by moisture in timber structures; however, moisture is necessary for hygroscopic insulation materials. With high moisture content, wood elasticity is reduced, corrosion of connectors is promoted, thermal conductivity and heat storage capacity are increased. Thanks to hygroscopic fibers, moisture is stored and redistributed in blown cellulose insulation, the hydrothermal balance within timber walls is enhanced. A laboratory method to determine the diffusion coefficient under variable surface fluxes is developed, and the maximum bound water content is measured using Archimedes’ principle. 40 cm thick test specimens under controlled interior and exterior conditions were tested in the experiments. Moisture content fluctuation was monitored over three months. The diffusion coefficient was derived from Fick’s law and from conservation principle using the inverse method. Results show a decreasing diffusion coefficient that stabilizes over time and a maximum bound water content of 34%. The findings indicate that effective insulation materials must combine a high diffusion coefficient and water storage capacity to manage water condensation and preserve structural durability. Keywords: cellulosic insulation material; bound water maximum moisture content; diffusion coefficient+.

INTRODUCTION Water inside timber structures is undesirable from many perspectives, despite its necessity in wood and other natural and hygroscopic insulation materials (Babiak, 1990; Krieger and Srubar, 2019). The mechanical strength and modulus of elasticity of wood are reduced at higher equilibrium moisture contents (Fu et al., 2022). The biological durability, dimensional stability, corrosion of steel connectors, thermal conductivity, and many other material characteristics show an undesirable trend with increasing moisture content (Zelinka et al., 2014). From another perspective, the descending trend of thermal diffusivity with moisture content increases the lag time of the structure (USDA Forest Products Laboratory 2010). Specific heat and accumulation capacity of structures increase with moisture content (Szodrai and Lakatos 2017; Kotoulek et al. 2019). Despite some mentioned advantages for water presence in structures, the biological durability seems to be the most significant (Martín et al., 2023; Thybring et al., 2022) The moisture content changes significantly in 39

wooden structures in real situations in contrary to set laboratory conditions (JaskowskaLemańska, and Przesmycka, 2021; Brandstätter, 2024). The boundary conditions are changing with relative humidity and temperature. Also, the initial moisture content of the material is significant, as the production process can be wet or dry. The insulation may be installed within the wall, either in a dry state or with a specified initial moisture content. The structures are composed of blown materials serving as insulation. The importance of insulation lies in its large volume or thickness and its hygroscopic character (Slimani et al., 2019; Viljanen and Lu, 2019). The insulation material stores and conducts water within its volume. From a biological durability perspective, it is desirable to keep the insulation material as dry as possible. The entire wall assembly, and each of its parts, should reach equilibrium as quickly as possible (Mattila, 2017), and if condensation occurs within the insulation, it should accept water within its structure as bound water. Then, bound water will be transported to the wall surface by the structure of the insulation material, because the created capillaries where free water occurs are chaotic and not straightforwardly oriented perpendicular to the wall surface. That is the reason why the diffusion coefficient and the maximum bound water moisture content of the insulation materials studied The evaporation of water vapor from its surfaces can be substantially enhanced by the wall construction, Figure 1:

a. b. Fig. 1 The examples of insulation in different structures and possible fluxes at the surfaces.

The fluxes of water inside both structures (Figure 1a, b.) are different and can be different in one structure, also. The direction of the flux depends on the boundary conditions and the instantaneous moisture content within the structure. The equilibration of two different instantaneous moisture contents within the wall structure is described by the solution of the diffusion equation (Künzel, 1995; Hagentoft, 2001). The diffusion coefficient is the quantity that represents the rate of equilibration between two different instantaneous moisture contents within a material and is defined by Fick’s law (Indekeu et al., 2022; Künzel and Kiessl, 1997). The diffusion coefficient information must be supplemented with average moisture content values within the insulation to provide complete information on the velocity of the flux or a description of the moisture content field within the insulation. A method for measuring the above-mentioned needs to be developed. The method will help determine diffusion coefficients not only in laboratory conditions but also in situ in timber structures. The first aim of this contribution is to develop a laboratory method for determining the diffusion coefficient using variable fluxes at the opposing surfaces. The 40

second aim is the measurement of the maximum bound water moisture content of blown insulation material using Archimedes’ principle as described by Hrčka et al., 2020.

MATERIALS AND METHODS STEICOfloc is a loose-fill thermal insulation material based on recycled cellulose fibers derived primarily from post-consumer newspaper. The material is produced through mechanical shredding and fiberization, resulting in a light, open, and flexible fibrous matrix suitable for pneumatic blowing into wall cavities, ceilings, and roofs. To ensure fire safety and biological durability, the fibers are treated with minerals, most commonly boric acid (H₃BO₃) as a fire retardant and biocide, and ammonium sulfate ((NH₄)₂SO₄)₄ as a fire retardant. Chemically, STEICOfloc consists of approximately 85–90% cellulose (C₆H₁₀O₅)ₙ, 0–15% inorganic preservatives, and maybe a small content of lignin. From a materials science perspective, cellulose fibers exhibit high hygroscopicity, allowing the insulation to absorb and release water vapor without structural degradation temporarily. The capillary and sorption characteristics facilitate moisture redistribution within the insulation layer, contributing to a balanced hydrothermal environment in timber-frame constructions. The vapor diffusion resistance factor (µ) ranges between 1 and 2, confirming the high vapor permeability of the material (STEICO, 2022). The recommended installation density for vertical wall cavities is 55–65 kg·m-3 to ensure dimensional stability and minimize settlement, while horizontal applications can be filled with lower densities, around 45 kg·m-3 (STEICO, 2022). Diffusion coefficient measurement The method of diffusion coefficient measurement is based on solution of diffusion equation (1) (Crank 1975): 𝜕2𝑐

𝜕𝑐

= 𝐷 𝜕𝑥 2 𝜕𝑡

(1)

Where: c is concentration defined as the ratio of mass of water to initial specimen volume, t is time, x spatial coordinate and D diffusion coefficient. The solution is derived for zero initial condition and different fluxes, as the functions of time, at both surfaces, x=0 and x=R, equations (2) and (3): 𝜕𝑐

𝜕𝑥 𝑥=0 𝜕𝑐

−𝐷

= 𝑓0 (𝑡)

𝜕𝑥 𝑥=𝑅

= 𝑓𝑅 (𝑡)

(2) (3)

The average concentration ¯c can be only changed by fluxes at the surfaces and its time derivative is difference between fluxes: 𝜕𝑐̅ 𝜕𝑡

= 𝑓0 − 𝑓𝑅

(4)

If concentrations at some parts of thickness are determined, then diffusion coefficient is the only one unknown parameter in the solution of diffusion equation (1):

𝑐𝑖𝑛𝑡 +𝑐𝑒𝑥𝑡 2

− 𝑐̅ = 2 ∑∞ 𝑗=1

𝜋 2

sin((2𝑗−1) ) 𝜋 2

(2𝑗−1)

−(2𝑗−1)2

𝑒

𝜋2 𝐷𝑡 4 𝑅 2 ( ) 4

𝑡 𝜕𝑐̅ ∫0 𝜕𝜏 𝑒

(2𝑗−1)2

𝜋2 𝐷𝜏 4 𝑅 2 ( ) 4

𝑑𝜏

(5)

Where:¯cint is average concentration of adjacent parts to interior, ¯cext is average concentration of adjacent parts to exterior, (2j-1)π/2 is jth root of characteristic equation, R is thickness of specimen and τ integration variable. The left side of equation (5) is known by measurement. The least square method is applied on right side of equation (5) using criterion: 𝑐

+𝑐

𝑐

𝑒𝑥𝑡 𝑖𝑛𝑡 𝑄(𝐷) = ∑∞ − 𝑐̅)| 𝑛=1 (( 2

𝑡ℎ𝑒𝑜𝑟

+𝑐

− ( 𝑖𝑛𝑡 2 𝑒𝑥𝑡 − 𝑐̅)|

𝑒𝑥𝑝

)

(6)

Where: “theor” denotes right side of equation (5) and “exp” is experimentally determined values of average concentration and concentrations of adjacent parts to interior (int) and exterior (ext): 𝑅

𝑐̅𝑖𝑛𝑡 (𝑡) = ∫04 𝑐(𝑥, 𝑡)𝑑𝑥

(7)

(8)

c̅ext (t) = ∫3R c(x, t)dx 4

The method of determining the diffusion coefficient must fulfil the measurement's versatility requirements, as reflected in the initial and boundary conditions used to solve the diffusion equation. The solution of the diffusion equation will serve as a key factor in determining the diffusion coefficient and the moisture content field inside the wall. The potential for water diffusion in insulating materials, such as wood, is concentration, defined as the mass of water per unit volume of the dried insulation material. The dried substance was obtained by drying specimens of the insulation material at atmospheric pressure and 105 °C in an air environment. The experimental scheme is shown in Figure 2.

Fig. 2 The scheme of experiment.

The wall thickness was set to 40 cm. The temperature of 22 °C and humidity of 50% were set in the climatic chamber Binder KBF 720 (Tuttlingen, Germany) as interior conditions. The external conditions were exerted on a saturated aqueous solution of 42

CuSO4·5H2O at 22 °C. Mass measurements of the individual parts were performed daily for three months. Masses and times were recorded on the computer. Then, the average concentration in time was computed as the average of all four parts. Bound water measurement The measurement of the maximum bound water moisture content was performed using the method described by Hrčka et al. (2020). The method also uses the equilibrium between water and an arbitrary absorbing material, recycled cellulose fibers (STEICOfloc). The mass of the specimen was measured in water, and the apparent mass was determined. The ratio of apparent mass and oven-dried specimen is equal to the maximum bound water moisture content. The oven-dried mass was achieved in a dry-air environment at 105°C and normal pressure. The apparent density was measured at 21.5°C. The measurement was performed using the balances Radwag XA 60/220X (Radom, Poland) with the original density determination kit, and the mass of the oven-dried specimen was 40.0 mg. The maximum bound moisture content was reported when its value did not change, rounded to 3 significant digits.

RESULTS AND DISCUSSION Equation (5) is the basis for the method of diffusion coefficient measurement. It contains only one unknown parameter – the diffusion coefficient on the right side of the equation. The left-hand side of the equation was calculated from the specimen masses and volume. Figure 3 presents the specimen moisture content change over time, and the experimental results were fitted using the method of least squares.

Fig. 3 Moisture contents of whole specimen four individual parts, the initial moisture content was zero.

After imbedding the oven-dried specimens in the climatic chamber, all four specimens began to increase their instantaneous moisture contents. As the experiment progressed, the rate of attaining higher instantaneous moisture content decreased. Finally, specimens’ moisture contents reached stable values. As Figure 3 shows, the differences in moisture content between adjacent parts of the specimen did not reach equilibrium values. The differences could be due to non-constant flux throughout the specimen and to the material 43

exhibiting a cosine-like instantaneous moisture content distribution in the spatial coordinate. The reason the equilibrium moisture content is taken into account does not seem valid in all parts, because it was not reached throughout the entire specimen. The left side of the equation (5) was fulfilled in all details, because the right side contains the description of the flux evolution during the experiment. Then, the diffusion coefficient showed a decreasing trend throughout the experiment (Figure 4).

Fig. 4 The evolution of diffusion coefficient value during sorption experiment.

The curve depicted in Figure 4 showed a decreasing character and presumably reached a constant final value. It must be emphasized that the left side of equation (5), which included only measured instantaneous moisture contents and the average value of the insulating material, was fully satisfied, and diffusivity was the only unknown parameter. It is important to emphasize that equations (5) and (1) do not exclude the possibility of a variable diffusion coefficient during the experiment. Diffusivity is therefore difficult to treat as a property. It was assumed that the diffusion coefficient would reach a constant value under steady flux, that the insulation material would form a layer of water within it, and that the diffused water would move smoothly over it. If the created layer of water is modified with a versatile boundary, the diffusion coefficient will change until a new steady flux is reached. The Nuclear Magnetic Resonance approach of Zou et al. (2023) was used to fit the parameters of their proposed model for the longitudinal transport diffusion coefficient of bound water in cellulose fibres. The value obtained for the diffusion coefficient was 3·10−9 m2s−1. Thus, the longitudinal transport diffusion coefficient of bound water between cellulose microfibrils appears to be close to the self-diffusion coefficient of (bulk) water (i.e. D = 2.3·10−9 m2s−1) (Zou et al. 2023). This self-diffusion value and the diffusion coefficient of bound water in cellulose fibres in the longitudinal direction are in good agreement with the calculated values obtained by our method. Diffusivity is not the only criterion for determining the suitability of a material for insulation. Another criterion is the bound water maximum moisture content. It was assumed that good insulation material should have high diffusivity and a high maximum moisture content within the wall structure, as shown in Figure 1b. If water vapor condenses, the insulation material must be able to diffuse the maximum amount of water possible. The results of the bound water maximum content measurement for STEICOfloc are presented in 44

Table 1. The initial density of the specimen inside the cuvette was 65 kg.m-3 in the dried state Tab. 1 Maximum bound (B) and free (F) moisture contents of STEICOfloc measured using Archimedes’ principle. wBmax (%) 33.7

wFmax (%) 1400

The bound water maximum content value of 33.7% is comparable to the value reported by Hrčka et al. (2020) for cellulose, 38.9 ± 0.01%. The value is significantly lower due to the presence of some lignin in the STEICFloc insulation material.

CONCLUSION The diffusion coefficient and the maximum moisture content of bound water are key factors for recognizing insulation materials. If condensation occurs inside a structure, the insulation material must be able to diffuse the maximum amount of water possible through the surface, which is normal to the flux in a given time interval. The STEICOfloc insulation cellulosic material exhibits a decreasing diffusion coefficient over time during sorption in constant climate conditions in laboratory conditions, at both surfaces. The maximum bound water moisture content of STEICOfloc was 33.7%. This value is almost equivalent to cellulose derived from wood. If a different insulation material is more suitable for the diffusion of water within a wall structure, the diffusion coefficient and the maximum bound water moisture content should be higher. Such an experiment must be performed with different commercially available insulation materials.

REFERENCES Babiak, M., 1990. Wood–water system. VŠLD, Zvolen. Brandstätter, F., Autengruber, M., Lukacevic, M., Füssl, J., 2024. The influence of geographical location on moisture distribution in wood cross sections: A numerical simulation study using Austria as an example. Journal of Wood Science 70, Article 35. https://doi.org/10.1186/s10086024-02147-z Crank, J., 1975. The Mathematics of Diffusion (2nd ed.). Oxford University Press. Fu, Z., Chen, J., Zhang, Y., Xie, F., Lu, Z., 2022. Review on wood deformation and cracking during moisture loss. Polymers 15(15), 3295. https://doi.org/10.3390/polym15153295 Hagentoft, C.-E., 2001. Introduction to Building Physics: Heat, Air and Moisture. Studentlitteratur, Lund. Hrčka, R., Kučerová, V., Hýrošová, T., Hönig, V., 2020. Cell wall saturation limit and selected properties of thermally modified oak wood and cellulose. Forests 11(6), 640. https://doi.org/10.3390/f11060640 Indekeu, M.L., Janssen, H., Woloszyn, M., 2022. Determination of the moisture diffusivity of rammed earth from water absorption measurements. Journal of Building Performance 13(1), 1– 10. https://doi.org/10.1080/20421338.2022.2042138 Jaskowska-Lemańska, J., Przesmycka, E., 2021. Semi-destructive and non-destructive tests of timber structure of various moisture contents. Materials 14(1), 96. https://doi.org/10.3390/ma14010096 Kotoulek, P., Božíková, M., Hlaváč, P., Petrović, A., Csillag, J., Malínek, M., Bilčík, M., 2019. Effect of different moisture contents on the thermal properties of wood. Journal on Processing and Energy in Agriculture 23(3), 109–113. https://doi.org/10.5937/JPEA1903109K

Krieger, B.K., Srubar III, W.V., 2019. Moisture buffering in buildings: A review of experimental and numerical methods. Energy and Buildings 202, 109394. https://doi.org/10.1016/j.enbuild.2019.109394 Künzel, H.M., 1995. Simultaneous Heat and Moisture Transport in Building Components. Fraunhofer IRB Verlag, Stuttgart. Künzel, H.M., Kiessl, K., 1997. Calculation of heat and moisture transfer in multi-layer building components. International Journal of Heat and Mass Transfer 40(1), 159–167. https://doi.org/10.1016/S0017-9310(96)00200-9 Martín, J.A., López, R.., 2023. Biological deterioration and natural durability of wood in Europe. Forests 14(2), 283. https://doi.org/10.3390/f14020283 Mattila, H.-P., 2017. Moisture behavior of building insulation materials and good building practices. Paroc Group Oy. Slimani, Z., Trabelsi, A., Virgone, J., Freire, R.Z., 2019. Study of the hygrothermal behavior of wood fiber insulation subjected to non-isothermal loading. Applied Sciences 9(11), 2359. https://doi.org/10.3390/app9112359 STEICOfloc, 2022. Technical Data Sheet. Tepore s.r.o. Available at: https://tepore.sk/uploads/steico-floc-cz-1.pdf Szodrai, F., Lakatos, A., 2017. Effect of the moisture in the heat storage capacity of building structures. Applied Mechanics and Materials 861, 320–326. https://doi.org/10.4028/www.scientific.net/AMM.861.320 Thybring, E.E., Fredriksson, M., Zelinka, S.L., Glass, S.V., 2022. Water in wood: A review of current understanding and knowledge gaps. Forests 13(12), 2051. https://doi.org/10.3390/f13122051 USDA Forest Products Laboratory, 2010. Wood Handbook: Wood as an Engineering Material. General Technical Report FPL-GTR-190. U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, Madison (WI). https://doi.org/10.2737/FPL-GTR-190 Viljanen, K., Lu, X., 2019. An experimental study on the drying-out ability of highly insulated wall structures with built-in moisture and rain leakage. Applied Sciences 9(6), 1222. https://doi.org/10.3390/app9061222 Zelinka, S.L., Glass, S.V., Derome, D., 2014. The effect of moisture content on the corrosion of fasteners embedded in wood subjected to alkaline copper quaternary treatment. Corrosion Science 83, 67–74. https://doi.org/10.1016/j.corsci.2014.01.044 Zou, Y., Maillet, B., Brochard, L. Coussot, F., 2023. Fast transport diffusion of bound water in cellulose fiber network. Cellulose 30, 7463–7478. https://doi.org/10.1007/s10570-023-05369-4 ACKNOWLEDGMENT

This study was supported by the Scientific Grant Agency Project VEGA 1/0599/25 and the Slovak Research and Development Agency Contract no. APVV-23-0369. AUTHORS’ ADDRESSES Ing. Viliam Púček Dr. Richard Hrčka Technical University in Zvolen T.G. Masaryka 24 96001 Zvolen, Slovakia xpucek@tuzvo.sk richard.hrcka@tuzvo.sk

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 47−55, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.05

MOISTURE CONDUCTIVITY AND DENSITY OF INDUSTRIAL WOODS: A STUDY FOR EFFECTIVE DRYING Andrii Spirochkin – Olena Pinchevska – Yuriy Lakyda – Denis Zavyalov – Rostislav Oliynyk – Ján Sedliačik ABSTRACT An analysis of the physical properties of the main industrial tree species revealed significant variation across growing regions with different climatic conditions . For drying sawn timber products, convection chambers equipped with automatic systems with pre-set schedules designed for tree species native to the countries where dryers are manufactured are most widely used. It does not always lead to positive results. Adjusting the parameters of the modes requires the density and moisture-conductivity coefficients for industrial tree species. The dependence of moisture conductivity coefficients in the transverse directions of moisture movement on temperatures in the 25 °C – 80 °C range was determined. Adequate regression equations for the dependence of moisture conductivity coefficients on temperature in the tangential and radial directions were obtained. The values of the average basic density of these tree species originating from different regions and its dispersion determined experimentally were as follows: pine 414 kg∙m-3 ± 11%; alder 448 kg∙m-3 ± 9%; oak 569 kg∙m-3 ± 10%; ash 640 kg∙m-3 ± 6%; hornbeam 667 kg∙m-3 ± 7%. These values were used to determine the analytical dependence of the moisture conductivity coefficients on the basic density and its dissipation, which is necessary for developing optimal schedules of drying sawn timber by adequately modelling convection drying and predicting process quality. Keywords: lumber; convection drying; processing temperature; moisture conductivity coefficient; basic density.

INTRODUCTION Drying sawn timber is the most time-consuming and energy-intensive process in wood processing. Today, convection chambers are mainly used for their implementation, in which the drying agent, i.e., air, is heated by contact with heaters filled with hot water. Using hot water as a heat source prevents temperatures from rising above 70-80 °C. This is because wood is increasingly being used as a construction material. The use of wood as a structural material requires compliance with mechanical property requirements, particularly strength (Toba et al., 2022; Perre et al., 2014). Such ‘low-temperature’ dryers are used by many woodworking companies. They all have virtually the same design and differ only slightly in the automation system and drying schedules. The latter is designed to account for the characteristics of tree species grown in the countries where the chambers are manufactured, so the operating parameters often need 47

to be adjusted to achieve a high-quality result (Simpson, 2007; Chen et al., 2020; Tomad et al., 2023). Meanwhile, it is known that even within the same country, both the physical and mechanical properties of wood depend on the region of growth. For example, the central regions where pine grows include Chernihiv, Volyn, and Zhytomyr, which have different soils and humidity. In a more humid region, raw wood materials will be less dense and, accordingly, will have worse mechanical properties. However, the process of drying sawn timber products will be easier. In Ukraine, industrial tree species such as pine, oak, ash, hornbeam, and alder are popular for manufacturing solid wood products. The most widespread areas of oak distribution are the Forest-Steppe and Polissya regions, with average fundamental density values of 554 kg∙m-3 and 600 kg∙m-3 (Lakyda et al., 2011). The distribution of hornbeam (with average fundamental density values of 620 kg∙m-3 and 710 kg∙m-3) and ash (with average fundamental density values of 600 kg∙m-3 and 680 kg∙m-3) is dominated by the Forest-Steppe zone, mainly Vinnytsia and Sumy regions, and alder (with average fundamental density values of 410 kg∙m-3 and 490 kg∙m-3) by Polissia (Zhytomyr and Volyn regions) (Lakyda et al., 2020). The Polissia region is characterized by higher air and soil humidity, while the Forest-Steppe region is drier. Therefore, the properties of timber from the different areas require an individual approach to drying sawn timber products. It is known that hardwood lumber with a high basic density is difficult to dry (Denig et al., 2000; Walker, 2006). Unlike other wood processing processes, such as sawmilling, joinery, and furniture production, where the result is evident during the process, the drying result is only visible afterward, and it is impossible to mitigate potential negative consequences. For example, if the movement of moisture is too fast under the influence of heat, which, on the one hand, reduces the processing time and, on the other hand, contributes to the occurrence of drying defects in the form of cracks due to high drying stresses. To understand and properly develop wood drying technology, it is of primary importance to study the entire complex of numerous elementary heat and moisture transfer phenomena. The theoretical study of these phenomena led to the creation of a mathematical model of interconnected heat and mass transfer, which enabled the description of non-isothermal drying, sorption, and two-phase filtration from a single perspective (Elustondo, 2021; Dzurenda and Deliiski, 2010). The theoretical studies developed to date on various approaches to solving the problems of wood drying focus on the need to consider individually the phenomena that limit the drying mechanism and the material's quality. The moisture conductivity coefficient is the key to calculating the drying time in any process model. Its value depends on many factors, such as the anatomical structure of wood, anisotropy, basic density, which characterizes the mass of dry wood per unit volume of green wood, and the processing temperature (Lykov, 1968; Pinchevska et al., 2023). Given that both wood and energy prices are rising, poor-quality drying of domestic tree species can result in significant losses due to incorrect processing time calculations. Therefore, to build adequate models for drying sawn timber products that allow calculating the expected drying time and predicting the achievement of the required process quality, it is necessary to have quantitative values for the physical quantities that affect the moistureremoval process in wood. Therefore, it is important to determine the moisture-conductivity coefficients for different types of wood. The aim of the research is to determine the coefficients of moisture conductivity and basic density for pine, alder, oak, ash, and hornbeam as key parameters for modelling and the development of rational drying schedules. 48

MATERIALS AND METHODS Radially and tangentially sawn timber made of pine (Pinus sylvestris L.), oak (Quercus robur L.), ash (Fraxinus excelsior L.), hornbeam (Carpinus betulus L.), and alder (Alnus glutinosa L.) wood were selected to determine the moisture conductivity and basic density. Test samples were cut to determine the moisture conductivity coefficients, and samples measuring 20×20×30 mm were used to determine the basic density. The number of samples was 27 per tree species, for a total of 300 samples examined. The procedure for determining the coefficient of moisture conductivity includes auxiliary experiments to determine the limit of hygroscopicity of wood, Whl, and main experiments (Pinchevska et al., 2018). For the auxiliary experiments, wood samples measuring 3×30×50 mm were first dried in a thermostat at a temperature of t = 103 ± 2 °C to a completely dry state, m 0. Then they were humidified in hygroscopic covers placed in a water-charged desiccator (Figure 1a) at 25, 40, 60, 80 °C. The weight of the samples was monitored hourly, and the experiment was completed when the samples reached a constant weight, mhl. The formula determines the moisture content of the hygroscopic limit: 𝑊ℎ𝑙 =

𝑚ℎ𝑙 −𝑚0 𝑚0

100%

(1)

The main experiments used tangential and radial sawn wood samples with dimensions of 5×50×70 mm and 10×50×70 mm, respectively. The samples, dried to a completely dry state, were placed in the desiccator charged with a sulfuric acid solution with a density of ρ = 1260 kg∙m-3 to achieve a uniformly distributed initial moisture content W in across the cross-section, which corresponds to the equilibrium moisture content W emc = 12% (Figure 1b).

a b Fig. 1 Location of the samples: a - samples in hygroscopic covers placed in a water-charged desiccator; b - samples in a sulfuric acid-charged desiccator.

The samples were then wrapped in hygroscopic covers and left in a water-charged desiccator to achieve a steady-state value of dimensionless humidity Е , (Pinchevska et al., 2023): 𝑊 −𝑊 Е = 𝑊 ℎ𝑙−𝑊 𝑓 (2) ℎ𝑙

𝑖𝑛

Where: Whl – moisture content of the hygroscopic limit, %, which is determined by moisture sorption in a saturated medium at a certain temperature; Win – initial moisture content of the sample, %; Wf – final moisture content of the sample, %. 49

The conditional moisture conductivity coefficients for samples of each thickness are calculated by the formula (Pinchevska et al., 2023): 𝜋𝑆 2

𝑎′′ = 16𝜏 (1 − Е) Where: S – sample thickness, mm; τ – duration of the experiment, h.

(3)

The actual coefficient of moisture conductivity is calculated by the formula (Pinchevska et al., 2023): 𝑎′ =

′′ (𝑆2 −𝑆1 )∙𝑎′′ 2 ∙𝑎1 ′′ 𝑆2 ∙𝑎′′ 1 − 𝑆1 ∙𝑎2

(4)

Where: 𝑎1′′ і 𝑎2′′ – average values of conditional moisture conductivity coefficients for samples of two different thicknesses S1 = 5 mm and S2 = 10 mm. Determination of the basic density, ρb, kg∙m-3, as an important indicator widely used for calculations of the processes of heating, drying, and impregnation of wood is determined by the formula: 𝜌𝑏 =

𝑚0 𝑉𝑚𝑎𝑥

(5)

Where: m0 – the weight of the absolutely dry sample, kg; Vmax – sample volume at humidity above the saturation of cell walls, m 3.

RESULTS AND DISCUSSION The results of determining the moisture conductivity coefficients for the researched tree species are shown in Figure 2. In all studied tree species, an increase in the values of moisture conductivity coefficients with increasing temperature was observed, which is associated with a decrease in moisture viscosity (Lykov, 1968; Pinchevska et al., 2018). The nature of the dependence of the moisture conductivity coefficients on temperature for each species is determined by the peculiarities of its structure and density. It was found that this process is adequately described by quadratic equations for such as pine and alder, which may be assocoiated with lower density compared to hardwood species. The adequacy testing was performed using Fisher’s, Fi, and Student's, St, criteria. It can be seen that the calculated values of the criteria, Ficalc, Stcalc, are lower than the tabulated ones, Fitab, Sttab, 0.93 ≤ 𝐹𝑖𝑐𝑎𝑙𝑐 ≥ 1.05; 2.5 ≤ 𝐹𝑖𝑡𝑎𝑏 ≥ 2.97; 0.03 ≤ 𝑆𝑡𝑐𝑎𝑙𝑐 ≥ 0.05; 𝑆𝑡𝑡𝑎𝑏 = 2.770: Pine: Tangential direction Radial direction

𝑎` = 0.0013𝑡 2 − 0.0114𝑡 + 2.2915 𝑎` = 0.0015𝑡 2 − 0.0146𝑡 + 3.3267

(6) (7)

Alder: Tangential direction Radial direction

𝑎` = 0.0011𝑡 2 + 0.0213𝑡 + 0.0794 𝑎` = 0.0012𝑡 2 + 0.0235𝑡 + 0.1599

(8) (9)

For hardwoods, the obtained equations correspond to the adequately described polynomial dependence (0.33 ≤ 𝐹𝑖𝑐𝑎𝑙𝑐 ≥ 6.84; 8.89 ≤ 𝐹𝑖𝑡𝑎𝑏 ≥ 6.09; 0.19 ≤ 𝑆𝑡𝑐𝑎𝑙𝑐 ≥ 1.99; 𝑆𝑡𝑡𝑎𝑏 = 2.77) Oak: Tangential direction Radial direction

𝑎` = 0.00006𝑡 3 − 0.0079𝑡 2 + 0.4042𝑡 − 5.0758 𝑎` = 0.00005𝑡 3 − 0.0076𝑡 2 + 0.4040𝑡 − 5.0920

(10) (11)

Ash: Tangential direction Radial direction

𝑎` = 0.00004𝑡 3 − 0.0066𝑡 2 + 0.3543𝑡 − 4.7747 𝑎` = 0.00003𝑡 3 − 0.0047𝑡 2 + 0.2743𝑡 − 3.5418

(12) (13)

Hornbeam: Tangential direction Radial direction

𝑎` = 0.00003𝑡 3 − 0.0051𝑡 2 + 0.2641𝑡 − 3.5553 𝑎` = 0.00003𝑡 3 − 0.0047𝑡 2 + 0.2555𝑡 − 3.2712

(14) (15)

Fig. 2 Effects of tree species on the actual moisture conductivity coefficient at different processing temperatures.

The correlation between moisture flow values in the radial and tangential directions across different species was established, ranging from 1.1 to 1.6. It is due to the significant influence of the ray cells, in which the anatomical elements of wood are arranged longitudinally. In addition, the ray cells' width varies from 0.005 mm to 1 mm, and their percentage of the total trunk volume can inhibit or accelerate moisture removal from the wood (Vintoniv et al., 2007). Even though oak has the widest ray cells and the percentage of its content in the trunk is 36%, most of the studied species (Ugolev, 2007; Vintoniv et al., 2007), the value of the coefficient of moisture conductivity is almost two times lower than that of pine. The results of the basic density study are shown in Figure 3. 51

Comparison of the average fundamental density values for the studied species with those reported by previous researchers showed that the results are ambiguous. The results of large-scale studies conducted by Lakyda et al. (2020) show a similar trend. However, according to Biley et al. (2008), the basic density of ash wood is 13% lower and close to values obtained for wood from the Russian Far East, which is most likely explained not by their own experiments but by reference data.

Fig. 3 Average values of the basic density of different species.

The basic density of wood shows a relatively large dispersion due to the wide distribution of tree species across the country. Since such a physical quantity as wood basic density is fundamental in determining many physical and mechanical properties, its dependence on the place of growth of wood raw materials has a direct impact on their variability (Majka et al., 2023). The dependence of the moisture conductivity coefficients on the basic density at different temperatures is shown in Figure 4. Given the complex dependence of the moisture conductivity coefficients on temperature and basic density of wood, the next step was to establish their analytical description. In addition, for the further development of rational drying schedules and the determination of processing time, it will be necessary to consider the dispersion of the basic density, which will certainly affect the dispersion of the moisture conductivity coefficients.

Fig. 4 Visualization of the dependence of the moisture conductivity coefficients in the transverse direction on the average values of the basic density.

Since the drying of sawn timber is a stochastic process (Pinchevska et al., 2016), accounting for the dispersion of the moisture conductivity coefficient, which drives moisture movement within the material, will allow predicting the drying quality of different types of wood when applying different drying schedules. In addition, the creation of databases of the properties of various tree species will facilitate the use of artificial intelligence to model and control the drying process (Elustondo et al., 2023).

CONCLUSION Analysis of the properties of industrial tree species in Ukraine showed that they depend on the region of origin. This affects achieving the desired results when modelling the process of drying sawn wood products. The scientific novelty lies in determining the moistureconductivity coefficients of industrial tree species, which are necessary for developing rational drying schedules and determining the objective time of the process. Adequate equations for the dependence of moisture conductivity coefficients on the processing temperature have been obtained. The dispersion of fundamental density values for the studied tree species, which affects the variability of moisture conductivity coefficients, was quantified. Further research is needed to determine the relationship between the moisture conductivity coefficients depending on the basic density of wood and temperature, the result of which will allow us to select rational drying schedules, even with the use of artificial intelligence, for each case, taking into account the dispersion of the basic density of wood. REFERENCES Biley, H., Pavlust, V., 2008. Drying and Protecting Wood. “Colorove nebo” Lviv, Ukraine, 312 p. Chen, C., Kuang, Y., Zhu, S., Burgert, I., Keplinger, T., Gong, A., Li, T., Berglund, L., Eichhorn, S.J., Hu, L., 2020. Structure–Property–Function Relationships of Natural and Engineered Wood. Nature Reviews Materials 5, 642–666. Denig, J., Wengert, M., Simpson, W.T., 2000. Drying Hardwood Lumber. The Forest Products Laboratory, University of Wisconsin, 144 p. Dzurenda, L., Deliiski, N., 2010. Thermal processes in wood processing technologies. Technical University in Zvolen, 273 p.

Elustondo, D., 2021. Semi-Empirical Linear Correlation between Surface Tension and Thermodynamics Properties of Liquids and Vapours. Chemical Physics 545, 111145. Elustondo, D., Matan, N., Langrish, N., Pang, S., 2023. Advances in wood drying research and development. Drying Technology 41(6), 890–914. Lakyda, P., Vasylyshyn, R., Lashenko, A., Terentiev, A., 2011. Norms for assessing the components of ground phytomass of trees of the main forest-forming species of Ukraine. Publishing house “EKO-inform”, 192 p. Blyshchyk, V., Lakyda, I., Bilous, A., Matushevych, L., Bala, O., Mateyko, I., Moroziuk, O., Kovalevskyi, S., Khan, Y., Sytnyk, S., Bokoch, V., Blyshchyk, I., Prylipko, I., Melnyk, O., Dubrovets, B., 2020. Experimental data on live biomass of Ukrainian deciduous forests. PC Komprynt, 488 p. Lykov, A., 1968. Drying theory. Energy, Мoscow Russia, 472 p. Majka, J., Czajkowski, L., Wieruszewski, M., Mirski, R., 2023. Kiln-drying effectiveness as influenced by moisture content and density variation within a Scots pine timber batch. Wood Material Science and Engineering 19, 752–761. Perre, P., Keey, R.B., 2014. Drying of Wood: Principles and Practices. In Handbook of Industrial Drying; Mujumdar, A, Ed.; CRC Press: Boca Raton, FL, 822–872. Pinchevska, O., Spirochkin, A., Sedliačik, J., Oliynyk, R., 2016. Quality assessment of lumber after low temperature drying from the view of stochastic process characteristics. Wood Research 61(6), 871–884. Pinchevska, O., Spirochkin, A., Boriachynski, V., 2018. Accelerated drying of oak blanks. CP “Comprint”. Kyiv, Ukraine, 144 p. Pinchevska, O., Spirochkin, A., Horbachova, O., 2023. Thermal treatment of wood. National University of Life and Environmental Sciences of Ukraine. Kyiv, Ukraine, 179 p. Simpson, W.T. 2007. Drying wood: a review - part 1. Drying Technology: 235–264. Toba, K., Nakai, T., Kanbayashi, T., Saito, H., 2022. Effects of Cyclic Drying and Moistening on the Mechanical and Physical Properties of Wood. European Journal of Wood and Wood Products 80, 1333–1341. Tomad, J., Leelatanon, S., Jantawee, S., Srisuchart, K., Matan, N., 2023. Internal Stress Development within Wood during Drying: Regime and Kinetics. Drying Technology 41, 77–88. Ugolev, B.N., 2007. Wood science and forestry commodity science. Moscow State Forest University, Moscow, Russia, 351 p. Vintoniv, І.S., Sopushynski, І.М., Teischinger, А., 2007. Wood science. Apriori, Ukraine, 312 p. Walker, J.C.F., 2006. Primary wood processing. Principles and Practice. 2nd edition University of Canterbury, Christchurch, New Zealand, Published by Springer, 596 p.

ACKNOWLEDGMENT The work was carried out with the support of the Ministry of Education and Science of Ukraine within the framework of the scientific project state registration number: 0122U202112: “Development of quasi-optimal wood drying schedules taking into account the stochastic nature of its physical properties”. The authors are grateful to the Ministry of Education and Science of Ukraine for the support of this research. This work was supported by the Slovak Research and Development Agency under the contracts No. APVV-18-0378, APVV-22-0238 and by the projects VEGA 1/0077/24 and VEGA1/0450/25. AUTHORS’ ADDRESSES Assoc. Prof. Andrii Spirochkin, PhD. Prof. Ing. Olena Pinchevska, DrSc. Assoc. Prof. Yuriy Lakyda, PhD. 54

Assoc. Prof. Denis Zavyalov, PhD. National University of Life and Environmental Sciences of Ukraine Department of Technology and Design of Wood Products Geroiv Oborony str. 15 03041 Kyiv, Ukraine olenapinchevska@nubip.edu.ua Assoc. Prof. Rostislav Oliynyk, PhD. Kyiv National Taras Shevchenko University Geography Faculty Meteorology and Climatology Department Akademika Glushkova 2a 02000 Kyiv, Ukraine rv_oliynyk@ukr.net Prof. Ing. Ján Sedliačik, PhD. Technical University in Zvolen Department of Furniture and Wood Products T. G. Masaryka 24 960 01 Zvolen, Slovakia sedliacik@tuzvo.sk

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 57−65, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.06

ENERGY DOSE AND SPECIFIC CUTTING ENERGY IN CO₂ LASER CUTTING OF SOLID AND ENGINEERED WOOD MATERIALS Lukáš Štefančin – Rastislav Igaz – Ivan Kubovský – Ivan Ružiak – Richard Kminiak ABSTRACT The energy requirements of CO₂ laser cutting for three solid wood species (spruce, oak, and beech) and three engineered wood-based materials (pine plywood, beech plywood, and highdensity fiberboard) are examined in this study. Energy dose (Ed) and specific cutting energy (Ec) were calculated for each material under selected laser power and feed rate combinations. The goal was to achieve a kerf width of 300 µm, consistent with the geometric tolerances of ISO 9013:2017. Results show that Ed increases with material density, while Ec reveals additional influences, including anatomical structure and bonding in engineered products. Oak exhibited the lowest Ec despite a relatively high density, while HDF and beech plywood showed the highest values. These findings suggest that material density can inform initial laser parameter selection, but cutting efficiency also depends on how energy interacts with structure and composition. The observed relationships between density and Ed, and between Ed and Ec, provide a framework for refining processing settings based on material characteristics. Keywords: CO2 laser; laser cutting; dimensional tolerances; energy dose; specific energy.

INTRODUCTION Laser cutting of wood has become a standard process in industries ranging from woodworking and cabinetry to model making. Particularly, CO₂ lasers are frequently used in the woodworking industry due to their high precision and minimal material waste (Naresh 2021; Mushtaq et al., 2020). Historically, in conventional woodworking, the width of a cut, commonly referred to as the kerf, has been determined by the physical thickness of the cutting tool, such as a saw blade (Menschel et al., 2021). Mechanical cutting tools introduce precise, predictable kerf dimensions defined by their geometry, which is an essential factor for dimensional planning and material optimization. By contrast, in laser cutting, the kerf is governed not by a physical blade, but by the diameter of the focused laser beam interacting with the material (MartínezConde et al., 2017). In the context of precision laser woodworking, the beam focus size effectively plays the same role as the saw thickness did in mechanical cutting, controlling the minimum achievable kerf width. In this study, a beam focus width of approximately 300 µm serves as the reference for achieving high-dimensional precision, drawing a direct operational parallel to mechanical processes but under new, thermally driven conditions. 57

The focus is on achieving kerf widths of around 300 µm, corresponding to the nominal diameter of the laser beam focus, to meet ISO 9013:2017 Class I dimensional tolerances for 6 mm-thick material. Although ISO 9013 defines tolerances based on deviations from the intended contour rather than kerf width directly, a kerf width of ~ 300 µm ensures that each side remains within ±150 µm of the intended boundary and thus stays within Class I limits without template modification, toolpath compensation, or kerf offset adjustment. Ensuring the quality of wood cuts is essential, yet there is no wood-specific international standard for evaluating laser-cut quality. In practice and research, the metalfocused ISO 9013 standard (initially developed for thermal cutting of metals) can be applied to assess the quality of laser-cut wood (Barcikowski et al., 2004b; ISO 9013:2017). However, wood’s organic nature introduces challenges not fully addressed by metalfocused metrics, variations due to moisture content, potential for surface charring, and structural anisotropy. CO₂ laser interaction with lignocellulosic material induces complex thermal, morphological, and chemical changes (Kúdela et al., 2023), further complicating attempts to standardize quality using metal-based tolerancing systems. While ISO 9013 provides useful dimensional reference, the standard does not account for the effects of grain direction, internal structure, or the thermal response of adhesives in engineered products. Incorporating a correction factor based on anatomical or structural features may help extend ISO 9013’s applicability to wood and wood-based materials more reliably. Natural woods vary in structure due to grain direction and growth characteristics, leading to inconsistent cutting behavior (Açık 2023a). In contrast, engineered wood products, such as plywood and high-density fiberboard (HDF), typically yield more predictable cutting outcomes due to their uniform structure and controlled manufacturing processes (Magaznieks and Narica 2018). Recent advancements have increasingly shifted laser processing of wood and wood composites toward systematic, data-driven approaches (Ružiak et al., 2024; Naresh et al., 2024). However, further refinement is needed to establish reproducible, material-specific methodologies that match the level of standardization seen in metal and polymer laser cutting (Hernández-Castañeda and Li 2011). Comparative work by Gochev also demonstrated that the specific energy required for laser cutting wood depends strongly on wood species and density, establishing a theoretical and experimental foundation for future research (Gochev 2016). Knowing how much energy is required to cut various materials to tight tolerances is essential not only for quality control but also for improving production efficiency, reducing costs, and guiding material-specific cutting strategy (Sobolewska and Ciecińska 2021). The goal of this study is to evaluate and compare the specific energy and energy dose required for CO₂ laser cutting of selected wood species and engineered wood-based materials to achieve a kerf width of 300 µm, corresponding to ISO 9013:2017 Class I tolerances, and determine how material density and structure influence energy dose and specific cutting energy.

MATERIALS AND METHODS Six materials were selected for this research, consisting of three natural woods: beech wood (Fagus sylvatica L.), oak wood (Quercus petraea), and spruce wood (Picea abies L.), and three engineered wood-based products: beech plywood, pine plywood, and high-density 58

fiberboard (HDF). Sample dimensions were 500 mm × 70 mm × 6 mm. All materials were acclimatized under controlled conditions to maintain moisture content between 8% and 10% before cutting. A CO₂ laser operating at a wavelength of 10.6 µm with a maximum power output of 135 W was used. Samples were processed at different power outputs (40%, 60%, 80%, and 100%, corresponding to 54 W, 81 W, 108 W, and 135 W, respectively) and at varying cutting speeds (5, 10, 15, and 20 mm·s⁻¹). The laser system uses a focusing lens with a focal length of 50.8 mm, a beam radius of 0.3 mm, and compressed air at 0.35 bar as the assist gas. The laser cuts were made tangentially on the radial surface, parallel to the grain. Kerf widths resulting from each combination of power and speed were measured using a high-resolution Keyence VHX 7000 digital microscope. Combinations of speed and power were identified for each material that yielded kerf widths as close as possible to the target width of 300 µm on both the top and bottom sides of the kerf, complying with Class I dimensional tolerances specified by ISO 9013:2017 for a 6mm thick material. To determine a suitable combination of laser cutting speed and power for each material, the goal was to achieve an average kerf width as close as possible to 300 µm, in line with Class I dimensional tolerances according to ISO 9013:2017. For each tested setting, the measured kerf widths at the top and bottom sides of the samples were compared to the target value. The differences were calculated individually for the top and bottom and then summed to represent the total deviation from 300 µm. The setting with the smallest total deviation was selected as the most appropriate. This method allowed both the entrance and exit kerf widths to be considered, minimizing the influence of tapering on the results. Where multiple settings had similar deviations, preference was given to the combination with the lower deviation from the 300 µm target kerf width. Specific energy (Ec) and energy dose (Ed) were calculated using equations 1 (Orech and Juza 1987) and 2 to quantify the energy efficiency and energy requirements for the desired kerf width under power and speed combinations. Density measurements for all materials were carried out (at w ≈ 8%) for the calculation of specific energy E c. 𝑃

𝐸𝑐 = 𝜌×𝑣×𝑒×𝑠 [ J ∙ kg −1 ] 𝐸𝑑 =

𝑃 𝑑×𝑣

[ J ∙ m−2 ]

(1) (2)

Where: P – power output of laser [W]; ρ – density of sample [kg ∙ m-3]; v – cutting speed [m ∙ s -1]; e – depth of cut [m]; s – kerf width [m]; d – beam diameter [m].

RESULTS AND DISCUSSION Table 1 presents the optimized experimental settings and the corresponding kerf widths closest to the target value of 300 µm, along with calculated values of energy dose (Ed) and specific cutting energy (Ec) across three wood species (spruce, beech, oak) and three engineered wood-based materials (beech plywood, pine plywood, HDF). 59

Tab. 1 Laser cutting parameters, kerf widths, and energy characteristics of selected wood species and wood-based materials. Material

ρw [kg∙m-3]

speed [mm∙s -1]

power [W]

Kerf width top [µm]

Kerf width bottom [µm]

Avg width [µm]

Ed [J∙m-2]

Ec [J∙kg-1]

BeechPlywood

740.1

108

387.56

297.27

342.41

2.40E+07

4.98E+06

PinePlywood

558.3

323.11

289.11

306.11

1.20E+07

3.56E+06

HDF

884.7

394.79

307.16

350.98

3.60E+07

5.78E+06

Spruce wood

332.3

367.87

251.28

309.57

9.00E+06

4.30E+06

Beech wood

728.0

408.24

232.96

320.60

1.80E+07

3.92E+06

Oak wood

747.1

375.99

207.94

291.96

1.35E+07

3.12E+06

The average kerf width varied narrowly around the desired target (291.96 µm to 350.98 µm), demonstrating the suitability of the selected laser settings in achieving class I dimensional tolerances according to ISO 9013:2017. However, noticeable variations were observed among materials, reflecting differences in their anatomical and physical structures and densities. Our Ec value for spruce wood 4.3 × 10⁶·kg⁻¹ is consistent with the findings of Kubovský et al., who reported Ec values for Picea abies L. between 4.1 × 10⁶ to 7.4 × 10⁶ J·kg⁻¹ depending on laser power, feed rate, and focal position (Kubovský et al.,2012). Influence of Material Density 3,95E+07

HDF

3,45E+07

Ed [J∙m-2]

2,95E+07 BeechPlywood

2,45E+07

Beech

1,95E+07

Spruce

9,50E+06 4,50E+06

Oak

PinePlywood

1,45E+07

250

350

Ed = 140.26∙ρw2 - 125764∙ρw + 4E+07 R² = 0.8497 450

550

650

750

850

950

ρw [kg∙m-3] Fig. 1 Relation between material density and energy dose (Ed) in CO₂ laser cutting.

Figure 1 illustrates the relationship between material density (ρw) and the energy dose (Ed) required to achieve a kerf width of 300 µm. It shows a consistent trend across the six materials tested. Spruce, with the lowest density (ρw = 332.2 kg·m⁻³), required the lowest energy dose (Ed = 9.00×10⁶ J·m⁻²), while HDF, the densest sample (ρw ≈ 885 kg·m⁻³), required the highest energy (Ed = 3.6×10⁷ J·m⁻²). A second-degree polynomial regression fitted to the data Ed = 140.26∙ρw² − 125764∙ρw + 4×10⁷ yielded a coefficient of determination R2 = 0.8497, indicating that approximately 85% of the variation in energy dose required can be explained by differences in material density. This suggests a strong, though not exclusive, dependence of energy dose on density. 60

The results show that Ed increases rapidly with density above 700 kg·m⁻³, suggesting that denser materials require more energy per unit area to reach the target kerf width. Beech, oak, and beech plywood are all close in density (around 740 kg·m⁻³), yet their required energy doses differ. Oak requires less energy than beech, despite similar density. This may be related to anatomical structure: oak is ring-porous, with large earlywood vessels that create internal variation in how heat is conducted and absorbed. Beech, as a diffuse-porous species, has a more uniform vessel distribution, which may lead to more stable heating but slower material degradation. This suggests that while density plays a major role as well as other factors like wood anatomy and adhesive content in plywood also influence the energy required for laser cutting. This interpretation is consistent with Guedes et al. (2020), who reported higher energy requirements in denser woods during mechanical processing, as well as Andrade et al. (2022), who found that wood density has a moderate positive correlation with specific cutting energy, though other factors like anatomical structure also play a role, and Açık (2023)b, who observed greater kerf widths and thermal effects in denser species during CO₂ laser cutting. Given the limited sample size (n = 6), further testing is needed to confirm the general applicability of these findings. Energy Dose (Ed) and Specific energy (Ec) 6,50E+06 HDF

6,00E+06

Ec[J∙kg⁻¹]

5,50E+06

BeechPlywood

5,00E+06 4,50E+06

Spruce

4,00E+06

PinePlywood

3,50E+06

Beech

y = 3E-09x2 - 0.0468x + 4E+06 R² = 0.7529

Oak

3,00E+06 2,50E+06 6,00E+06

1,10E+07

1,60E+07

2,10E+07

2,60E+07

3,10E+07

3,60E+07

Ed [J∙m-2] Fig. 2 Relation between energy dose delivered (Ed) and specific energy needed (Ec) in CO₂ laser cutting.

Figure 2 presents the relationship between the energy dose required to achieve a kerf width of 300 µm (Ed) and the corresponding cutting energy needed to remove 1kg for the six tested materials (Ec). The data show a positive nonlinear correlation, with Ec generally increasing alongside Ed . A fitted second-order polynomial regression Ec = 3E-09∙Ed2 – 0.0468∙Ed + 4E+06 describes this relationship with a coefficient of determination R²=0.7529, suggesting that roughly 75% of variability in Ec can be explained by changes in the applied energy dose. Materials at the lower range of energy dose (spruce, pine plywood, oak) exhibit relatively lower Ec values (around 3.0–4.5×10⁶ J·kg⁻¹). At higher Ed values, notably for beech plywood and HDF, Ec values rise as well, peaking above 6.0×10⁶ J·kg⁻¹ for HDF. This indicates that higher-density materials receiving larger energy doses require 61

disproportionately more energy per unit mass to achieve the target kerf width. The deviation observed between materials at similar Ed levels, for example, beech versus beech plywood, indicates that additional factors beyond applied surface energy and density influence cutting efficiency. Such factors could include differences in internal structure, anatomical features, or the presence of adhesives in composite materials, all affecting heat absorption, transfer, and material removal rates. However, while Ed quantifies the intensity of the laser energy applied to a material surface, Ec assesses how efficiently this energy translates into removing a mass of material. Comparing these metrics provides insights into the effectiveness of laser cutting conditions, looking into whether increased energy exposure yields proportionally efficient material removal. A key comparison in this study is between beech wood and beech plywood, materials of nearly identical densities (728.0 vs. 740.1 kg·m⁻³; a difference of only 1.7%). Despite this similarity, beech plywood required approximately 27% higher specific cutting energy (Ec), indicating that density alone cannot fully account for differences in energy demand. Additionally, the average kerf width in beech plywood was 6.8% greater. These observations suggest that engineered structures, specifically the alternating grain orientations and adhesive layers in plywood, create barriers to heat penetration and result in less uniform thermal distribution. Consequently, more energy is dissipated within the plywood structure, reducing the efficiency of material removal. Gochev described how such structures of accumulated thermal degradation residues, such as carbonized lignin in the kerf, which may contribute to reduced cutting efficiency and elevated specific energy requirements Ec (Gochev 2016). This behavior aligns with previous observations in peripheral mechanical processing, where wood species with complex grain structure or bonding agents required higher cutting energy (Carolina et al., 2022; Guedes et al., 2020). Oak, despite having similar density to beech, required the lowest specific energy (Ec = 3.12×10⁶ J·kg⁻¹). This suggests that anatomical differences and possibly enhanced thermal conductivity along the grain direction positively influence cutting efficiency. Similar observations were reported by Açık (2023)b, who noted improved laser processing characteristics in anisotropic materials, such as bamboo, due to aligned fiber structures. In contrast, HDF showed the highest energy demand in terms of both energy dose (Ed = 3.60×10⁷ J·m⁻²) and cutting energy per unit mass (Ec = 5.78×10⁶ J·kg⁻¹). This result reflects significant energy losses likely stemming from the material's high density and adhesive-rich fiber matrix. Such characteristics were previously identified by Barcikowski et al. (2004) as key factors elevating energy requirements during laser cutting. For engineered wood products like beech plywood, energy behavior during laser processing depends significantly on layered structure, alternating grain orientations, and glue-line interactions. Differences in thermal conductivity between wood layers and adhesive lines influence local heating, charring, and the efficiency of material removal. Adjusting processing parameters, cutting speed, and power output can improve energy utilization. While laser power and feed rate are often used as the main parameters in kerf width adjustment, the actual cut geometry is determined by the geometry of the focused beam, its actual spot diameter, depth of focus, and where that focus lies relative to the material surface, as well as assist gas pressure and other factors. Gochev (2023) showed that placing the focal plane at the surface gives the best results in 6 mm-thick material, whereas for thicker workpieces, moving the focus point below the surface or deeper into the material yields a narrower kerf and straighter cut walls. 62

The relationship between density, energy dose (Ed), and specific cutting energy (Ec) shows how energy demand in laser cutting is influenced by material properties. Density influences the energy dose (Ed), which in turn reflects on Ec, the energy needed to remove mass. These relationships do not imply direct dependence but show a pattern that can be useful when selecting cutting conditions. Density can be used as a starting value when estimating suitable power and speed, while Ed helps refine expectations of cutting efficiency. This chain, density to Ed to Ec, offers a basis for more informed adjustments to processing settings in future work.

CONCLUSION CO₂ laser cutting of three wood species and three engineered materials using energy dose (Ed) and specific cutting energy (Ec) to evaluate cutting performance were examined in this work. Ed showed a strong connection to material density, while Ec revealed how structure and composition affect material removal. Engineered products such as HDF and beech plywood had the highest Ec values, which may be due to their resin content and layered construction. Oak, with a similar density to beech, showed the lowest Ec, suggesting that internal structure plays a role in how materials respond to laser exposure. The observed relations between density, Ed, and Ec suggest that density could help guide the choice of laser settings, with Ed providing additional information on the energy applied and its effectiveness. Although the sample group is limited, these outcomes support further testing aimed at improving laser cutting efficiency based on measurable material properties. REFERENCES Açık, C., 2023a. Investigation of microscopic properties of some industrial wood species as a result of laser cutting. International Conference on Pioneer and Innovative Studies, 1, 451–454. https://doi.org/10.59287/icpis.872 Açık, C., 2023b. Research of computerized numerical control laser processing qualities of some wood species used ın the furniture industry. Maderas. Ciencia y tecnología, 25(25), 33–34. https://doi.org/10.4067/S0718-221X2023000100433 Andrade, C.A., Rodrigues Brito, T., Moreira Da Silva, J.R., Ferreira, S.C., Américo, A., Junior, C., Lima, J.T., 2022. Influence of basic wood density on the specific cutting energy. Research, Society and Development 11. https://doi.org/10.33448/RSD-V11I7.29674 Barcikowski, S., Ostendorf, A., Bunte, J., 2004. Laser cutting of wood and wood composites evaluation of cut quality and comparison to conventional wood cutting techniques. PICALO 2004 - 1st Pacific International Conference on Applications of Laser and Optics, 18–23. https://doi.org/10.2351/1.5056078 Carolina, A., Andrade A., Rodrigues B.T., Moreira J., Ferreira S., Américo A., Junior C., Lima J., 2022. Influence of basic wood density on the specific cutting energy. Research, Society and Development, 11(7), e13511729674. https://doi.org/10.33448/RSD-V11I7.29674 Carlos Hernández-Castañeda, J., Kursad Sezer, H., Li, L., 2011. The effect of moisture content in fibre laser cutting of pine wood. Optics and Lasers in Engineering, 49(9), 1139–1152. https://doi.org/10.1016/j.optlaseng.2011.05.008 DuPlessis, M.P., Hashish, M., 1978. High Energy Water Jet Cutting Equations for Wood. Journal of Engineering for Industry, 100(4), 452–458. https://doi.org/10.1115/1.3439460 Gochev, Zh., 2016. Laser wood cutting and modifications in its structure. II-nd International Furniture Congress: proceedings of papers, 13-15 October, Muğla Sitki Koçman University

Faculty of Technology Department of Wood Product Industrial Engineering, Turkey, pp. 210215. Gochev, Zh., 2023. Real Parameters of a Focused CO2 Laser Beam and its Determination when Using Lenses with Different Focal Lengths, 32nd International Conference on Wood Science and Technology – ICWST 2023, Unleashing the Potential of Wood-Based Materials, proceeding of papers, 7-8 December, Zagreb, pp. 67-74, ISBN 978-953-292-083-3. https://www.sumfak.unizg.hr/en/science-and-international-cooperation/conferences/icwst2023/ ISO (2017). ISO 9013:2017 - Thermal cutting — Classification of thermal cuts — Geometrical product specification and quality tolerances. https://www.iso.org/standard/60321.html#amendment [accessed 18 November 2024] Kubovský, I., Babiak, M., Cipka, Š., 2012. A determination of specific wood mass removal energy in machining by CO₂ laser. Acta Facultatis Xylologiae, 54(2), 31–37. Kúdela, J., Andrejko, M., Kubovský, I., 2023. The Effect of CO₂ Laser Engraving on the Surface Structure and Properties of Spruce Wood. Coatings, 13(12), 2006. https://doi.org/10.3390/coatings13122006 Magaznieks, E., Narica, P. 2018. Optimization of CO2 laser cutting parameters for MDF and HDF wood fiber boards. HUMAN. ENVIRONMENT. TECHNOLOGY, 22, 134–139. https://doi.org/10.17770/HET2018.22.3623 Martínez-Conde, A., Krenke T., Frybort S., Müller U., 2017. Review: Comparative analysis of CO2 laser and conventional sawing for cutting of lumber and wood-based materials. Wood Science and Technology, 51(4), 943–966. https://doi.org/10.1007/s00226-017-0914-9 Menschel, M., Pokines, J.T., Reinecke, G., 2021. Correlation between saw blade width and kerf width. Journal of Forensic Sciences, 66(1), 25–43. https://doi.org/10.1111/1556-4029.14556 Mushtaq, R.T., 2020. State-Of-The-Art and Trends in CO2 Laser Cutting of Polymeric Materials— A Review. Materials, 13(17), 3839. https://www.mdpi.com/1996-1944/13/17/3839 Naresh, C., Sameer, M.D., Bose, P.S.C., 2024. Comparative Analysis of RSM, ANN and ANFIS Techniques in Optimization of Process Parameters in Laser Assisted Turning of NITINOL Shape Memory Alloy. Lasers in Manufacturing and Materials Processing, 11(2), 371–401. https://doi.org/10.1007/S40516-024-00247-8/FIGURES/22 Naresh, P.K., 2021. Laser cutting technique: A literature review. Materials Today: Proceedings, 56, 2484–2489. https://doi.org/10.1016/j.matpr.2021.08.250 Oliveira Guedes, T., 2020. Cutting energy required during the mechanical processing of wood species at different drying stages. Ciencia y tecnología, 22(4), 477–482. https://doi.org/10.4067/S0718-221X2020005000406 Orech, J., Juza, F., 1987. Měrná energie úběru a její určení při interakci laserového záření se dřevem. Drevársky výskum, 114: 29−40. Ružiak, I., Igaz R., Kubovský I., Tudor E., Gajtanska M., Jankech A., 2024. ANN Prediction of Laser Power, Cutting Speed, and Number of Cut Annual Rings and Their Influence on Selected Cutting Characteristics of Spruce Wood for CO2 Laser Processing. Materials, 17(13). https://doi.org/10.3390/MA17133333 Sobolewska, A., Ciecińska, B., 2021. Problems of Quality Assurance and Selection of Control Criteria in Laser Cutting Operations of Wood and Wood-Like Materials. Multidisciplinary Aspects of Production Engineering, 4(1), 142–152. https://doi.org/10.2478/mape-2021-0013

ACKNOWLEDGMENT This work was supported by the VEGA Agency of the Ministry of Education, Science, Research, and Sport of the Slovak Republic and the Slovak Academy of Sciences Grant no. 1/0577/22, by the Slovak Research and Development Agency under the Contract no. APVV-20-0159 and by the Internal project agency of the Technical University in Zvolen Proj. number IPA 3/2024.

AUTHORS’ ADDRESSES Ing. Lukáš Štefančin doc. Ing. Richard Kminiak, PhD. Technical University in Zvolen, Faculty of Wood Sciences and Technology, Department of Woodworking, T. G. Masaryka 24, 960 01 Zvolen, Slovakia xstefancin@tuzvo.sk xkminiak@tuzvo.sk Ing. Rastislav Igaz, PhD. doc. Ing. Ivan Kubovský, PhD. Mgr. Ivan Ružiak, PhD. Technical University in Zvolen, Faculty of Wood Sciences and Technology, Department of Physics, Electrical Engineering and Applied Mechanics, T. G. Masaryka 24, 960 01 Zvolen, Slovakia igaz@tuzvo.sk kubovsky@tuzvo.sk ruziak@tuzvo.sk

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 67−76, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.07

BEARINGS LOAD ON A CIRCULAR SAW MILL DURING CUTTING BEECH WOODS Georgi Kovatchev – Valentin Atanasov ABSTRACT The influence of some technological factors on the magnitude of vibrations of the cutting mechanism in a circular saw mill is presented in the study. The cutting mechanism is driven by four V-belts with a “B” section. During operation, vibro-acceleration was measured using specialized measurement equipment described in the methodology. Measurements are made at four points in the radial direction. Two of them are located near the cutting tool (Ax and Ay) of the machine, and the other two (Bx and By) are near the belt pulley. The results of the experiment are presented graphically. The experiments were carried out at a rotation frequency of 1014 min-1. During the experiments, beech trees were cut down. During the research, attention was paid to some technological factors, including the feed speed of the processed material, ranging from 20 m/min to 60 m/min, and the wood thickness, ranging from 80 mm to 240 mm. The study is aimed at improving the reliability and efficiency of a machine as well as ensuring the accuracy and quality of products. Keywords: circular saw mill; cutting mechanism; vibrations.

INTRODUCTION Circular saws are widespread in practice machines. Their universality allows them to be used in diverse woodworking and furniture industry practices. They can be used to process both solid woods from different species, lengthwise and crosswise to the wood fibers, as well as wood-based materials. Circular saws have a relatively simple construction, high productivity, and are easy to maintain. Circular saws should be able to work at different cutting speeds. This is inevitably associated with the machinery required to operate at various rotational speeds. They are a precondition for the emergence of varying cutting forces that create conditions for loads in the mechanisms, and an increased noise and vibration levels lead to errors during operation (Droba et al., 2015, Halim et al., 2024, Kang et al., 2025, Merhar 2021, Orlowski et al., 2020, Schajer et al., 2012, Svoren et al., 2021, Vesely et al., 2012, Vitchev et al., 2019, Vukov et al., 2012, Wei et al., 2020, Wu et al., 2021). All these loads are borne by the machine bearings, which are constantly subjected to dynamic loads of varying magnitudes and origins. The quality of machining significantly influences every detail. Each part must have an accurate shape, dimensions, and roughness class that meet the tolerances specified in the technical documentation (Kminiak et al., 2018; Sydor et al., 2021). All these requirements relate to the proper selection of technological cutting modes. The quality of the finished product, the production time, and also the price of the products depend strongly on them. Circular saws in good working order and their 67

operating modes have a significant impact on the entire work process of the enterprise. Constant control and technical serviceability are mandatory parts of the working day in every woodworking and furniture company (Kovatchev et al., 2022). The aim of the present work is to measure and analyse the vibro acceleration (а, m/s2) in the cutting process of beech woods on a circular saw mill. The object of research is the bearing load under varying technological factors. The study is aimed at improving the reliability and efficiency of a circular sawmill machine to ensure the accuracy and quality of products.

MATERIALS AND METHODS The experiment in the present work was conducted using a circular saw mill Kara KallionKonepaja Oy – Finland. The general view of the machine is shown in Figure 1.

Fig. 1 Circular saw mill Kara KallionKonepaja Oy – Finland,generalview.

Fig. 2 Circular saw blade D = 1060 mm.

The cutting mechanism of the selected machine has a relatively simple design. This fact helps a lot to conduct the experiments correctly. The mechanism is driven by an asynchronous electric motor with a power of 55 kW, as proposed by the machine manufacturer, and a rotation frequency of 1500 min-1. Torque from the electric motor to the working shaft of the machine is transmitted using a belt drive. Four V-belts with a “B” section are used. The operating frequency of the machine is 1014 min-1 which is entirely normal given the diameters of the circular saw blades used. The selected rotational speed is realized by pulleys mounted on the electric motor shaft and the machine shaft. The cutting tool used for the experiments was a circular saw blade with a diameter of 1060 mm shown in Figure 2. The saw is fixed to the circular shaft by an inner and outer circular tool flange, a flange nut, and a pin. The technical data of the cutting tool are shown in Table 1. The inscriptions in the table are: D - diameter of the circular saw blade, d – blade shaft diameter, B – milling width, α – back angle of cutting,  – angle of sharpening,  – front angle of cutting, z – number of teeth.

Tab. 1 Technical data of the cutting tool. Type of instrument Circular saw blade

D mm 1060

d mm 55

α  15

B mm 5,5

  50

  25

z бр 60

Material of the teeth HM

The cutting speed was calculated by Formula 1. At a rotation frequency of 1014 min-1 the calculated cutting speed was v = 56 m/s. V = π.D.n, m/s,

(1)

Where: D – diameter of the cutting tool, m; n –rotation frequency of the cutting tool, s-1. During the experiment, beech (Fagus sylvatica) boards were cut. They have a length of 2500 mm, a width of 400 mm, and thicknesses of 80 mm, 160 mm, and 240 mm. The moisture content of the boards is 40.3% and their density is 823 kg/m 3. Some of the beech boards are shown in Figure 3.

Fig. 3 Beech (Fagus sylvatica) boards.

The influence of several critical factors in the cutting process on the vibro-acceleration (а, m/s2) measured in the bearing housings is examined in the paper. The impact of feed speed (U, m/min) and wood thickness (h, mm) on vibro acceleration (а, m/s2) was determined using a planned two-factor regression analysis. During the research, the feed speed of the processed material is 20, 40, and 60 m/min, and the wood thickness is 80,160, and 240 mm. Table 2 shows the studied factors and their levels in open and coded form. Tab. 2 Survey factors. Factors Feed speed U, [m/min] Wood thickness h, [mm]

Open 20 80

Cod. −1 −1

Factors levels Open Cod. 40 0 160 0

Open 60 240

Cod. 1 1

Table 3 shows the experimental matrix. Feed speed is indicated by X 1 and wood thickness by X2. The results were calculated by the software products QstatLab5 and Microsoft Excel.

Tab. 3 Experimental matrix. № 1 2 3 4 5 6 7 8 9

U, m/min 60 60 20 20 40 40 60 40 20

h, mm 240 80 240 80 160 240 160 80 160

X1 +1 +1 -1 -1 0 0 +1 0 -1

X2 +1 -1 +1 -1 0 +1 0 -1 0

The intensity of the vibrations was assessed based on the vibro-acceleration (а, m/s2) measured at different working modes of the machine. The measurements were performed at four measurement points on the bearing housings of the machine's main shaft. Two of them are located near the cutting tool (Ax and Ay) of the machine, and the other two (Bx and By) are near the belt pulley. The circular saw is supported by two double-row self-aligning ball bearings 2312 according to the machine manufacturer. The technical data of the bearing are shown in Table 4. The inscriptions in the table are: D - outer diameter, d – inner diameter, B – width, C – basic dynamic load rating, and C0 – basic static load rating. Tab. 4 Technical data of the bearings. Bearing type Double-row self-aligning ball bearing 2313

D mm

d mm

B mm

C kN

C0 kN

Maximum allowable rotational speed, min-1

130

87.1

25.8

5200

The bearings are fixed in a monolithic cast iron body Figure 4. They take on all loads during operation and transmit them to the machine body (www.nskeurope.com, https://www.skf.com). The measurement points on each bearing housing are located mutually perpendicular, radial to the main shaft of the machine Figure 5 (БДС ISO 10816 – 1:2002).

Fig. 4 Cast iron monolithic bearing body.

Fig. 5 Measurement points.

The basic scheme of the cutting mechanism is shown in Figure 6. The distance between the circular saw and the front bearing is 240 mm, the distance between the circular saw and the rear bearing is 1040 mm, the distance between bearings is 800 mm and the distance between the rear bearing and belt pulley is 200 mm.

Fig. 6 Cutting mechanism.

Vibro acceleration (а, m/s2) was measured using a specialized device, the PCE VT2700, shown in Figure 7. The measurement points are located on the bearing housing of the machine. It responds significantly to the dynamic state in Figure 8.

Fig. 7 PCE VT-2700 Vibration Tester.

Fig. 8 Measuring sensor.

RESULTS AND DISCUSSION The experimental part includes work trials in cutting beech (Fagus sylvatica) boards. The presented results are for the vibro acceleration (а, m/s2) measured at points A for the bearing near the cutting tool and B for the bearing near the pulley. The measurement directions are respectively: Ax and Bx - in direction parallel to the feed direction. Ay and By - in direction perpendicular to the feed direction. Figure 9 shows the vibrо acceleration measured at idle in the four directions.

Fig. 9 Vibro acceleration measured at idle.

The regression equations 2 and 3 show the influence of factors at the cutting beech (Fagus sylvatica) boards at point A. Ax = 137.666 + 35.666x1 + 16.833x2 - 3x1x1 – 2.5x2x2 -7.25x1x2 Ay = 104.111 + 34.666x1 + 20.833x2 + 10.333x1x1 – 6.166x2x2 + 3.25x1x2

(2) (3)

As it can be seen from the regression equations obtained, the most decisive influence on the vibro acceleration (а, m/s2) at the cutting of beech (Fagus sylvatica) boards is the factor of feed speed (U, m/min). The regression coefficients before X1 are respectively 35.666 for the Ax direction and 34.666 for the Ay direction. The thickness of the processed material (h, mm) is the second most important factor. The regression coefficients before X1 are respectively 16.833 for the Ax direction and 20.833 for the Ay direction. The influence of the studied factors in the Ax direction can be seen in Figure 10. Figure 11 shows the vibration acceleration change in the Ay direction.

Fig. 10 Vibro acceleration measured at Ax direction.

Fig. 11 Vibro acceleration measured at Ay direction.

Figure 10 shows that increasing the feed speed (U, m/min) of the processed material increases the vibro acceleration (а, m/s2) increases. This tendency was observed in all three thicknesses (h, mm). The lowest measured values are when cutting boards with a thickness of 80 mm are used. The acceleration varies from а = 70 m/s2 to а = 160 m/s2. The highest acceleration values were measured at a feed speed of 60 m/min and a board thickness of 240 mm. The acceleration varies from from а = 120 m/s2 to а = 180 m/s2. The same trend is observed in the Ay direction Figure 11. As feed speed increases (U, m/min), the vibro acceleration (а, m/s2) increases. This tendency was observed in all three thicknesses (h, mm). Slightly lower acceleration values were measured in the Ay direction. For the most significant board thickness of 240 mm and a feed speed of 60 m/min, the value of a varies from a = 92 m/s2 to a = 165 m/s2. The processed material is recommended to be fed at a lower speed. For this particular case, 20 m/min and 40 m/min. This will reduce the machine's productivity but will improve machining quality and accuracy (KANG et al. 2024, KOVATCHEV et al. 2022, KOVATCHEV et al. 2023, NASIR et al. 2020). Decreases in vibro-acceleration are a prerequisite for maintaining the bearing's technical characteristics for an extended period. The regression Equations 4 and 5 show the influence of factors on the cutting beech (Fagus sylvatica) boards at point B

Вx = 69.222 + 11x1 + 11.333x2 + 2.666x1x1 – 1.333x2x2 -0.75x1x2

(4)

Вy = 62 + 13.5x1 + 11.333x2 – 5.5x1x1 - 3x2x2 + 3x1x2

(5)

From Equation 4, we can see that in the Bx direction, the two studied factors, feed speed (U, m/min) and thickness of the processed material (h, mm), have the same influence on the measured vibro acceleration (а, m/s2). The regression coefficients before X1 and X2 are approximately equal (11). In the Вy direction, the most decisive influence on the vibro acceleration (а, m/s2) at the cutting of beech (Fagus sylvatica) boards is the factor of feed speed (U, m/min). The regression coefficient before X1 is 13.5. The thickness of the processed material (h, mm) is the second important factor – X2 = 11.333. Figure 12 and Figure 13 show the variation in the vibro-acceleration measured in the Вx and Вy directions..

Fig. 12 Vibro acceleration measured at Bx direction.

Fig. 13 Vibro acceleration measured at By direction.

Figure 12 shows that, in the Вx direction, as the feed speed (U, m/min) increases, the vibro acceleration (а, m/s2) increases. This tendency was observed in all three thicknesses (h, mm). The lowest measured values are when cutting boards with a thickness of 80 mm are used. The acceleration varies from а = 46 m/s2 to а = 72 m/s2. The highest acceleration values were measured at a feed speed of 60 m/min and a board thickness of 240 mm. The acceleration varies from а = 71 m/s2 to а = 94 m/s2. The same trend is observed in the By direction. This is shown in Figure 13. When the feed speed grows (U, m/min), the vibro acceleration (а, m/s2) increases. This tendency was observed in all three thicknesses (h, mm). The highest measured acceleration values are at a feed speed of 60 m/min and a board thickness of 240 mm, from a = 48m/s2 to a = 80 m/s2. From the results obtained at point B, it is clearly seen that the vibro acceleration (а, m/s2) levels are lower than at point A. This is entirely normal, as point B is significantly further from the cutting area, and the main load is taken by the bearing at point A.

CONCLUSION Based on the conducted experimental studies, the following more critical conclusions and recommendations can be drawn: ➢ The strongest influence on the vibro acceleration (а, m/s2) at the cutting of beech (Fagus sylvatica) boards is the factor of feed speed (U, m/min). The thickness of the processed material (h, mm) is the second most crucial factor. It is evident from the obtained regression equations and the resulting graphs. The presented data show that 73

the selected operating modes of the circular machine do not create a prerequisite for entering dangerous resonance zones. It is recommended to feed the processed material at lower feed speeds (U, m/min). It puts less strain on the bearings and protects the machine from costly repairs. On the one hand, a lower feed speed will reduce the machine's productivity. But on the other hand, the lower feed speed reduces vibro acceleration, shocks during working modes, which is a prerequisite for better quality of the processed materials (Xinyu et al., 2023, Kang et al., 2025, Kovatchev et al., 2022, Mohammadpanah et al., 2017, Orlowski et al., 2007, Svoren et al., 2015, Svoren et al., 2022, Ukvalbergiene et al., 2007). ➢ Bearing A, which is located next to the cutting tool, is significantly more loaded during operation. This bearing serves as the central component of the vibrations caused by cutting forces and transmits them to the machine body. Furthermore, this is the bearing exposed to a higher risk of damage. ➢ Bearing B, which is located near the pulley, is less loaded. It is quite far from the cut area. Тhe vibrations caused by cutting forces do not load it as much as bearing A. Accordingly, the risk of damage is lower.

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Kovatchev, G., Atanasov, V., Radkova, I., 2023. Influence of mechanical oscillations on the accuracy of making grooves in wood-based materials, Pro Ligno, Volume 19, Issue 3, pp. 3-9, Online ISSN 2069-7430, ISSN-L 1841-4737. Merhar, M., 2021. Influence of temperature distribution on circular saw blade natural frequencies during cutting, BioResources 16(1), ISSN 1930-2126, pp. 1076-1090. Mohammadpanah, A., Hutton, S., 2017. Theoretical and experimental verification of dynamic behavior of a guided spline arbor circular saw. Shock and Vibration, Volume 2017, Arcital ID 6213791, https://doi.org/10.1155/2017/6213791 Nasir, V., Mohammadpanah, A., Cool, J., 2020. The effect of rotation speed on the power consumption and cutting accuracy of guided circular saw: Experiment measurement and analysis of saw critical and flutter speeds. Wood Materials Science & Engineering, Volume 15, Issue 3, pp 140-146, https://doi.org/10.1080/17480272.2018.1508167 Orlowski, K., Sandak, J., Tanaka, C., 2007. The critical rotational speed of circular saw: simple measurements method and its practical implementations, Journal of Wood Science, Volume 53, pp. 388-393. DOI: 10.1007/s10086-006-0873-5 Orlowski, K., Dudek, P., Chuchala, D., Blacharski, W., Przybylinski, T., 2020. The design development of the sliding table saw towards improving its dynamic properties, Applied Sciences-Basel 10(20). https://doi.org/10.3390/app10207386 Schajer, G., Ekevad, M., Gronlund, A., 2012. Practical measurement of circular saw vibration mode shapes. Wood Materials Science & Engineering, Volume 7, Issue 3,pp 162-166, https://doi.org/10.1080/17480272.2012.678383 Svoren, J., Javorek, L., Droba, A., Pauliny, D., 2015. Comparison of natural frequencies values of circular saw blade determination by different methods, Drvna Industrija, Zagreb, 66(2), pp. 123128, ISSN 0012 – 6772. Svoren, J., Nascak, L., Koleda, P., Barcik. S., Nemec, M., 2021. The circular saw blade body modification by elastic material layer effecting circular saws sound pressure level when idling and cutting, Applited Acoustics, Volume 179, https://doi.org/10.1016/j.apacoust.2021.108028. Svoren, J., Nascak, L., Barcik, S., Koleda, P., Stehlik, S., 2022. Influence of circular saw blade desing on reducing energy consumption of a circular saw in the cutting process, Applited Sciences, 12(3), 1276, https://doi.org/10.3390/app12031276 Sydor, M., Mirski, R., Stuper-Szablewska, K., Rogozinski, T., 2021, Efficiency of Machine Sanding of Wood, Applied Sciences, Volume 11 – Issue 6 /2860/ March 2 2021, ISSN 2076 – 3417, https://doi.org/10.3390/app11062860 Ukvalbergiene, K., Vobolis, J., 2007. Research of inter-impact of wood circular saws vibration modes, Wood Research, Volume 52(3), pp. 89-100. Vesely, P., Kopecky, Z., Hejmal Z., Pokorny, P., 2012. Diagnostics of Circular Sawblade Vibrations by Displacement Sensors, Drvna Industrija, Zagreb, 63(2), pp. 81-86, ISSN 0012 – 6772. Vitchev, P., Angelski, D., Mihailov, V., 2019. Influence of the processed material on the sound pressure level generated by sliding table circular saw, Acta Facultatis Xylologiae Zvolen, 61(2): 73−80, 2019, https://doi.org/10.17423/afx.2019.6 Vukov, G., Gochev, ZH., Slavov, V., 2012, Torsional Vibrations in the Saw Unit of a Kind of Circular Saws. Numerical Investigationsof the Natural Frequencies and Mode Shapes. Proceedings of Papers, 8th International Science Conference “Chip and Chipless Woodworking Processes”, Zvolen, 2012, ISBN 978-80-228-2385-2, pp. 371 – 378. Wei, F., Zhang, J., Zhou, H., Di, H., 2020. Investigation on the vibration characteristics of circular saw blade with different slots, IOP Conference Series: Journal of Physics, Volume 1633, https://doi.org/10.1088/1742-6596/1633/1/012006 Wu, T., Wang, D., Zhao, M., 2021. Optimization of diamond circular saw blade vibration noise analysis, IOP Conference Series: Materials Science and Engineering, Volume 1138, https://doi.org/10.1088/1757-899X/1138/1/012045 Xinyu, Y., Yunqi, C., Hongru, Q., Tao, D., Nanfeng, Z., Baojin, W., 2023. The transvere vibration characteristics of circular saw blade on mobile cantilever-type CNC sawing machine, Machines, 11(5), https://doi.org/10.3390/machines11050549

AUTHORS’ ADDRESSES Chief Assist. Prof. GeorgiKovatchev, PhD. Assoc. Prof. Valentin Atanasov, PhD. University of Forestry, Faculty of Forest Industry Kliment Ohridski Blvd. №10, 1797 Sofia, Bulgaria g_kovachev@ltu.bg vatanasov_2000@ltu.bg

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 77−87, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.08

PROPERTIES OF WOOD SURFACE COATED WITH OIL WAX Krasimira Atanasova – Dimitar Angelski – Dobriyan Dobriyanov ABSTRACT The research is aimed at establishing the changes in colour, gloss, hydrophobicity, and roughness of wood surfaces after treatment with hard wax oil, as well as the number of layers and the appropriate amount of liquid system required to achieve an effective coating. The water permeability of the coating was used as a criterion. Commercial hard wax oil was applied to the wood of spruce (Picea abies Karst.), aspen (Popolus tremula L.), beech (Fagus sylvatica L.), ash (Fraxinus excelsior L.), and European oak (Quercus robur L.). Changes in the colour of the wood substrates were evaluated visually. Gloss was measured using a gloss meter in accordance with ISO 2813:2014. Changes in roughness were assessed through the parameters Rz and RSm. Measurements were conducted with a contact surface roughness tester. Hydrophobicity was evaluated using the sessile drop method. It was found that a twolayer coating is optimal, and that the density, composition, and structure of the substrate influence the amount of liquid system required to form a coating with uniform colour and gloss. The coating was classified as unstable. Changes in colour, roughness, gloss, and hydrophobicity of the treated surfaces were established. No raising of the wood grains was found. The characteristics of the substrate had a significant impact on the coating properties. Keywords: hard wax oil; wood surface; water permeability; contact angle; gloss.

INTRODUCTION Products based on vegetable oils and natural waxes provide an effective, environmentally friendly protective coating for wooden surfaces (Teacă et al., 2019). Vegetable oils are natural, renewable raw materials obtained by esterification of glycerol with saturated or unsaturated fatty acids (Guner et al., 2006). Depending on the degree of saturation of the fatty acids they contain, oils are classified as drying, semi-drying, or nondrying. The first two types are used as binders in coating systems. Through radical chain oxidation, they harden upon contact with air, forming spatially cross-linked structures. To accelerate the process, siccatives are used (Bulian and Graystone, 2009). Linseed, tall, soybean, nut, and hemp oils are most effective in protecting wood from microorganisms and insects (Teacă et al., 2019). Coatings containing tall oil, linseed oil, or tung oil reduce water absorption and consequently increase the dimensional stability of treated wood surfaces (Koski, 2008; Humar and Lesar, 2013). Waxes are used as an additive in coating systems to preserve the appearance (gloss) and softness of wood. They are easy to apply and impart hydrophobic properties to the treated surfaces (Liu et al., 2011). They are used for non-biocide protection of outdoor wood structures, to increase water resistance, and to reduce photochemical degradation. They 77

contain waterborne or organic solvent-soluble, long-chain, lipophilic compounds that form a coating while preserving the substrate's original appearance and structure (Bulian and Graystone, 2009). The most effective method for imparting hydrophobicity to a wood surface, recommended by Janesch et al. (2020), is a combination of oil penetrating the wood surface to a certain extent with wax. Colour and gloss are essential decorative properties for any coating. Colour evaluation is based on spectral estimates of the background colour's wavelength, its saturation, and its brightness. Gloss is determined by the degree of orientation of the rays reflected by the coating (Kavalov and Angelski, 2014). Gloss quality depends on several factors, including wood species, chemical composition, coating system type, number of layers, and substrate preparation (Bekhta et al., 2014). Roughness reflects the presence, number, and size of surface irregularities at a micro level. For wood surfaces, roughness is a combination of the anatomical roughness specific to each particular wood species and the conditions of their processing (Kavalov and Angelski, 2015). It is evaluated using different groups of roughness parameters, depending on the materials and technological processes under investigation. Hydrophobicity is an indicator of the degree of wetting of a solid substrate by a liquid. An indispensable tool for characterizing wetting is the measurement of the water contact angle (WCA) (Arminger et al., 2022). According to Shi and Gardner (2001), in addition to the stage of creating a contact angle at the boundary interfacial surfaces, wetting also includes the stages of spreading the liquid phase onto the surface of the solid phase and of the liquid phase penetrating into the porous solid phase. Hydrophobicity depends on many factors, including surface tension in the contact zone, chemical composition and heterogeneity of the phases, roughness of the contacting surfaces, etc. The permeability of coatings to water and water vapour is a major factor in their wood protection function. Permeability determines the flow of liquids or gases through a solid surface. Liquid water and water vapour uptake are determined by coating film thickness, the number of coats, and the coating system formulation (Angelski and Atanasova, 2021). The wood of each tree species is characterized by an individual structure. Its composition includes up to 30% of various extractive substances: tannins, resins, polyphenols, waxes, fats, starch, essential oils, and minerals (Spiridon, 2020), which influence the properties of the coating formed on its surface. In this regard, the aim of the present study is to assess the water permeability of a multilayer coating to establish the optimal number of layers and the appropriate amount of liquid system to obtain an effective coating, as well as the changes in colour, gloss, hydrophobicity, and roughness of wood surfaces as a result of the coating application.

MATERIALS AND METHODS For the treatment of the specimens, a colorless gloss version of hard wax oil (Hartwachs-Öl Original, OSMO, Germany), intended for interior use, was chosen According to the manufacturer, the product contains renewable plant-based raw materials: sunflower oil, soybean oil, thistle oil, carnauba wax and candelilla wax, paraffin, siccatives and waterrepellent additives, as well as unscented white spirit (benzene-free). The product complies with the requirements of Directive 2004/42/EC. It is recommended for all types of wood flooring and furniture. Application is possible by brush, roller, or pad. A two-layer liquid 78

system is recommended, with 30–40 g/m2 per layer applied after the previous layer has solidified. The coating is safe for people, animals, and plants. Wood of spruce (Picea abies Karst.), aspen (Popolus tremula L.), beech (Fagus sylvatica L.), ash (Fraxinus excelsior L.), and European oak (Quercus robur L.) without flaws and visible discolourations was selected for the experiment. The specimens were manufactured in accordance with EN 927-5:2023, with six specimens of each wood species and an additional 18 spruce specimens, of which six were used as controls. The density of each specimen was measured. The average density of wood from different tree species, the dimensions of the specimens, and the orientation of the wood grains are presented in Tab. 1. Tab. 1 Density of wood from different tree species. Dimensions and orientation of specimens. Density, 3 kg/m 460 600 740 750 770

Tree species Spruce (Picea abies Karst.) Aspen (Popolus tremula L.) Beech (Fagus sylvatica L.) Ash (Fraxinus excelsior L.) Oak (Quercus robur L.)

Dimensions L x B x δ, mm 150×70×20 150×70×20 150×70×20 150×70×20 150×70×20

Surface orientation Tangential Radial-tangential Radial-tangential Radial Radial-tangential

The wood samples were sawn and milled into flat surfaces. The moisture content of all control specimens ranged from 8% to 10%, as measured with a contact hydrometer (Hydromette Compact, Gann, Germany). The test specimens were conditioned for а month at 23 ± 2 °C and 50 ± 5 % R.H. Before treatment, the surfaces were sanded with P120 sandpaper. The liquid system was applied with a pad until a uniform and homogeneous layer was obtained. The specimens were cured for 24 hours. The experiments were conducted seven days after the coating had dried. Application of the liquid system, coating curing, and subsequent conditioning were performed at a controlled temperature of 23 ± 2 °C and relative humidity of 50 ± 5%. The surfaces were not sanded before applying the next layer of the coating system. The water permeability test was carried out in accordance with EN 927-5:2023. The weight of the specimens after 72 hours of drying was also measured. The amount of applied liquid system (Q) was calculated using equation (1): 𝑄=

𝑚𝑎 −𝑚𝑏 𝐴

(g.m-2)

(1)

Where: ma – weight of the specimen after coating(g); mb – weight of the specimen before coating (g); A – area of the treated surface (m2). Colour changes were assessed visually. Gloss was measured with a gloss meter GM 100 (Deutschland GmbH, Germany) according to ISO 2813:2014. Three measurements were made on each specimen, along the wood grain length. To assess the roughness, a surface roughness tester model SJ-210 (Mitutoyo, Japan) with a diamond V-shaped probe tip with a radius R = 5 µm was used, with the following settings: - profile – R, profile filter – Gauss; - evaluation length le = 15 mm; - number of section lengths nsc = 6; - section length lsc = 2.5 mm, - measuring speed 0.25 mm/s. 79

Measurements were taken across the wood grain at the same evaluation lengths after each layer of the coating was applied, as well as on the initial (sanded) surface. Six measurements were made on each specimen. The following parameters were selected for observation and analysis: - arithmetic mean height of the assessed profile Ra; - maximum height Rz; - mean profile element spacing RSm. Parameters are defined by ISO 21920-2:2021. Hydrophobicity was assessed with a contact-angle measuring system, according to the principles and procedures described in EN 828:2013. The OneAttension software, Version 4.1.4 (r 9753) from Biolin Scientific, was used. Measurements were performed along the wood grains with a drop volume of 7.3 µl at a temperature of 20 °C. Deionized water was used as the test liquid. The change in the mean water contact angle WCA mean (°), and the change in the baseline (mm) were evaluated. Twelve measurements were carried out on one specimen of each tree species. Preliminary experiments were conducted to determine the flow time and the system's solid content. A flow time of 56 s was measured using a 6-mm flow cup, according to ISO 2431:2019, and a solid content of 65% for a single-layer coating. Excel was used for statistical processing of the measured data and graphical presentation of the results.

RESULTS AND DISCUSSION Water permeability of the coating After conducting the water permeability test, no cracks or defects were found on the surfaces of the specimens. The results of the measurements for single-layer, double-layer, and triple-layer coatings are presented in Table 2. Tab. 2 Average values of the weight of spruce specimens before and after the water permeability test, and after 72 hours of drying. Amount of water absorbed. Coating layers One layer Two layers Three layers

Weight before the test, g 102.47 96.39 100.48

Weight after the test, g 110.95 101.94 106.84

Weight after 72 hours of drying, g 105.32 98.6 103.09

Amount of water absorbed, g.m-2 818 491 494

The results show that, according to EN 927-2:2022, this coating system is non-stable. It can be used indoors or outdoors for end-use categories such as overlapping cladding, fencing, garden sheds, open cladding, and ventilated rain screen (EN 927-1:2013). The significant reduction in water permeation observed after applying a second layer of the coating system and the insignificant change after applying a third layer indicate that the twolayer coating is optimal. The decrease in the mass of absorbed water 72 hours after removing the test specimens from the water indicates that the coating is permeable to water vapour. Amount of oil wax system applied Figure 1 shows the dependence of the amount of applied oil required to form a twolayer coating on the substrate density. 80

Fig. 1 Influence of wood density on the amount of oil applied (for a two-layer coating).

The graph in Figure 1 shows an inverse relationship between the amount of liquid system applied (Q) and the density of the wood substrate. The exception is spruce wood, which shows that the treated surface orientation (Atanasova and Savov, 2023) and wood composition (in this case, the presence of resin) also influence the results. It can be observed that Q for ring-porous wood is compared to that of diffuse-porous wood. When comparing the amount of liquid system applied to beech and ash, as well as to ash and oak, it can be argued that wood structure has a more significant influence on Q than density. However, this conclusion is conditional, as the two parameters are interdependent. Changes in colour and gloss It was found that the surfaces with a two-layer coating were pleasant to the touch, changed colour to varying degrees (Fig. 2), and acquired a gloss (Table 3). The texture was visible and clearly expressed. No grain-raising of the wood was felt.

Spruce Aspen Beech Ash Oak (Picea abies Karst .) (Popolus tremula L.) (Fagus sylvatica L.) (Fraxinus excelsior L.) (Quercus robur L.) Fig. 2 Change in the colour of the specimens due to the formation a two-layer coating: 0 – initial surface; 2 – two-layer coating.

The significant changes in the colour and texture contrast of the specimens from hardwood (Fig. 2) indicate a reaction between the oil that has penetrated the substrate and the wood's natural colourants. No migration and redistribution of the colourants was observed. It suggests that the coating system reacts more slowly with the colourants in the wood substrate than water and that its movement is limited (Angelski and Atanasova 2021). The observation is consistent with studies by Demirel et al. (2016) and Zhang and Song 81

(2024), which indicate that oil penetration into the substrate occurs through conducting vessels, not through cell walls. Tab. 3 Change in the gloss values of the specimens due to the formation of a two-layer coating. Average values, GU Tree species

Initial surface

Spruce Aspen Beech Ash Oak

Change, %

Two-layer coating

20 ̊

60 ̊

85 ̊

20 ̊

60 ̊

85 ̊

20 ̊

60 ̊

85 ̊

2.78

5.23

4.80

3.40

12.25

18.68

134

289

2.63

5.07

6.06

3.68

15.60

31.68

208

423

2.55

3.83

11.10

5.92

25.42

53.63

132

563

383

2.75

4.53

8.10

4.18

17.93

34.63

296

328

2.02

3.17

10.22

2.93

11.68

28.13

269

175

Based on the results presented in Table 3, surfaces with a two-layer hard wax oil coating are described as matte to semi-gloss (ISO 2813:2014). For different substrates, the gloss unit values have increased to various degrees. The increase was most significant for beech. The least noticeable change was for spruce. Similar minimal changes in colour and glosses of spruce wood treated with oil-wax emulsion were also reported by Janesch et al. (2020). Surface roughness Table 4 presents the arithmetic mean values of the parameters Rz and RSm, the variation coefficients, and the accuracy indicators in the three consecutive phases of processing.

Oak

Ash

Two-layer coating

Initial surface

Single layer coating

Two-layer coating

Initial surface

Single layer coating

Two-layer coating

Accuracy indicator p, %

Single layer coating

Variation coefficient V, %

Initial surface

Average values, µm Roughness parameter

Beech

Aspen

Spruce

Tree species

Tab. 4 Average values of the roughness parameters after each processing phase, variation coefficients V, %, and accuracy indicators p, %.

Ra Rz

5.68* 43.22

5.56 42.96

5.02* 37.79

5.10* 10.38

5.09 4.74

6.02* 10.04

2.28* 4.64

2.27 2.12

2.69* 4.49

RSm Ra Rz

237.98* 5.67* 41.41

240.98 5.26 38.82

337.80* 4.48* 30.53

7.69* 5.70* 6.86

15.01 3.47 7.03

16.62* 6.08* 6.63

3.44* 1.47* 1.77

6.71 0.90 1.81

7.43* 1.57* 1.71

RSm

248.36*

309.77

427.15*

9.49*

8.79

16.04*

2.45*

2.27

4.14*

5.52*

4.31

3.67*

13.64*

11.04

15.93*

3,52*

2.85

4.11*

39.44

28.91

23.20

15.48

9.22

14.89

4.00

2.38

3.85

RSm

285.92*

431.99

625.75*

12.35*

25.41

25.48*

3.19*

6.56

6.58*

9.88*

8.95

7.20*

19.55*

19.77

21.64*

5.05*

5.10

5.59*

75.76

67.56

52.29

18.83

16.83

19.86

4.86

4.35

5.13

RSm Ra

481.47*

676.07

769.46*

16.13*

24.61

20.68*

4.65*

6.35

5.53*

8.36*

7.43

7.32*

19.99*

16.40

22.91*

5.16*

4.24

5.91*

69.36

63.03

57.14

26.54

21.62

24.20

6.85

5.58

6.25

RSm

430.35*

454.86

581.07*

37.85*

17.82

17.88*

9.77*

4.60

4.62*

* Atanasova (2025)

The presented data show that during the formation of a multilayer coating, the arithmetic mean height of the profile (Ra) and the maximum height (Rz) decrease, while the mean profile element spacing (RSm) increases, indicating that the surfaces become less rough. No raising of the wood grains was detected. The increase in the values of the coefficient of variation and the accuracy index after forming the second layer of the coating is impressive. This shows that with the chosen application technology, surfaces with a singlelayer coating have a more homogeneous structure than surfaces with a double-layer coating. A similar trend was found for the coefficient of variation and the accuracy indicators for processing the gloss measurements. These results can be explained by the nano-structured surface of the wax emulsion coating (Arminger et al., 2022). The values of the coefficient of variation and the accuracy index for the Rz parameter for aspen wood are an exception to this trend, which can be explained by the fuzzy structure of the aspen surface. Hydrophobicity Table 5 presents the changes in the average water contact angle WCA mean and the baseline B for the initial surfaces, and for the surfaces with a two-layer coating 5 seconds after the start of the test. Tab. 5 Evaluation of the change in the hydrophobicity of surfaces due to the formation a two-layer coating through the changes in the water contact angle WCA mean (°), and the baseline B (mm). Tree species Spruce Aspen Beech Ash Oak

Initial surface WCA mean, ° 78.742 23.957 61.072 67.718 70.675

Average values Two-layer coating

B, mm WCA mean, ° 3.546 81.592 6.347 101.917 4.193 88.046 3.992 100.108 3.842 98.230

B, mm 3.308 2.858 3.184 2.839 2.830

Change, % Δ WCA 3.62 325.42 44.17 47.83 38.99

ΔB -6.71 -54.97 -24.06 -28.88 -26.34

The presented results show a clearly pronounced hydrophobicity of the treated surfaces. The most significant change is for aspen. The values for spruce have changed the least. Figure 3 presents the dynamics of the change in the mean water contact angle for the initial surfaces over the course of 30 seconds.

Fig. 3 Time dependence of the static contact angle with water over the course of 30 s for the initial surfaces.

Figure 4 presents the dynamics of the change in the baseline length for the initial surfaces in the first 5 seconds of the measurement.

Fig. 4 Time dependence of the baseline over the course of first 5 s of the measurement for the initial surfaces.

The presented graphs show that the decrease in the contact angle upon wetting of the various wood substrates is due first to water penetration into the substrate and then to liquid spreading over the surface. The highest penetration rate occurs in aspen. Given the relatively constant values of the angle for the surface of spruce wood, it can be argued that under the conditions of the measurements, evaporation is negligible. The sharp changes in the curve for aspen wood reflected the presence of partially detached wood grains characteristic of its sanded surface. Figure 5 shows the dynamics of the change in the mean water contact angle for the treated surfaces over the course of 30 seconds. The changes in the baseline after the first second range from 0.001 to 0.005 mm.

Fig. 5 Time dependence of the static contact angle with water over the course of 30 s for the treated surfaces.

From the graphs presented in Figures 3 and 5, it can be concluded that treatment with hard wax oil homogenizes wood surfaces, limits wetting and water spreading by creating a nano-structured surface, and significantly reduces water penetration into the substrate. These results extend the conclusions made by Arminger et al. (2022) for superhydrophobic surfaces obtained by treating beech with aqueous wax dispersion, and for oil 84

wax emulsions applied to surfaces of various wood species. They also confirm the influence of surface pretreatment on the size of the WCA and on the degree of hydrophobicity achieved.

CONCLUSION The goal of the presented study was to determine the changes in colour, gloss, hydrophobicity, and roughness of sanded surfaces of spruce, aspen, beech, ash, and European oak after treatment with hard wax oil, as well as the number of layers and the appropriate amount of liquid system applied to obtain an effective coating. The water permeability of the coating was used as a criterion. It was found that a two-layer coating was optimal. The two-layer coating was classified as unstable in accordance with EN 927-2:2022. Changes in colour, reductions in roughness, and increases in gloss and hydrophobicity of the treated surfaces were established. No raising of the wood grains was found. In the case of ring-porous wood species, the coating was coloured and had increased texture contrast due to the reaction of the coating system with colouring substances in the substrate. The gloss and hydrophobicity of the coating were influenced by the structure and composition of the substrate. The density of the treated wood also influenced the amount of liquid system needed to form a layer with uniform colour and gloss. The results of this study can be used to optimize the process of treating different types of wood surfaces with hard wax oil. REFERENCES Angelski, D., Atanasova, K., 2021. Water permeability of nano water-based coatings applied on wood. Proceedings of the first international „Salzburg Conference for Smart Materials “, September 16-17, Kuchl, Austria: 79-84. Arminger, B., Gindl-Altmutter, W., Hansmann C., 2022. Efficient recovery of superhydrophobic wax surfaces on solid wood. European Journal of Wood and Wood Products 80 (2) https://doi.org/10.1007/s00107-022-01793-8 Atanasova, K., Savov, V., 2023. Effect of process conditions on waterborne wood coating performance applied by dipping. Bulletin of the Transilvania University of Brasov, Series II: Forestry, Wood Industry, Agricultural Food Engineering 16(65) Special Issue: 1-22. https://doi.org/10.31926/but.fwiafe.2023.16.65.3.1 Atanasova, K., 2025. The surface roughness of wood after hard wax oil treatment. Bulletin of the Transilvania University of Brasov, Series II: Forestry, Wood Industry, Agricultural Food Engineering 18(67), 55-64 https://doi.org/10.31926/but.fwiafe.2025.18.67.1.4 Bekhta, P., Proszyk, S., Lis, B., Krystofiak, T., 2014. Gloss of thermally densified alder (Alnus glutinosa Gaertn.), beech (Fagus sylvatica L.), birch (Betula verrucosa Ehrh.), and pine (Pinus sylvestris L.) wood veneers. European Journal of Wood Products 72 (6), 799-808. https://doi.org/10.1007/s00107-014-0843-3 Bulian, F., Graystone J. A., 2009. Wood Coating: Theory and Practice, First Edition, Elsevier, Amsterdam. EN 828:2013. Adhesives - Wettability - Determination by measurement of contact angle and surface free energy of solid surface. European Committee for Standardization. EN 927-1:2013. Paint and varnishes - Coating materials and coating systems for exterior wood - Part 1: Classification and selection. European Committee for Standardization. EN 927-2:2022. Paint and varnishes - Coating materials and coating systems for exterior wood. Part 1: Performance specification. European Committee for Standardization.

Demirel, G. K., Temiz, A., Demirel, S., Jebrane, M., Terziev, N., Gezer, E. D., Ertas, M., 2016. Dimensional stability and mechanical properties of epoxidized vegetable oils as wood preservatives. Proceedings COST Action FP1407, 2nd Conference on Innovative Production Technologies and Increased Wood Products Recycling and Reuse, 29-30th September 2016, Brno, Czech Republic, pp. 49-50. Directive 2004/42/EC of the European Parliament and of the Council of 21 April 2004 on the

limitation of emissions of volatile organic compounds due to the use of organic solvents in certain paints and varnishes https://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2004:143:0087:0096:EN:PDF

EN 927-5:2023. Paints and varnishes - Coating materials and coating systems for exterior wood Part 5: Assessment of the liquid water permeability. Guner, F.S., Yagci, Y., Erciyes, A.T., 2006. Polymers from triglyceride oils. Progress in Polymer Science 31:633–670. https://doi.org/10.1016/j.progpolymsci.2006.07.001 OSMO, Product information. http://www.osmobg.com/userfiles/product_files_shared/PIDIY_HWO_GB_LR-0117_R.pdf POLYX®-OIL ORIGINAL Humar, M., and Lesar, B., 2013. Efficacy of linseed- and tung-oil-treated wood against wood-decay fungi and water uptake, International Biodeterioration & Biodegradation 85, 223-227. https://doi.org/10.1016/j.ibiod.2013.07.011 ISO 2813:2014. Paints and varnishes - Determination of gloss value at 20°, 60° and 85° ISO 2431:2019. Paints and varnishes - Determination of flow time by use of flow cups ISO 21920-2:2021. Geometrical product specifications (GPS) - Surface texture: Profile. Part2: Terms, definitions and surface texture parameters Janesch, J., Armingera, B., Gindl-Altmuttera, W., Hansman, C., 2020. Superhydrophobic coatings on wood made of plant oil and natural wax. Progress in Organic Coatings 148:105891 https://doi.org/10.1016/j.porgcoat.2020.105891 Kavalov, A., Angelski, D., 2014. Furniture Technology. Publishing House of the University of Forestry, Sofia, ISBN 978-954-332-115-5 (in Bulgarian). Kavalov, A., Angelski, D., 2015. Alternative methods for friction smoothing of wood surfaces. Publishing House of the University of Forestry, Sofia, ISBN 978-954-332-137-7 (in Bulgarian). Koski, A., 2008. Applicability of Crude Tall Oil for Wood Protection. Academic dissertation, University of Oulu, Oulu University Press, Oulu, Finland. Liu, C., Wang, S., Shi, J., Wang, C., 2011. Fabrication of superhydrophobic wood surfaces via a solution-immersion process, Applied Surface Scence 258(2), 761-765. https://doi.org/10.1016/j.apsusc.2011.08.077 Shi S. Q., Gardner, D. J., 2001. Dynamic adhesive wettability of wood. Wood and Fiber Science 33(1): 58-68. Spiridon, I., 2020. Extraction of lignin and therapeutic applications of lignin-derived compounds. A review. Environmental Chemistry Letters 18:771– 785. https://doi.org/10.1007/s10311-020-00981-3 Teacă, C.-A., Roşu, D., Mustaţă, F., Rusu, T., Roşu, L., Roşca, I. and Varganici, C.-D., 2019. Natural bio-based products for wood coating and protection against degradation: A Review. BioResources 14(2), pp.4873-4901. https://doi.org/10.15376/biores.14.2.Teaca Zhang, D., Song K., 2024. Effects of Photoinitiators on Curing Performance of Wood Wax Oil Coating on Wood, Coatings 14(1), 2. https://doi.org/10.3390/coatings14010002 ACKNOWLEDGMENT This paper was supported by the National Program "Young Scientists and Postdoctoral Students 2", 2025 - Bulgaria, University of Forestry, Faculty of Forest Industry.

AUTHORS’ ADDRESSES Chief Assist. Prof. Krasimira Atanasova, PhD. Prof. Dimitar Angelski, PhD. Assist. Prof, Dobriyan Dobriyanov, PhD. student University of Forestry, Sofia Faculty of Forest Industry 10 Kliment Ohridski Blvd. 1797 Sofia, Bulgaria k_atanasova@ltu.bg d.angelski@ltu.bg d.dobriyanov@ltu.bg

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 89−100, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.09

COLORISTIC SOLUTION FOR COMPLEX MOSAIC IMAGES LASER-ENGRAVED ON WOOD Mikhail Chernykh – Alina Korepanova – Ekaterina Maksimova – Maxim Gilfanov – Vladimir Stollmann ABSTRACT The results of developing a coloristic series with a greater number of visually distinct color shades for laser engraving complex mosaic images on beech and aspen wood are presented in the paper. Two independent methods used to study the engraved wood shade yielded consistent results: instrumental, based on determining color coordinates in the Lab system, and visual, based on tone expert evaluation. The reduced discretization step of the tone gradient ΔEs to two Е units combined with simultaneous tone gradient spread, allows increasing the number of shades and extending the coloristic series of engraved beech and aspen wood. The successive power elevation caused by the computer template raster (resolution) density growth results in the formation of three distinctive regions on the tone gradient: the light-toned region, the darkened region, and the lightened region. The integrated coloristic index Е decreases in the first two regions but increases in the third one due to the light reflection by carbonized wood cells. Keywords: wood; laser engraving; tone gradient; absorbed power; coloristic series.

INTRODUCTION Laser engraving is successfully used to produce and decorate items made of wood and other wood-based materials. The practical application of engraved wood color has been described in several works. Petutschigg et al. (2013) got new aesthetic opportunities in ski design. Jurek and Vagnerova, 2021; Gochev and Vitchev, 2022; Zukova et al., 2022 engraved photo replicas on beech wood and birch plywood; Lungu et al., 2022 decorated maple furniture with traditional Romanian ornaments to preserve cultural identity. Chernykh et al. (2018) produced a series of decorative panel pictures from the veneers of various wood species. Evdokimova (2023) described the possibilities of improving the quality of pseudo-3D images engraved on birch wood by more fully exploiting its coloristic properties. Numerous papers have been dedicated to studying the interconnection between the color of laser engraved wood and wooden materials with changed chemical properties, roughness, engraving modes: Hill et al., 2006; Barchikovski et al., 2006; Lin et al., 2008; Kubovsky and Babiak, 2009; Chernykh et al., 2011, 2012, 2015; Kubovsky et al., 2016; Yakimovich et al., 2016, Vidholdova et al., 2017, Gurau et al., 2017; Geffert et al., 2017; Li et al., 2018; Kudela et al., 2019, 2022, 2023. 89

The accumulated knowledge and practical experience enable the shift from copying existing photographs and images to designing them for further laser engraving. Such approach is based on taking into account coloristic capabilities of the engraved wood and achieving the color match between the carved image and developed drawing in the image (drawing) design (Chernykh et al., 2024). Such matching allows the customer to select the engraved image color palette at the time of placing an order and even to participate in the creation of the drawing's coloristic solution, thus increasing the chances of selling the item. Despite selling custom-made items, another group can be singled out: items produced without the customer's participation, following the designer's project, and displayed for sale. To succeed in business, the designer must predict the buyers' perception. The laser engraved wood has a brown color with various shades, and the image threedimensionality is achieved by the shade difference – different color saturation. The tone changes smoothly in half-tone drawings and photographs, but in mosaic drawings, widely used in fine and decorative art (Figure 1), it changes discretely, stepwise.

Stylized images

Classical mosaic

Country / nation cultural code

Mosaic images

Cultural heritage conservation

Marque try

Anime / anime style

Fig. 1 Areas of mosaic drawing application.

To create a mosaic drawing for further laser engraving, it is necessary to discretize the tone gradient of the laser engraved wood. The discretization step of the tone gradient ∆E s is found as ∆𝐸𝑠 = |𝐸1 − 𝐸2 |

(1)

Where: E1, E2 – values of integrated coloristic index Е of the tone gradient stages compared, √𝐿2 + 𝑎2 + 𝑏2

(2)

Where: L, a, b – color coordinates in Lab system. In Chernykh et al. (2024), the discretization step for the tone gradient of the engraved aspen wood sample was set to 6. With such a value of ∆Es, only six stages can be singled out in the tone gradient of aspen (as well as other wood species discussed in the paper – birch, pine, larch, beech, and spruce). 90

Six tone shades are not enough to create a complex mosaic drawing; therefore, it is of practical interest to increase their number by reducing the discretization step to the minimum possible. With more mosaic image shades used, it becomes possible to increase the number of its small elements, making the image more comprehensive and volumetric and thus improving its quality. The decrease in the discretization step is limited by the tone threshold distinction by the human eye ∆, Ep, at which the visual difference of the color series stages, similar in tone, disappears. The contrast sensitivity of the human eye has been studied in several works. For this, Antipin (1970) and Mikov and Morozov (2007) compared the brightness of the image background and details. ∆𝐵

(3)

𝜀𝑝 = 𝐵 𝑝

Where: εp – contrast sensitivity; В – mean value of brightness of the compared spots; ∆Bp– threshold distinction between the brightness of two compared neighboring color spots by a human eye (for example, the image background and details) ∆𝐵𝑝 = 𝐵1 − 𝐵2

(4)

Where: В1 and В2 – brightness of the compared spots. Not only brightness but also color tone influences the harmonic perception of the laserengraved image (Jurek and Vagnerova, 2021); therefore, the integrated coloristic index E was used in this study instead of brightness. The work is aimed at forming a discrete series of engraved wood tone gradients with an increased number of shades to develop complex mosaic drawings.

MATERIALS AND METHODS The discretization step of the tone gradient ∆Es was found by an expert evaluation method in Chernykh et al. (2013). The laser-engraved samples of aspen and beech wood, measuring 20×20×300 mm, reported in Chernykh et al. (2024), were used in the study. The samples had a tangential section and a longitudinal fiber direction. Before engraving, the surface was planed on a thickness planer. Samples’ moisture: 12%. The testing strips were engraved on the samples using a grey computer template with the resolution N uniformly increasing from 0 to 255 or from 0 to 100% of black. Equipment: Laser CO2 marker with CNC GCC Synrad (USA), 30 W. The engraving power Pi was 4.5 W, the speed V was 1000 mm/sec, the laser machine resolution R was 600 dpi, the focal distance L was 300 mm, and the focal plane position coincided with the surface engraved. The sample was placed inside the hollow casing (Figure 2) with a rectangular opening (window) whose dimensions matched those of the tone gradient (20×150 mm) engraved on 91

the sample. The scale with resolution N values was made on one of the longitudinal edges of the casing window according to the values of monochromatic computer template used for gradient engraving on the samples, and on the opposite edge – the scale with values of integrated coloristic index E according to the corresponding gradient values on the sample measured with the help of spectrophotometer GretagMacbeth “Eye-One Pro” (Switzerland).

Fig.2 Casing with a fixed sample.

The clearance for placing and moving samples was envisaged between the sample engraved surface and the casing (Figure 3) to observe different regions of the engraved gradient.

Fig. 3 Sample from white dense paper with windows.

The template window height was 15 mm, and the widths of the first and second templates were 12 mm, and the third was 10 mm. The distances between the middles of the windows were: 18 mm – in the first sample, 13 mm – in the second, and 6.5 mm – in the third, which corresponded to the discretization step of the tone gradient ∆Es equal to 7, 5, and 4 Е units. The experts, moving the templates, compared tone differences across windows and recorded the values of three indices – N and E at the middle of the windows, as well as the presence or absence of a visually perceived tone difference. When available, they put 1 in the “Perception Wi” line of the table, and when unavailable zero. Tab. 1 Values of measured indices. Index Resolution N, %

Template 1* 5

Integrated coloristic 87 86 77 67 index Е, units Experts’ group 0.9 1.0 1.0 0.9 perceptionW *Similar tables were used for templates 2 and 3.

0.9

0.3

0.4

0.9

0.8

The experts’ group collective perception W was found for each selected discretization step based on each expert’s individual perception W i 92

𝑚

(5)

𝑊=𝑀

Where: m – number of positive replies on the availability of brightness difference between the regions compared; М – number of respondents (25 designers were interviewed). The collective perception W could range from 0 to 1. Its equally probable value was 0.5 when the experts’ opinions were similarly divided. In the paper, we proceeded from the assumption that the collective perception of experts is available and can be compared with the perception of a typical buyer when observing an engraved mosaic image. Suppose most experts can differentiate the tones of the neighboring steps of the coloristic series with a specific ∆Es value. In that case, a typical buyer will also determine the neighboring spots of the image, similar in tone, and understand the designer’s drawing based on the coloristic series with the same ∆Es value. The image, designed based on the research results, was engraved into beech wood using a CO2 laser engraver, GCC Laser Pro Mercury III (USA), at the maximum power, Pmax = 26 W. The engraving mode: pulse power Pi = 6.5 W, engraving speed V = 1000 mm/sec, laser resolution R = 600 dpi. The beam was focused on the workpiece surface (a focus shift against the engraved surface, both upwards and downwards, increased the line width and blur, thereby deteriorating image quality).

RESULTS AND DISCUSSION The study results are given in the graphs (Figure 4).

a) b)

Fig. 4 Engraved tone gradient on the aspen sample (а), dimensions in mm; the graphs of dependence of the experts’ groupcollective perception W on the template resolution N with different discretization steps of the tone gradient (b): 1 - ∆Es = 7 (template 1), 2 - ∆Es = 5 (template 2), 3 - ∆Es = 4 (template 3).

Three distinctive regions of the engraved gradient are visually apparent on the sample: I – light-shaded region, II – intensively darkened region, and III – lightened region. While the template resolution N increased, the number of laser pulses ƒ per unit time, absorbed power PW, and temperature Т of the wood heated increased. The surface became darker. In the light shade region, the gradient tone slightly differed from the wood's natural color; the difference was not marked by all experts. Nevertheless, most of them registered surface darkening with increasing resolution N, and consequently, the raster density and absorbed power PW. Perception W in this region exceeded the equally probable value of 93

0.5, changing from 0.6 to 0.9 depending on the discretization step ∆Es. The perception reached its maximum value of 1 near the boundary between regions I and II. The experts' perception in the area I agreed with the results of the previous investigation reported in Chernykh et al. (2024): the integrated coloristic index Е slightly decreased in region I (Figure 5).

Fig. 5 Dependencies of the integrated coloristic index Е of the tone gradient of the sample engraved on aspen upon resolution N according to Chernykh, M. et al. 2024 (1) and printed out on paper (2).

When we continued comparing Figures 4 and 5, we discovered that the integrated coloristic index E was changing most in the beginning of the region II till the resolution N value approximately equal to25-23%, and simultaneously the maximum value of perception W was preserved, registering the intensive tone change. Further, the decrease in perception W was observed in region II, together with N growth, and, at the same time, the reduction in E values slowed. W and E values were minimal at the boundary of regions II and III, and the darkest tone was reached when the tone threshold of the engraved wood was reached. With further resolution N increase and, consequently, the number of laser pulses ƒ per time unit, as well as the average laser radiation power Рс, absorbed powerРw and heating temperature Т, the sample surface did not darken but, on the contrary, lightened, the integrated coloristic index E started growing, and the perception was the least. Kudela et al. (2023) pointed out that wood color could serve as an indicator of significant changes in its properties resulting from processing. Judging from the graphs of color change demonstrated in Figures 4 and 5, it can be assumed that carbonization of separate wood cells and lightning connected with it started at an early stage of laser processing (in our case, it began when resolution N approximately equaled 25-30% when, simultaneously, E decrease was slowing down, and perception W was decreasing). The assumption was supported by investigation results on the engraved spruce wood microstructure, which demonstrated the simultaneous presence of carbonized and non-carbonized cells (Kudela et al., 2024). Further, with N growth, the number of carbonized cells and the light-reflection area gradually increased, reaching a level that led to further tone lightening of the overall engraved surface. The slowing down of lightening L and integrated coloristic index E decrease with the increased laser beam power (and, consequently, radiation dose, as well as absorbed power 94

Рw) were observed on beech wood (Vidholdova et al., 2017, Kudela et al., 2019), maple wood (Lungu et al., 2022), oak and spruce wood (Kudela et al., 2023, 2024). The lightning effect limited the range of E values and the number of coloristic series shades. On the whole, based on the graphs shown in Figures 4 and 5, it is possible to observe a match between the change characteristics of the integrated coloristic index E and perception W as a function of template resolution N and absorbed power Pw. The proposed decrease in the tone gradient discretization step to ∆E equal to 4 allowed extending the gradient coloristic series to seven stages, which was insufficient to design a complex drawing. The study continued with models that allowed transforming the tone change intensity along the gradient length, due to its extension, and thereby obtaining a greater number of stages in its coloristic series. For this, the sample tone gradient was transferred to paper in the computer program (graph 2 in Figure 5). Some discrepancy in the E values between the sample and the model can be explained by the influence of wood texture. The models' tone gradients were discretized with steps ∆Es = 4 and ∆Es = 2 (Figure 6). The decrease of the discretization step ∆Esto 2 allowed doubling the number of stages of the coloristic series.

а)

b) Fig. 6 Coloristic series of aspen wood formed on models with discretization step ∆E sequal to 4 (a) and 2 (b).

The investigation of perception W of the coloristic series options shown in Figure 6, in which the neighboring stages of the tone shades, directly adjoining each other, demonstrated the influence on the perception of optic illusion called “Mach band” (Ratliff, 1965). The illusion is related to the features of the human visual system and neutralizes the tonal differences between the neighboring stages. As a result, the expert evaluation becomes overrated. Separation of degrees of coloristic series allowed eliminating the influence of the abovementioned illusion. The graph of perception W of the series with separated stages is given in Figure 7.

(а)

(b)

(c) Fig. 7 Texture of the engraved sample in the region II (а), perception of the coloristic series of the aspen wood tone gradient with separated stages with discretization step ∆E s equal to 2 in the region II, the dots in the graph correspond to the boundaries between the series stages (b); the coloristic series with separated stages (c).

On the whole, the graph in Figure 7 b agrees with the graphs of region II in Figure 4. Thus, the tone changed more in the beginning of region II, and the perception equaled 1; the tone change diminished in the middle portion, the W value decreased, and the perception was minimal in the end. The sharp decrease in perception at the boundary between stages 8 and 9 was influenced by the texture shown in Figure 7a. Perception W was close to the equally probable value of 0.5 in the area of the tone gradient, in dark shades at the boundaries of stages 6 and 7, 7 and 8, 10 and 11, and 11 and 12. It was necessary to enlarge the discretization step in this area to provide the better perceptibility of the stages, having combined, for example, pairwise, the neighboring stages starting from the seventh for aspen and from the tenth for beech, as demonstrated in Figure 8.

а)

b) Fig. 8 Specified coloristic series for aspen wood (а); and beech wood (b).

The discrete series with separated stages (Figure 8b, the right one) was used for designing the mosaic drawing. A bald eagle, considered a holy bird, a symbol of bravery and spiritual bond with the sky by native people of North America, for example, the Navajo, was used as an artistic image for engraving. The drawing contained a lot of mosaic elements of various sizes and shades (Figure 9).

а)

(b) Fig. 9 Image designed based on the coloristic series given in Figure 8b (a) and laser engraved image on beech wood (b), 130x215 mm.

The computer template for laser engraving was designed based on the drwaing.

CONCLUSION A method for extending the coloristic series of the tone gradient of laser-engraved wood by decreasing the gradient discretization step and simultaneously spreading tones to provide the opportunity for engraving complex mosaic drawings is proposed. The method allows shifting from copying existing drawings and photographs to their design for further laser engraving, thereby achieving a match of the engraved image color with the designed drawing color. The investigation of the dependence of the tone change on the absorbed power Pw, carried out by two independent methods – an instrumental method determining color coordinates L, a, b, and an integrated coloristic index E, and a visual method of expert evaluations, demonstrated agreement between the results. The process of expert assessments allows for the identification of consumers’ preferences. While the absorbed power Pw goes up, three distinctive regions are successively formed on the tone gradient of the engraved wood: the region of light tones, the darkened region, and the lightened region. The highest darkening rate is registered at the beginning of the second region; it decreases in descending order in the middle and at the end due to light reflection from the carbonized wood cells. With the absorbed power Pw increasing, the number of carbonized cells and the light-reflection area increase, reaching a level that further lightens the overall engraved surface. The lightened region emerges on the tone gradient. The lightening effect limits the targeted color change opportunities for laser-etched wood within a specific range of E values, particular to each species. REFERENCES Antipin, М.V., 1970. Integral evaluation of television picture quality. L.: Nauka, 382 p.

Barcikovski, S., Koch, G., Odermantt, J., 2006. Charakterisation and Modification of the heat affected zone during lazer material processing of wood composites. HolizalsRoh und Werkstoff, 64: 94-103. Chernykh М., Yapparova E., Yapparova L., 2011. Classification of artistic items of wood. Peculiarities of their decoration with engraved ornament. Design. Materials. Technology, 4(19): 30-35. Chernykh, M., Yapparova, E., 2012. Methods of designing raster pattern model in the process of wood laser engraving. Design. Materials. Technology, 2(22). 78-81. Chernykh, M., Kargashina, E., Sstollmann, V., 2013. Assessing the impact of aesthetic properties characteristics on wood decorativeness. Acta FacultatisXylologiaeZvolen, 55(1): 13-26. Chernykh, M., Dryukova, A., 2015. Laser engraving of raster images on charred materials. Design. Materials Technology, 54(39): 74-77. Chernykh, M., Kargashina, E., Stollmann, V., 2018. The use of wood veneer for laser engraving production. Acta Fac. XylogiaeZvolen, 60 (1): 121-127, https://doi.org/10.17423/afx.2018.60.1.13 Chernykh, M., Zykova, M., Stollmann, V., Gilfanov, M., 2022. Influence effect of wood laser engraving mode on aesthetic perception of images. Acta Fac. XylologiaeZvolen, 64(2): 87-96, https://doi.org/10.17423/afx.2022.64.2.09 Evdokimova, A., Chernykh. M., Gilfanov, M., Stollmann, V., 2023. Automation of tenplate correction algorithm for quality improvement of pseudo-3d engraved images. Acta Fac. XylologiaeZvolen, 65(2); 63-76, https://doi.org/10.17423/afx.2023.65.2.06 Geffert, A., Vybohova, E., Geffertova, J., 2017. Characterization of the changes of colour and some wood components on the surface of steamed beech wood. Acta FacultatisXylogiaeZvolen, 59(1): 49-57, ISSN 1366-3824, https://doi.org/10.17423/afx.2017.59.1.05 Gochev, Z., Vitchev, P., 2022. Colour modifications in plywood by different modes of CO2 laser engraving. Acta Fac. XylologiaeZvolen, 64(2): 77-86, https://doi.org/10.17423/afx.2022.64.2.08 Gurau, L., Petru, A., Varodi, A., Timar, M.C., 2017. The Influence of CO2 Laser Beam Power Output and Scanning Speed on Surface Roughness and Colour Changes of Beech (Fagus sylvatica), BioResources, 12: 7395-7412. Hill, C.A.S., 2006. Wood Modification Chemical, Thermal and Other Processes. John Boe Wiley & Sons, Lid, Chichester, UK. https://doi.org/10.1002/0470021748 Jurek, M., Vagnerova, R., 2021. Laser beam calibration for wood surface colour treatment. European Journal of Wood and Wood Products, 79(5): 1097-1107, https://doi.org/10.1007/s00107-02101704-3 Kubovsky, I., Babiak, M., 2009. Color changes iadided by CO2 laser irradiation of wood surface. Wood Research 54(3): 61-66. Kubovsky, I., Kacik, F., Reinprecht, L., 2016. The impact of UV radiation on the change of color and composition of the surface of lime wood treated with a CO 2 laser. Journal of Photochemistry and Photobiology A: Chemistry 322, 60-66, https://doi.org/10.1016/j,jphotochem. 2016.02.022 Kudela, J., Reinprecht, L., Vidholdova, Z., Andrejko, M., 2019. Surface properties of beech wood modified by CO2 laser. Acta Fac. XylologiaeZvolen 61(1): 5-18, https://doi.org/10.17423/afx.2019.61.1.01 Kudela, J., Kubovsky, I., Andrejko, M., 2022. Influence irradiation Parameters and Properties of Oak Wood Surface Engraved with a CO2 laser, Materials, Vol. 15, Iss. 23, p. 21, ISSN 1996-1944, https://doi.org/10. 3390/ma15238384 Kudela, J., Andrejko, M., Kubovsky, I., 2023. The Effect of CO2 laser Engraving on the Surface Structure and Spruce Wood, Coatings, Vol.13, lss. 12, p. 17, ISSN 2079-6412, https://doi.org/10.3390/coating 13122006 Li, R., Xu, W., Wang, X.A., Wang, C., 2018. Modeling and predicting of the color changes of wood surface during Co2 laser modification. J. Clean, 183: 818-823.

Lin, C.J., Wang, Y.C, Lin,L.D., Chiou, C.R., Wang, Y.N., Tsai, M.J., 2008. Effects of feed speed ratio and laser power on engraved depth and color difference of Moso bamboo lamina. Jornal of Materials Processing Technology 198(1-3). https://doi.org/10.1016/jmatprotec. 2007.07.020 Lungu A., Timar M., Beldan E., Georgescu S., 2022. Adding Value to Maple (Acer pseudopltanus) Wood Furniture Surfaces by Different Methods of Transposing Motifs from Textile Heritage. Coatings.2022, 12.1393 Lungu, A., Timar, M., Beldan, E., Georgescu, S., 2022. Adding Value to Maple (Acer pseudopltanus) Wood Furniture Surfaces by Different Methods of Transposing Motifs from Textile Heritage. Coatings, 12(10), 1393, https://doi.org/10.3390/coatings12101393 Petutschnigg A., Stockler, M., Steinwenden, F., Schnepps, J., Gutler, H., Blinzer, J., Holzer, H., Schnabel, Th., 2013. Laser Treatment of Wood Surfaces for Ski Cores: An Experimental Study. Advances in Materials Science and Engineering, Volume 2013 (11), Article ID 123085, pp 1-7, ISSN 1687-8434 (Print), ISSN 1687-8442 (Online), https://doi.org/10.1155/3013/123085 Ratliff, Floyd, Mach Bands, 1965. Wantitative Studies on Neutral Networks in the Retina. Holden, Day series in psychology. ISSN 2836-6875. Vidholdova, Z., Reinprechr, L., Igaz, R., 2017. The impact of laser surface modification of beech wood on irs color occurrence of molds. BioResources, 12(2): 4177-4186. Yakimovich, B., Chernykh, M., Stepanova, A., Siklienka, M., 2016. Influence are selected laser parameters on quality of images engraved on the wood. Acta Fac. XylogiaeZvolen, 58(2): 4550, https://doi.org/10.17432/ afx.2016. 58.2.05 ACKNOWLEDGMENT This publication was created with the financial support of the project: Comprehensive research of mitigation and adaptation measures to diminish the negative impacts of climate changes on forest ecosystems in Slovakia (FORRES), ITMS: 313011T678 (100%) supported by the Operational Programme Integrated Infrastructure (OPII) funded by the ERDF.

AUTHORS’ ADDRESSES Mikhail Chernykh, Prof. DSc. Kalashnikov Izhevsk State Technical University, Department of Industrial and Artistic Processing of Materials, Izhevsk, 426069, Studencheskaya, 7, rid@istu.ru Alina Korepanova, student Kalashnikov Izhevsk State Technical University, Department of Industrial and Artistic Processing of Materials, Izhevsk, 426069, Studencheskaya, 7, korepanovvalina@gmail.com Ekaterina Maksimova, student Kalashnikov Izhevsk State Technical University, Department of Industrial and Artistic Processing of Materials, Izhevsk, 426069, Studencheskaya, 7, flin.neison@gmail.com Vladimir Stollmann, Assoc. Prof. Technical University in Zvolen, Faculty of Forestry T.G. Masaryka 24, 960 53 Zvolen, Slovak Republic, stollmannv@tuzvo.sk Maxim Gilfanov, Director of LLC “Synergy”, Izhevsk, 426063, Karlutskaya embankment, gravirovkarf@ya.ru 100

ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 101−115, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.10

INNOVATIVE COMPOSITIONS OF STRUCTURAL ELEMENTS AND THEIR ESTIMATED FIRE RESISTANCE Ľudmila Tereňová – Daria Mokrenko – Mária Kozlovská ABSTRACT The paper is focused on the investigation of innovative compositions of structural elements suitable mainly for use in timber constructions, with respect to determining their expected fire resistance. The examined compositions of structural elements meet several requirements that contribute to both the energy efficiency and fire safety of buildings. The tested structures consisted of magnesium oxide boards forming the sheathing of the samples, combined with various types of thermal insulation cores (PUR foam, paper honeycomb, and straw mixed with MgO mortar). The expected fire resistance was determined by conducting mediumscale fire tests simulating the progression of a fully developed compartment fire. The samples were exposed to radiant heat from a radiation panel with an output of 20 kW·m⁻². The best results were achieved by the sample containing the straw and MgO mortar mixture, which reached an estimated fire resistance of 90 to 120 minutes, confirming the suitability of this material combination in the composition of the structural element. The sample with the honeycomb core achieved an assumed fire resistance of 30 to 45 minutes, while the sample with PUR thermal insulation had the lowest, at 15 minutes. Keywords: structural element; magnesium oxide board; thermal insulation core; expected fire resistance; medium-scale test.

INTRODUCTION Modern construction is characterised by increasing demands for sustainability, rapid building processes, and energy efficiency. Timber structures have excellent potential to meet these requirements; however, these must also be reconciled with the need for fire safety. It can be achieved by using appropriate materials and suitable layer compositions in the structural elements of wooden buildings. An example of an innovative material is the magnesium oxide (MgO) board, also known as a magnesia board, which is composed primarily of magnesium oxide (MgO). In the structural elements of timber buildings, MgO boards can replace large-format materials such as particleboard, fibreboard, OSB, CETRIS boards, fire-resistant plasterboard, Fermacell boards, and other fireproof claddings. They can be applied to both the interior and exterior. MgO boards are characterised by good thermal and acoustic insulation properties, non-combustibility, and resistance to surface flame spread. At present, the worldwide production of magnesium oxide boards comes almost exclusively from China (Iqra et al., 2025). However, Slovakia is one of the leading countries in magnesite mining (Dubecký et al., 2017). Magnesite (MgCO₃) is the most essential 101

mineral of magnesium and occurs in crystalline and cryptocrystalline (massive) forms (Fig. 1). The massive form may also be of sedimentary origin. It contains admixtures of CaO, Fe₂O₃, MnO, Al₂O₃, SiO₂, and others that influence the raw material’s quality. A substance is generally considered magnesite if it contains at least 40% MgO and no more than 4% CaO. Magnesite is primarily used to produce caustic sinter, which serves as a base for refractory materials, insulations, and special cement formulations resistant to acids and oils. Deadburned magnesite (periclase) is produced exclusively from crystalline magnesite and is used for refractory linings in metallurgical furnaces and converters, cement kilns, and sulphuric acid production equipment (Baláž, 2008). MgO has been a component of various natural building materials used since ancient times and has proven its durability over centuries (Voroncov et al., 2008).

Fig. 1 Crystalline magnesite, Lubeník locality (Baláž, 2008).

Today, relatively little attention is given to environmentally friendly building materials. Achieving environmentally sound construction is impossible without ecological materials and products featuring a low carbon footprint, low emissions of hazardous substances, and high biological stability. A unique property of magnesium oxide boards is their ability to absorb CO₂ from the air throughout their entire life cycle, thereby actively purifying and improving indoor air quality. MgO boards can be used in almost all building applications, i. e. ceilings, partitions, fireplaces, all types of internal and external wall claddings, ventilated façades, decorative ceilings, and anywhere that requires protection from fire, rot, or mould (Jandačka and Holubčík, 2020) The MgO board generally consists of five layers (Fig. 2). Surface layer No. 1 is smooth and suitable for painting. Layer No. 5 usually has a rough texture, making it suitable for applying plaster or adhesive. Layers No. 2 and No. 4 are made of fibreglass mesh, which serves as reinforcement. Layer No. 3 forms the core of the MgO board (Dubecký et al., 2017).

Fig. 2 The structure of the MgO board (Dubecký et al, 2017) 1 – surface layer, 2 – fiberglass mesh, 3 – core, 4 – fiberglass mesh, 5 – surface layer.

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One of the key factors that makes MgO boards an excellent choice for fire safety is their high melting point. Magnesium oxide has an exceptionally high melting temperature, meaning the board can withstand elevated temperatures for a relatively long time before beginning to decompose. This property provides a significant advantage in the event of a fire, as it allows the board to resist flames and prevent their rapid spread. The surface of the MgO board contains a protective layer that acts as a barrier, reducing heat transfer to the opposite side. Therefore, if an interior MgO board is used as a fire-rated wall, it can help to contain the fire on one side and protect adjacent areas for a specific period of time (Chen, 2025). Another important aspect is the low smoke emission of MgO boards during fire exposure. Smoke is often one of the most significant hazards in a fire because it can cause breathing difficulties and reduce visibility, hindering evacuation. Interior MgO boards produce only a minimal amount of smoke when exposed to fire, which is a significant contribution to the overall fire safety of occupants in a building (Chen, 2025).) In addition to their fire-resistant properties, interior MgO boards also possess sound thermal insulation. It means they help to prevent heat from a fire from penetrating through the board into other parts of the building. It is important not only for preventing the spread of fire but also for maintaining the structural integrity of the building (Chen, 2025). The coefficient of thermal conductivity of MgO boards is 0.216 W·m⁻¹·K⁻¹. The MgO boards, therefore, have a clear justification and potential for broader use, both in terms of cost and due to their superior technical parameters compared with commonly used materials in timber constructions, such as plasterboard, CETRIS boards, OSB boards, or plywood (Mokrenko and Kozlovská, 2020). At present, we are surrounded by a wide range of materials and material combinations used in manufactured products. In most industrial production processes, raw materials are transformed into semi-finished goods, many of which pose potential hazards. Therefore, it is essential to understand the material composition and nature of the raw materials used in industrial sectors, as only through suitable modifications can the undesirable effects of materials be minimised (Morais et al., 2024). The aim of the paper is to experimentally determine the assumed fire resistance of selected innovative compositions of structural elements using MgO boards, in combination with insulating materials: PUR, paper honeycomb, and MgO mortar mixed with straw, and based on the results of the behavior of individual compositions under fire conditions, to recommend possibilities for their use in current timber constructions.

MATERIALS AND METHODS The test samples used for the experiment were provided by the Department of Technology and Innovation in Construction at the Faculty of Civil Engineering, Technical University of Košice, where experiments on the production of MgO boards were carried out, including tests of their tensile and flexural strength. The department also designed assemblies of structural elements comprising MgO boards and various core materials, which were subsequently submitted for fire resistance testing. Three types of structural element compositions were tested, with two samples of each type (sample A and sample B). Sample No. 1 consisted of MgO boards combined with polyurethane thermal insulation (PUR), sample No. 2 consisted of MgO boards with a paper honeycomb insulation core, and sample No. 3 used MgO boards combined with a strawbased filling. Thus, both natural and synthetic materials were used as infill components. 103

For each composition, two test specimens were evaluated. The temperature deviation between replicate samples did not exceed ±5 °C at comparable exposure times, confirming the reliability of the results. Sample No. 1: A panel with PUR insulation (MgO–PUR) was composed of MgO boards with a thickness of 12 mm and PUR foam insulation 90 mm thick. Sample No. 2: A panel with a honeycomb insulation core (MgO–honeycomb). For the production of the MgO–honeycomb panel, MgO boards of 12 mm thickness were combined with a paper honeycomb core 90 mm thick. Honeycomb panels were produced from high-quality kraft paper by lamination. They are available in various thicknesses and dimensions. Their compressive strength depends on the surface paper and the honeycomb cell size. The honeycomb is a lightweight, hexagonal filler material that provides excellent thermal insulation and mechanical strength. Paper honeycombs are suitable as core materials for sandwich constructions (www.vostina.com). Sample No. 3: A straw-based panel (MgO–straw) was made from 12 mm-thick MgO boards and a thermal insulation core consisting of straw mixed with MgO mortar. The straw– MgO mortar mixture was prepared by a weight ratio of 3 parts straw : 2 parts MgO mortar. The binder was mixed with a 10 % magnesium chloride solution to achieve a workable consistency. After blending, samples were cured under laboratory conditions (20 ± 2 °C, RH = 60 %) for 7 days before testing. Wheat straw with a bulk density of 469 (kg·m⁻³) was used. Straw, as a building material, deserves particular attention in sustainable construction due to its natural, energy-efficient, and environmentally friendly properties (Džidić and Miličić, 2017). The MgO mortar consisted of caustic magnesite, magnesium chloride, potassium dihydrogen phosphate, and calcium chloride. Caustic magnesite (calcined magnesite) is produced by firing magnesite at temperatures up to approximately 1000 °C and is ideal for manufacturing refractory boards, lightweight partition boards, magnesium sulphate, paper production, and desulphurisation processes (sk.magnesium-fertilizer.com). Figures 3 to 5 illustrate the test samples, and Table 1 lists the principal technical parameters of the materials used: a)

Fig. 3 Sample No. 1: MgO–PUR a) unexposed side, b) exposed side, c) panel composition.

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Fig. 4 Sample No. 2: MgO–Honeycomb a) unexposed side, b) exposed side, c) panel composition. a)

Fig. 5 Sample No. 3: MgO–Straw a) unexposed side, b) exposed side, c) panel composition. Tab. 1 Technical parameters of materials used in the sample composition. Material

Density (kg·m⁻³)

MgO board 950 – 1000 ± 25* PUR 30 Honeycomb – MgO mortar 1800 – 2100 * Values represent average ± SD, ** source: (Jensen, 2000), (Maršál et al., 2016).

Surface mass (g/m²) – – 120 – 150 –

Thermal conductivity λ (W·m⁻¹·K⁻¹) 0.216 0.036 0.0313 0.6

Reaction-to-fire class (STN EN 13501-1: 2019) A1** E – F** D** A1**

A medium-scale test was carried out in a testing chamber with internal dimensions of 1670 mm × 550 mm × 2010 mm (width × depth × height), as shown in Fig. 6. The source of radiant heat was a radiation panel with a size of 500 × 300 mm. Automatic gas regulation ensured a constant burner power of 20 kW·m⁻². The surface temperature of the radiation panel reached approximately 1,000 °C, corresponding to the maximum temperatures of a fully developed compartment fire. The 105

samples were placed inside the testing chamber 20 minutes after the equipment was switched on, once the radiation panel had reached the required operating parameters. The distance between the samples and the radiant panel surface was 150 mm. The duration of each test depended on the behaviour of the individual samples when exposed to radiant heat, with exposure times of 15, 30, 60, and 90 minutes. To measure the temperature profile, Ni–Cr thermocouples were used, placed in the centre of the sample in sequence T1–T4. The first thermocouple (T1) was located on the heated surface of the sample; T2 and T3 were positioned at the interfaces of the individual layers; and T4 was situated on the unheated surface. The temperatures were recorded every second using an Almemo 710 data logger (Fig. 7) and stored in a computer. Smoke extraction was provided by an exhaust unit located at the top of the testing chamber (Ø 250 mm).

Fig. 6 Testing chamber.

Fig. 7 Datalogger Almemo 710.

Prior to each test, all Ni–Cr thermocouples were calibrated using a furnace reference point to ensure accuracy within ±2 °C across the measurement range.

RESULTS AND DISCUSSION The measured results were evaluated based on recorded temperatures and the behaviour of the samples during testing. The expected fire resistance of the proposed structural element compositions was determined based on temperatures measured on the unexposed surfaces. In accordance with the testing standard STN EN 1363-1 (2021), this 106

temperature must not rise by more than 140 °C above the initial average surface temperature at the start of the test, and not more than 180 °C at any single point on the unexposed surface. Sample No. 1 (MgO–PUR) was assessed as having a fire resistance of approximately 15 minutes. The results from sample 1b were considered representative. The test of sample 1a was terminated after 13 minutes due to an automatic shutdown of the radiation panel caused by improper placement within the test chamber. Fig. 8 shows the temperature development over the 13-minute duration of this test.

Fig. 8 Temperature profile of Sample 1a (MgO–PUR).

For sample 1b, the radiation panel was positioned outside the chamber, at the boundary of the testing enclosure, allowing better air access to the burner (as illustrated in Figure 6). The distance between the sample and the radiant surface was adjusted from 100 mm to 150 mm. The temperature curve for sample 1b is shown in Fig. 9.

Fig. 9 Temperature profile of Sample 1b (Mgo–PUR).

During the test of sample 1a, thermocouple T2 malfunctioned (Fig. 8), and the test lasted 13 minutes. The maximum temperature at T1 after 13 minutes was 666.7 °C, and at T4 (on the unexposed surface) 22.2 °C. In sample 1b, smoke was observed from the inner part after approximately 15 minutes, accompanied by exposure of the fibreglass mesh on the MgO board. Around the 15th minute, the T1 thermocouple detached from the heated surface, 107

resulting in a measurement interruption. Until that point, the temperature showed a rising trend (max. T1 = 547.8 °C), followed by a decline after reattachment. The difference in maximum temperatures between samples 1a and 1b was due to their differing distances from the radiant panel (100 mm vs 150 mm). The temperature curve for sample 1b (Figure 9) shows a sharp inflection at the 25 th minute, when the temperature at T2 exceeded that at T1, indicating the onset of internal heat penetration. On the unexposed surface (T4), the temperature after 60 minutes was 104.2 °C. Fig. 10 illustrates sample 1b during and after testing. After around 20 minutes, significant bulging of the MgO board occurred due to thermal degradation of the PUR core, followed by heavy smoke emission from the sides and interior of the sample. After cooling, complete charring of the PUR insulation was observed, with the MgO board disintegrating in the thermally stressed region (Fig. 10c). For comparison, Figure 10d shows sample 1a after its early termination, where the MgO board and PUR insulation had already severely degraded after just 13 minutes. a)

Fig. 10 Sample 1b (MgO–PUR) during and after testing a) 20 min – bulging of the sample, b) 55 min – degradation of PUR and exposed fibreglass mesh of the MgO board, c) PUR insulation after sample cooling, d) sample 1a after 13 minutes of testing.

The results indicate that the PUR insulation completely degraded, leaving only a brittle black shell. Similar behaviour of sandwich panels with polyurethane cores has been reported by Tereňová (2024), in which the internal layer was almost entirely burned out, reducing the thickness from 60 mm to 7 mm. During testing, an unpleasant acrid odour was noted, causing eye and respiratory irritation. The critical temperature for the MgO–PUR sample was reached after 25 minutes, when rapid internal heating and thermal degradation of the PUR insulation occurred. The estimated fire resistance of the assembly was 15 minutes. Sample No. 2 (MgO–honeycomb) exhibited an estimated fire resistance of 30 to 45 minutes. Around the 5th minute, sample 2a began to brown in the centre, and by the 10th minute, smoke appeared at the interface between the MgO board and the honeycomb core. After 15 minutes, a grey circle formed on the surface of the MgO board, followed by smoke emissions that gradually intensified. By the 30th minute, noticeable bulging of the MgO surface occurred, along with exposure of the mesh, heavy smoke release, and a distinct odour. The temperature development for sample 2a (Fig. 11) shows that the temperature at T2 (572.8 °C) surpassed that at T1 (571.4 °C) after 43 minutes, indicating heat transfer through the honeycomb structure. At that time, the unexposed surface temperature (T4) was only 16.9 °C. By the 55th minute, smoke was observed escaping from the rear interface between the honeycomb and MgO board, and the test was concluded at 60 minutes. Sample 2b showed similar behaviour. Fig. 12 presents its temperature development, but the data 108

from sample 2a were considered more representative, as during sample 2b testing, thermocouple T1 detached from the MgO surface at the 6th minute, delaying the temperature increase and altering the crossover point between T1 and T2.

Fig. 11 Temperature profile Sample 2a (MgO–Honeycomb).

Fig. 12 Temperature profile Sample 2b (MgO–Honeycomb).

Photographs in Fig. 13 depict the sequence of changes during and after testing of sample 2a. The MgO surface began to brown at the start (Fig. 13a), deformed significantly by 30 minutes (Fig. 13b), emitted smoke from the rear interface at 55 minutes (Fig. 13c), and displayed degraded honeycomb material after removing the MgO board (Fig. 13d).

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Fig. 13 Sample 2a (MgO–Honeycomb) during and after testing a) browning of MgO at the beginning of the test, b) bulging of MgO at 30 min, c) 55 min – smoke emission from the rear gap, d) exposed mesh on MgO board, e) degraded honeycomb after removal of the MgO board.

The test of sample 3a was unsuccessful due to a failure in the automatic oxygen supply to the burner, which caused the radiation panel to shut down after 23 minutes and 52 seconds. The test of sample 3b proceeded correctly and was completed after 90 minutes. The temperature profiles for both samples (Figs. 14 and 15) revealed similar trends, suggesting that the results of sample 3a would have been comparable if the test had been completed. At the time of termination of the 3a test (23:52 min), the temperature at T1 was 518.7 °C, while the corresponding temperature for sample 3b was 569.5 °C. This difference was likely caused by inhomogeneities in the manually prepared mixture of MgO mortar and straw. The maximum temperature at T1 for sample 3b (586.4 °C) was reached after 39 minutes, while the unexposed surface (T4) temperature at that time was 32.1 °C. At the end of the 90-minute test, the T4 temperature reached only 57.8 °C. Throughout the test, the temperature at T2 never exceeded that at T1, demonstrating that the thermal barrier was maintained within the structure. The recorded temperature pattern suggested a fire resistance of 90 to 120 minutes.

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Fig. 14 Temperature profile Sample 3a (MgO–straw).

Fig. 15 Temperature profile Sample 3b (MgO–straw).

During testing, a crack began forming between the MgO board and the straw layer at the 9th minute (Fig. 16a), gradually expanding as the test continued. By the 25th minute, the fibreglass mesh became visible on the MgO surface (Fig. 16b), and after 50 minutes, smoke started escaping through the crack (Fig. 16c). At 60 minutes, the mesh was clearly exposed (Fig. 16d). Despite this, no further degradation occurred, and the sample remained structurally stable until the end of the 90-minute test. After removal from the chamber, the panel remained intact (Fig. 16e). Once cooled, the MgO board was detached, and fragmentation was observed only in the most heat-exposed areas, while the MgO mortar mixed with straw remained solid and undamaged (Fig. 16f).

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Fig. 16 Sample 3b (MgO–Straw) during and after testing a) formation of a crack at 9 min, b) 25 min – beginning of mesh exposure, c) 50 min – smoke emission from the enlarged crack, d) 60 min – pronounced exposure of the mesh, e) sample after completion of the test, f) sample after removal of the MgO board.

Even after thermal exposure, the panel preserved structural integrity without delamination or complete disintegration. It suggests that the MgO–straw mixture not only prevents temperature breakthrough but also retains mechanical cohesion, an advantageous property for load‑bearing wall assemblies. The results demonstrate that the fire resistance of the tested assemblies strongly depended on the type of insulation core used. Although the thermal conductivity coefficients of the insulation materials were relatively similar (see Table 1), their behaviour under high temperatures differed significantly. For Sample 1 (MgO–PUR), the PUR insulation was destroyed, leaving only a brittle carbonised shell. It aligns with previous findings by Tereňová (2024), who reported similar behaviour in sandwich panels with polyurethane cores, in which the inner layer was almost entirely burned away, resulting in a thickness reduction from 60 mm to 7 mm. The sample emitted a pungent odour throughout testing, causing eye and respiratory irritation. The critical temperature occurred approximately 25 minutes into the experiment, corresponding to rapid internal heating and the onset of PUR degradation. The estimated fire resistance was therefore 15 minutes. In the case of Sample 2 (MgO–honeycomb), the improved fire resistance (30 to 45 minutes) was attributed to the unique geometry of the honeycomb core. Its dense structure 112

delayed heat transfer and fire spread, contributing to greater stability of the MgO board during exposure. As Lee (2025) noted, suitable flame-retardant treatment of honeycomb materials can slow combustion and improve fire performance. The critical temperature for this sample was reached after 43 minutes, when gradual degradation of the honeycomb core began. Sample 3, the MgO–straw mixture combining natural reinforcement with MgO mortar, showed clearly superior thermal and structural stability, achieving 90–120 minutes of fire resistance. It confirms its potential as an effective and sustainable core material for load‑bearing timber assemblies, see also Abdul Motaleb et al. (2022) or Tlaiji et al. (2022). Compared to the MgO–PUR and MgO–honeycomb panels, the MgO–straw composite reduced the temperature rise on the unexposed surface by approximately 45–60 %, and maintained stable internal temperature gradients throughout the 90‑minute exposure. The primary advantage of MgO-based boards lies in their resistance to high temperatures and flame. When used as cladding for structural components, they significantly enhance the overall fire resistance and safety of the construction. This finding aligns with the study by Švajlenka et al. (2021), who evaluated thermal parameters of wall assemblies with internal linings made of gypsum, MgO, and clay boards. Their results showed that wall variants using double MgO boards (2 × 12.5 mm) achieved some of the best thermaltechnical performance and, based on our findings, are also expected to provide superior fire resistance. In summary, the fire performance of MgO-based structural assemblies is primarily determined by the insulation material selected. The more susceptible the insulation is to thermal degradation, the more rapidly temperatures rise inside the structure, leading to loss of MgO board integrity. In contrast, the MgO–straw sample retained its structural cohesion even after 90 minutes of exposure, whereas the MgO–PUR and MgO–honeycomb samples showed visible deterioration and fragmentation of the MgO surface during and after the tests.

CONCLUSION The results of the research demonstrate that magnesium oxide (MgO) boards are a suitable fire protection system for achieving the required fire resistance of building structures. The findings revealed that the behaviour of these materials under fire conditions is significantly influenced by the composition of the structural element and, above all, by the thermal insulation material used directly behind the MgO cladding. Plastic-based materials, such as polyurethane (PUR), proved unsuitable because they degrade rapidly at high temperatures and cause a substantial increase in the structure's internal temperature, leading to a gradual loss of mechanical integrity of the MgO board. The combination of MgO board with a natural material, i., paper honeycomb, achieved improved fire resistance. The specific geometry and low thermal conductivity of the honeycomb core enhanced the durability and temperature stability of the MgO layer. The best performance was obtained with MgO mortar mixed with straw, which proved to be the most suitable insulation material. During the entire 90-minute test, the temperature on the heated MgO surface remained higher than on subsequent thermocouples, indicating that no thermal degradation occurred within the inner layer. For further research, other ecofriendly materials such as mineral wool, wood fibre, straw panels, or natural wood-based composites are recommended as potential insulation cores.

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MgO boards, when combined with an appropriate filler material within a structural assembly, are a promising solution for enhancing the fire resistance of load-bearing elements in multi-storey timber buildings. The results presented confirm that appropriate combinations of MgO‑based facings and natural insulation materials, such as straw–MgO mortar, can significantly enhance the fire safety and environmental performance of modern timber structures. REFERENCES Abdul Motaleb, K. Z. M., Pranta, A. D., Repon, M. R., Karim, F.-E. , 2024. Preparation and characterization of MgO-based composites: Analysis of moisture, corrosion, and fungal resistance, and mechanical properties. Construction and Building Materials 447, 137926. https://doi.org/10.1016/j.conbuildmat.2024.137926 Baláž, P., 2008. Slovenský magnezit. Enviromagazín 6/2008/Slovak magnesite. Enviromagazin 6/2008 online. https://www.enviromagazin.sk (accessed on 23 October 2025). Caustic-Calcined-magnezite. Star Grace Mining CO., Limited online. https://sk.magnesiumfertilizer.com/mineral-fertilizer/magnesium-oxide-fertilizer/caustic-calcined-magnesite-1.html (accessed on 13 October 2025). Dubecký, D., Špak, M., Kozlovská, M., 2017. Experimental Preparation of Magnesium Oxide Board. Applied Mechanics and Materials, Vol. 861, pp. 11-18, 2017. ISSN 1662-7482. Džidić, S., Miličić, I. M., 2017 Fire resistance of the straw bale walls, in: 5th International Conference Contemporary Achievements in Civil Engineering. Subotica, pp. 423-432. htttps://doi:10.14415/konferencijaGFS2017.044 Chen, D., 2025. How does interior MgO board perform in a fire, Jiangsu, China online. https://sk.leader-board.net/blog/how-does-interior-mgo-board-perform-in-a-fire-549447.html (accessed on 22 October 2025). Iqra, Soe, K., Yang, R., Zhang, Y.X., 2025. A Review of Recent Advances in MgO-Based Cementitious Composites for Green Construction: Mechanical and Durability Aspects. Buildings, 15, 3513. https://doi.org/10.3390/buildings15193513 Jandačka, J., Holubčík, M., 2020. Emissions production from small heat sources depending on various aspects. Mob. Netw. Appl. 25, pp. 904–912 (Google Scholar) (CrossRef) Jensen, L. S., 2000. European classification of products for reaction to fire - DS/EN 13501-1. Fire Technology, 36: 95-103. Lee, J. 2025. Is the honeycomb core fire resistant? China online. https://sk.cnsanmachineryru.com/blog/is-a-honeycomb-core-fire-resistant-171831.html (accessed on 24 October 2025). Maršál, K., 2016. Fire reaction of thermal insulating materials. Advanced Building Materials. Springer, Cham. p. 191-197. Mokrenko, D., Kozlovská, M., 2020. Comparative analysis of magnesium oxide boards properties. IOP Conference Series Materials Science and Engineering 867. https://doi:10.1088/1757-899X/867/1/012032 Morais, C. R., Pinto, G. L., Mendes, A., 2024. Sustainable carbonaceous raw materials: A contribution to reduce the negative environmental impacts of chemical industry. Current Opinion in Green and Sustainable Chemistry, 49, 100913. STN EN 1363-1: 2021 Skúšanie požiarnej odolnosti. Časť 1: Základné požiadavky [Fire resistance testing - Part 1: Basic requirements]. STN EN 13501-1:2019 Klasifikácia požiarnych charakteristík stavebných výrobkov a prvkov stavieb. Časť 1: Klasifikácia využívajúca údaje zo skúšok reakcie na oheň [Classification of reaction to fire performance of construction products and building elements - Part 1: Classification using data from reaction to fire tests]. Švajlenka, J., Kozlovská, M., Mokrenko, D., 2021. MgO-Based Board Materials for Dry Construction Are a Tool for More Sustainable Constructions – Literature Study and Thermal Analysis of Different Wall Compositions. Sustainability 2021, 13(21), 12193.

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https://doi.org/10.3390/su132112193 Tereňová, Ľ., 2024. Protipožiarna bezpečnosť PUR a PIR panelov. Požární ochrana 2024 – Recenzovaný sborník abstraktů XXXIII. ročníku mezinárodní konference/Fire safety of PUR and PIR panels. Fire protection 2024 – Peer-reviewed proceedings of the XXXIII International Conference. Ostrava: SPBI, 2024. pp. 112-117. Tlaiji, G., Biwole, P., Ouldboukhitine, S., Pennec, F., 2022. A Mini-Review on Straw Bale Construction. Energies 2022, 15, 7859. https://doi.org/10.3390/en15217859 Voroncov, V., 2008. Natural materials in architecture: training aid (Belgorod, Russia) Voština. Harona, s.r.o. online. https://vostina.com/ (accessed on 15 October 2025).

ACKNOWLEDGMENT This work was supported by the Slovak Research and Development Agency under the Contract no. APVV-22-0030. The authors also wish to thank the Department of Technology and Innovation in Construction, Faculty of Civil Engineering, Technical University of Košice, for providing the samples used in the fire resistance testing. AUTHORS’ ADDRESSES Ing. Ľudmila Tereňová, PhD. Department of Fire Protection Faculty of Wood Sciences and Technology, Technical University in Zvolen T. G. Masaryka 24 960 01 Zvolen, Slovakia ludmila.terenova@tuzvo.sk Ing. Daria Mokrenko, PhD. prof. Ing. Mária Kozlovská, CSc. Department of Technology and Innovation in Construction Faculty of Civil Engineering, Technical University of Kosice Vysokoškolská 4, 042 00 Košice, Slovakia daria.mokrenko@tuke.sk maria.kozlovska@tuke.sk

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ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 117−126, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.11

THE INFLUENCE OF SEWING THREAD FINENESS AND STITCH LENGTH ON SEWN JOINT STRENGTH Anna Vilhanová – Nadežda Langová – Marek Vojtkuliak ABSTRACT The strength and, by extension, the aesthetic integrity of sewn seams in upholstered furniture covers are key determinants of overall product quality. An upholstery fabric with a sandwich structure composed of two plain-weave layers is examined in the study, and how sewn-seam performance in both warp and weft directions is affected by sewing thread fineness (linear density: 135, 90, and 70 tex) and stitch length (3, 4, 5, and 6 mm). Specimens were prepared and tested in tension in accordance with EN ISO 13935-1. The maximum force at failure (Fmax) and failure modes were recorded. Results show that increasing thread linear density (i.e., using coarser threads) increases seam strength in both joining directions, with the highest Fmax obtained for 135 tex. Shorter stitches (3–4 mm) provided higher seam strength than longer stitches (5–6 mm). Failure mode depended on stitch length: at shorter stitches, rupture occurred primarily in the fabric at Fmax, whereas at longer stitches, failure was dominated by thread breakage. The findings provide actionable guidance for selecting thread and stitch parameters to enhance seam performance in upholstery applications. Optimizing these parameters can extend the service life of upholstered products, reduce material waste, and support more sustainable manufacturing practices. Keywords: sewn joint; seam strength; stitch length; sewing thread fineness; upholstery fabric; tensile test; seam failure.

INTRODUCTION The upholstery of functional surfaces in seating and sleeping furniture can be considered a unique type of surface finishing. In addition to its aesthetic value, upholstery significantly enhances user comfort. Upholstered constructions are typically characterized by a sandwich structure composed of materials of different natures, with textile cover fabrics playing a key role. The cover layer of the upholstery is subjected to user-induced loading during the service life of the product; therefore, upholstery fabrics are required to exhibit higher strength and performance characteristics compared to apparel textiles (Skorupińska et al., 2021; Joščák and Langová, 2018; Zubauskienė, 2017). Research into the properties of textile materials used across various fields, including upholstery, provides valuable insights through evaluations of parameters such as tensile strength, elongation, abrasion resistance, air permeability, and others. The production of upholstery covers is a process in which two-dimensional fabrics are transformed into threedimensional forms by assembling various pattern pieces. This transformation is achieved through sewing, which represents one of the critical processes determining the quality of the 117

final upholstered product (Levent, 2016; Vilhanová, 2021; Liao et al., 2014; Hunter and Cawood, 1979; Hui et al., 2007; Al Sarhan, 2011; Khanna et al., 2015; Bharani and Mahendra Gowda, 2012). The mechanical properties and structural characteristics of the joined material are fundamental determinants of seam quality; consequently, it is essential to examine and understand how specific material attributes influence sewability. Among the key factors affecting both seam strength and appearance is the fabric weave. Mukhopadhyay and Midha (2013) demonstrated that plain-weave fabrics exhibit the highest seam strength in both directions, attributed to the high number of interlacing points per unit area, which restricts yarn mobility under load. By contrast, twill constructions allow greater yarn displacement, thereby reducing seam strength. Moreover, Al Sarhan (2011) reported a positive effect of fabric density on seam performance, with higher densities enhancing seam strength across all seam types. Stitching direction also significantly influences strength, with warp-oriented seams generally stronger than weft-oriented seams. Çitoğlu et al. (2011) observed that the highest values of seam strength and elongation were achieved when fabrics were joined diagonally. Similarly, Oztas and Gurarda (2019) compared stitch angles and reported that seams prepared at 0°, 45°, and 90° had the greatest seam strength, whereas seams prepared at 30° and 60° had the lowest. Mohamed (2019), in a study on the influence of weft density and yarn material origin, reported that increasing fabric density positively affects the strength of sewn joints. Yildirim (2010) further highlighted the problem of seam opening in woven fabrics, which occurs due to the relative movement of weft yarns through warp yarns (or vice versa) during use. Scientific studies have demonstrated that the seam quality of a given textile fabric depends on the interactions among the fabric, sewing thread, stitch type, seam type, and sewing conditions, including needle size, needle geometry and surface, stitch density, sewing speed, and appropriate machine handling and maintenance. Among the parameters influencing seam quality, the fineness (linear density) of the sewing thread plays a particularly important role. In general, researchers have reported that increasing thread thickness increases seam strength (Mukhopadhyay et al., 2006; Gribaa et al., 2006; Gurarda, 2008; Bharani et al., 2012; Hayes and McLoughlin, 2013; Datta et al., 2017; Bhavesh et al., 2018). On the other hand, Gribaa et al. (2006) noted that thicker threads necessitate the use of larger needles, which may damage the material being joined. In addition to fineness, the material origin and structural design of the sewing thread play a crucial role in determining its properties (Hayes and McLoughlin, 2013). Behera et al. (1997) compared polyester, cotton, and core-spun polyester threads for joining denim fabrics. Their results showed that core-spun threads exhibited the highest breaking strength and elongation, followed by polyester and cotton threads. The increased strength of corespun and polyester threads was attributed to the presence of stronger filaments in the core and the higher tenacity of polyester fibers. These findings are consistent with those of Ünal (2012) and Sular et al. (2015). Meric and Durmaz (2005) compared multifilament and staple sewing threads, finding that seams produced with multifilament threads had higher seam strength, whereas those made with staple threads had the lowest strength. Many studies have examined the effect of stitch density on the tensile properties of seams. It has been consistently observed that both seam strength and seam efficiency increase with higher stitch density (Hunter and Cawood, 1979; Mukhopadhyay et al., 2004; Gurarda, 2008; Ünal, 2012; Nassif, 2013; Datta et al., 2017; Bhavesh et al., 2018). This behavior can be explained by the increased number of contact points between the sewing thread and the fabric yarns, which produces a firmer interlocking along the seam line and a more uniform distribution of tensile stress across multiple points. 118

The influence of individual factors in the sewing process on seam performance can be expressed as seam efficiency, defined as the ratio of seam strength to the unseamed fabric strength. In the context of apparel textiles, this value generally ranges between 85% and 90% (Gurarda, 2008). High overall seam quality is essential for the long-term durability of a product and, together with consumer satisfaction, influences its marketability (Bharani and Mahendra Gowda, 2012). Research on sewn joints in upholstery fabrics remains limited, with many upholstery material types and seam variants yet to be explored. To improve seam quality in upholstery, laboratory testing of selected seam variants is necessary. The objective of this study was to determine the effect of sewing thread fineness and construction on the strength of seams in a selected upholstery fabric.

MATERIALS AND METHODS The test specimens were prepared from an upholstery fabric with a two-layer sandwich construction comprising two plain-weave fabrics. In the face (outer) fabric, the warp system is composed of multifilament yarns. In contrast, the weft system includes a combination of multifilament and chenille yarns (Fig. 1a). In the bottom (back) fabric, both the warp and weft systems are made of multifilament yarns (Fig. 1b). The properties of the tested material are summarized in Table 1.

Fig. 1 Structure of upholstery fabric LONDON: (a) face side, (b) back side. Tab.1 Properties of the upholstery fabric LONDON. Material composition 97 % PES 3 % nylon

Density (g/m2) 300

Fabric breaking strength (N) Warp Weft 898 801

Face fabric density (thread/cm) Warp Weft 36 21

Back fabric density (thread/cm) Warp Weft 26 14

The joining materials were sewing threads marketed under the trade names SYNTON and BELFIL. The properties of the sewing threads are listed in Table 2. Tab. 2 Properties of SYNTON and BELFIL sewing threads. Ticket number (Tkt)*

Material of threads

Synton 20 Synton 30 Belfil S 30 Synton 40

100 % PES 100 % PES 100 % PES 100 % PES

Fineness (tex) 135 90 90 70

Construction of threads multifilament multifilament staple multifilament

Thread breaking strength (N) 50.80 34.30 35.17 28.87

* The ticket number (Tkt) is a commercial numbering system used to indicate the linear density of sewing threads. It is an inverse system, threads with higher ticket numbers are finer, while those with lower numbers are coarser. Although not an SI unit, the ticket number provides a convenient reference for comparing thread sizes among different manufacturers and is roughly related to the linear density expressed in tex.

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Fig. 2 The testing sample dimension and loading scheme.

Test specimens of sewn seams were produced using a Groz-Beckert 100/16 sewing needle with an R-type point, which is recommended for joining woven fabrics, on an industrial Juki 185 sewing machine operating at a constant sewing speed of 4,000 stitches per minute. The study focused on the parameters of seam type 1.01.01 with stitch type 301 in accordance with ISO 4915:1991, at stitch lengths of 3 mm, 4 mm, 5 mm, and 6 mm. The mechanical properties of the sewn seams were evaluated following the methodology specified in ISO 13935-1. During the tensile test, the gauge length was set to 200 ± 1 mm and the loading rate to 100 mm/min. The seams were tested in both the warp and weft directions of the fabric, with eight specimens prepared for each direction. The loading scheme of the specimen and the test procedure are presented in Figure 2. Throughout testing, the maximum force acting on the seam was recorded, and the type of specimen failure was identified. The influence of selected factors, namely stitch length, sewing thread fineness, and thread construction type on seam quality was evaluated in terms of seam efficiency. Seam efficiency is defined as the ability of the fabric material to support the seam and is expressed according to Equation (1):

𝑃𝑠 =

𝐹𝑆𝑚𝑎𝑥 ∙ 100[%] 𝐹𝐹𝐿𝑚𝑎𝑥

(1)

Where: FSmax – seamed fabric strength (N); FFLmax – unseamed fabric strength (N).

RESULTS AND DISCUSSION The experimental part of the study investigated the influence of sewing thread fineness and stitch length on the mechanical properties of sewn joints in the selected upholstery fabric. The experimentally determined mechanical properties of the sewn joints, in which the tensile load was applied in the weft direction of the fabric, are presented in Table 3.

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Tab. 3 The average tested mechanical properties of the seam’s upholstery fabric in direction weft. Type of sewing thread

SYNTON 20

SYNTON 30

BELFIL 30

SYNTON 40

Stitch length (mm) 3 4 5 6 3 4 5 6 3 4 5 6 3 4 5 6

Seam strength ̅̅̅̅̅̅ 𝐹𝑚𝑎𝑥 (N) 704.43 682.43 675.88 609.54 650.36 540.98 451.57 398.28 706.57 531.56 412.80 386.17 573.60 451.80 403.92 338.58

Coefficient of variation CV (%) 2.66 2.56 2.39 5.05 5.46 3.27 6.08 4.98 3.54 5.66 5.14 6.10 2.58 8.83 1.88 5.11

Seam efficiency (%) 87.9 85.2 84.4 76.1 81.2 67.5 56.4 49.7 88.2 66.4 51.0 48,2 71.6 56.4 50.4 42.3

Slip modulus (N/mm) 20.65 20.42 19.65 17.67 21.08 22.01 20.01 13.24 21.08 19.09 19.70 16.09 20.75 20.01 19.27 17.89

Based on the results presented in Table 3, a clear and statistically significant effect of sewing thread fineness on the maximum load capacity (Fmax) of the sewn seams was observed. The highest Fmax value (704.43 N) was recorded for the seam sewn with SYNTON 20 thread at a stitch length of 3 mm. For all examined thread types, increasing stitch length led to a gradual decrease in both Fmax values and seam stiffness. The seam efficiency of the joints loaded in the weft direction ranged from 87.9% to 42.3%. The lowest efficiency (42.3%) was observed for the seam made with SYNTON 40 thread at a stitch length of 6 mm. Mechanical failure of the seams occurred under the maximum applied force (Fmax). When loaded in the weft direction, seams sewn with SYNTON 20 thread at stitch lengths of 3 mm and 4 mm exhibited rupture of the base fabric yarns (Fig. 3a). At a stitch length of 5 mm, a combination of slight fabric damage and complete thread breakage was observed (Fig. 3b). For all remaining seam variants tested in the weft direction, seam failure occurred due to thread breakage (Fig. 3c).

a) b) c) Fig. 3 Damage to joints loaded in the weft direction Synton 20.3 and 4 mm; b) Synton 20.5 mm; c) Syntom 30.5 mm.

The experimentally determined mechanical properties of sewn joints in which the loading force acted in the warp direction of the fabric are shown in Table 4. 121

Tab. 4 The average tested mechanical properties of the seam’s upholstery fabric in direction warp. Type of sewing thread

SYNTON 20 SYNTON 30

BELFIL 30

SYNTON 40

Stitch length (mm) 3 4 5 6 3 4 5 6 3 4 5 6 3 4 5 6

Seam strength ̅̅̅̅̅̅ 𝐹𝑚𝑎𝑥 (N) 778.09 766.66 758.20 623.64 700.93 581.65 448.86 370.42 691.69 518.14 452.01 399.29 607.45 468.13 375.35 316.43

Coefficient of variation CV (%) 1.95 3.11 4.23 4.87 4.07 4.37 4.42 5.96 4.03 2.07 5.34 2.03 3.01 5.72 3.42 5.58

Seam efficiency (%) 86.6 85.4 84.4 69.4 78.1 64.8 50.0 41.2 77.0 57.7 50.3 44.5 67.6 52.1 41.8 35.2

Slip modulus (N/mm) 22.54 20.19 20.72 19.64 20.87 20.70 19.44 13.93 22.08 21.09 20.00 16.08 19.96 20.01 18.90 17.02

For seams loaded in the warp direction, higher maximum strength values (Fmax) were observed compared with seams loaded in the weft direction, which is consistent with the inherently greater tensile strength of the fabric in the warp direction. The highest Fmax value (778.09 N) was recorded for the seam sewn with SYNTON 20 at a stitch length of 3 mm. As in the weft direction, seam strength decreased with increasing stitch length across all thread types, and seam stiffness (slip modulus) generally tended to decline as stitch length increased. The seam efficiency in the warp direction ranged from 86.6% (SYNTON 20, 3 mm) to 35.2% (SYNTON 40, 6 mm), with the lowest efficiency (35.2%) measured for the seam sewn with SYNTON 40 at 6 mm. Coefficients of variation were low overall (≈ 2–6%), indicating good repeatability of the measurements. The failure modes observed at Fmax were comparable to those identified in the weft direction. Specifically, rupture of the base fabric yarns occurred for seams sewn with SYNTON 20 at stitch lengths of 3 mm and 4 mm (Fig. 4a). At a stitch length of 5 mm, failure was characterized by thread rupture accompanied by limited damage to the fabric (Fig. 4b). For all remaining seam variants tested in the warp direction, failure occurred exclusively through thread rupture (Fig. 4c).

a) b) c) Fig. 4 Damage to joints loaded in the warp direction Synton 20.3 and 4 mm, b) Synton 20.5 mm, c) Syntom 30.4 mm.

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The significance of the effects of the studied factors on seam strength was assessed using univariate ANOVA followed by Duncan’s multiple range test (Table 5). The independent (main) effects of loading direction, stitch length, and sewing thread fineness were all statistically significant at the 5% level (Load Direction: F = 23.35, p < 0.001; Stitch length: F = 714.99, p < 0.001; Thread fineness: F = 1065.36, p < 0.001). Two- and threeway interactions were likewise significant, with the exception of the stitch length × loading direction interaction, which was only marginally significant (F = 2.90, p = 0.036). According to the F-test, thread fineness exerted the strongest effect on Fmax (F = 1065.36). Tab. 5 Table of three-factor analysis of variance.

Effect Intercept Load Direction Stitch length (mm) Sewing thread fineness Stitch length (mm)*Load Direction Stitch length (mm)*Sewing thread fineness Load Direction*Stitch length (mm) Sewing thread fineness*Stitch length (mm)*Load Direction

Univariate Results Significance for FSmax Sigma-restricted parameterization Effective hypothesis decomposition SS DOF F p 65365010 1 88462.39 0.000000 17251 1 23.35 0.000003 1584917 3 714.9 0.000000 2361583 3 1065.36 0.000000 6423 3 2.9 0.036347 329694 9 49.58 0.000000 47711 3 21.52 0.000000 52341

7.87

0.000000

Graphically, the influence of the watched factors, i.e. the fineness of the sewing thread and the stitch length, on the Fmax of sewn joints loaded in the warp and weft directions is shown in Figure 4.

Fig. 5 The effect of the sewing thread fineness and stitch length on the strength stitched joint.

Based on the evaluation of all experiments, sewing thread fineness (thickness) is a significant determinant of seam strength. Coarser threads produced higher Fmax, with the highest values recorded in the warp direction (778.09 N, SYNTON 20) and, for the weft direction, 706.57 N (BELFIL 30). This is consistent with the ANOVA, in which thread 123

fineness exerted the strongest effect on Fmax (F = 1065.36, p < 0.001). Increasing stitch length from 3 to 6 mm generally reduced both seam strength and stiffness (slip modulus) across all thread types; seam efficiency ranged from 87.9% to 42.3% in the weft and from 86.6% to 35.2% in the warp direction. Coefficients of variation were low (2–6%), indicating good repeatability. These findings are in agreement with the results reported by Gurarda (2008), Bhavesh et al. (2018), and Mukhopadhyay et al. (2004), who also found that increased thread fineness (coarser yarns) and shorter stitch lengths contribute to higher seam strength in woven fabrics. Regarding failure modes, fabric rupture (yarn breakage in the base fabric) was observed at shorter stitch lengths (3–4 mm) with the coarser SYNTON 20 thread, whereas at longer stitches (5–6 mm) failure was predominantly by thread breakage; at 5 mm, a mixed mode (minor fabric damage plus complete thread rupture) occurred occasionally. These observations indicate that needle-induced damage was not the controlling factor in strength reduction: fabric rupture arose mainly from higher local stresses at shorter stitches and larger thread diameter, while at longer stitches the thread itself became the limiting element. A similar pattern of failure behavior was reported by Al Sarhan (2011) and Oztas and Gurarda (2019), who observed a transition from fabric rupture to thread breakage with increasing stitch length, attributed to load redistribution and reduced stitch density. Interaction effects among stitch length, load direction, and thread fineness were broadly significant (including the three-way interaction, p < 0.001), underscoring that optimal seam parameters must be selected in combination rather than in isolation. These statistical relationships align with findings by Wang et al. (2001), who also demonstrated significant interaction effects among sewing parameters, indicating that the mechanical response of seams results from the combined influence of multiple variables rather than any single factor.

CONCLUSION The production of three-dimensional upholstery covers is a process in which twodimensional upholstery fabrics are transformed into three-dimensional forms by assembling individual components. This transformation is achieved through sewn joints, which are a critical quality factor in an upholstered product. Based on the experimental results, the following conclusions can be drawn: - The strength of the seam in the tested upholstery fabric depends on the loading direction, fineness of the sewing thread, and stitch density (stitch length); - Higher Fmax values were recorded for seams loaded in the warp direction compared to those loaded in the weft direction, corresponding to the higher tensile strength of the fabric in the warp direction; - Among the investigated parameters, sewing thread fineness was identified as the most influential factor affecting seam strength (confirmed by ANOVA; F = 1065.36, p < 0.001); - As sewing thread fineness increased (thinner thread), seam strength (Fmax) decreased. - Seam strength and stiffness (N/mm) decreased with increasing stitch length (3–6 mm) across all tested thread types and load directions; - These results confirm that both stitch length and thread fineness must be optimized jointly to ensure higher seam performance and durability of upholstery fabrics.

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REFERENCES Al Sarhan T.M., 2011. A study of seam performance of micro-polyester woven fabrics. Journal of American Science, Vol. 7 No. 12, pp. 41-46. Behera B.K., Chand S., Singh T.G., Rathee P., 1997. Sewability of denim. International Journal of Clothing Science and Technology, Vol. 9 No. 2, pp. 128-140. ISSN: 0955-6222 Bharani M., Mahendra Gowda R.V., 2012. Characterization of seam strength and seam slippage on pc blend fabric with plain woven structure and finish. Research Journal of Recent Sciences, Vol. 1 No. 12, pp. 7-14. Bharani M., Shiyamaladevi P.S.S., Mahendra Gowda, R.V., 2012. Characterization of seam strength and seam slippage on cotton fabric with woven structures and finish. Research Journal of Engineering Sciences, Vol. 1 No. 2, pp. 41-50. Bhavesh R., Madhuri K., Sujit G., Sudhir M., Raichurkar P.P., 2018. Effect of sewing parameters on seam strength and seam efficiency. Trends in Textile Engineering and Fashion Technology, Vol. 4 No. 1, pp. 1-5. Çitoğlu F., Yükseloğlu S.M., Kuyucu Y. A., 2011. The study of stitch parameters on the effect of stitch strength of the polyester lining fabrics. Tekstil ve Konfeksiyon, Vol. 21 No. 1, pp. 82-86. Datta M., Nath D., Javed A., Hossain N., 2017. Seam efficiency of woven linen shirting fabric: process parameter optimization. Research Journal of Textile and Apparel, Vol. 21 No. 4, pp. 293-306. Gribaa S., Amar, S. B., Dogui, A., 2006. Influence of sewing parameters upon the tensile behavior of textile assembly. International Journal of Clothing Science and Technology, Vol. 18 No. 4, pp. 235-246. Gurarda, A., 2008. Investigation of the seam performance of pet/nylon-elastane woven fabrics. Textile Research Journal, Vol. 78 No. 1, pp. 21-27. Hayes S., Mcloughlin J., 2013. The sewing of textiles”, in Jones, I. and Stylios, G.K. (Eds), Joining Textiles Principles and Applications. Woodhead Publishing Series in Textiles, Number 110, pp. 62-122. Hui P.C.L., Chan K.C.C., Yeung K.W., Ng F.S.F., 2007. Application of artificial neural networks to the prediction of sewing performance of fabrics. International Journal of Clothing Science and Technology, Vol. 19 No. 5, pp. 291-318. Hunter L. Cawood M.P., 1979. Textiles: Some technical information and data IV: sewability, sewing needles, threads and seams. SAWTRI Special Publication, p. 94. ISO 4915:1991 Textiles. Stitch types. Classification and terminology ISO 13935-1:2014 Textiles. Seam tensile properties of fabrics and made-up textile articles Joščák P., Langová N., 2018. Pevnostné navrhovanie nábytku [Strength design of furniture]. Zvolen: Technická Univerzita vo Zvolene. ISBN 978-80-228-3146-8. Khanna S., Kaur A., Chaterjee K.N., 2015. Interactions of sewing variables: Effect on the tensile properties of sewing threads during sewing process. JTATM Journal of Textile and Apparel, Technology and Management, Vol. 9 No. 3, pp. 1-13. Levent T., 2016. Upholstery fabrics as a design element in interior space and selection criterias. Mugla Journal of Science and Technoology. Turkey: Graduate School of Natural and Applied Sciences in Mugla Sitki Koçman University, Vol 2, No 2, 38-43. ISSN 2149-3596. Liao Y., Smyth G. K., Shi W., 2014. FeatureCounts: an efficient general-purpose program for assigning sequence reads to genomic features. Bioinformatics, Vol. 30 no. 7, Meric B., Durmaz A., 2005. Effect of thread structure and lubrication on seam properties. Indian Journal of Fibre and Textile Research, Vol. 30, pp. 273-277. Mohamed, H. E. E., 2019. The Effect of Different Structural Factors "The kind and density of wefts" and Sewing Seams on The Functional Performance of Upholstery Fabrics. Architecture and Arts Magazine, No 17. Mukhopadhyay A., Ghosh S., Bhaumik S., 2006. Tearing and tensile strength behaviour of military khaki fabrics from greige to finished process. International Journal of Clothing Science and Technology, ISSN: 0955-6222.

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Mukhopadhyay A., Midha, V.K., 2013. The quality and performance of sewn seams. Joining Textiles Principles and Applications, Woodhead Publishing Series in Textiles, Number 110, pp. 175-207. Nassif N. A. A., 2013. Investigation of sewing machine parameters on the seam quality, Life Science Journal, Vol. 10 No. 2, pp. 1427-1435. Oztas H., Gurarda A., 2019. Investigation of the effects of different bias angles of stitching on seam performance of wool suits. AUTEX Research Journal, Vol. 19 No. 4, pp. 324-331. Skorupińska E., Wiadarek K., Sydor M., 2021. Influence of technological parameters on the upholstery seams in furniture. Annals of Warsaw University of Life Sciences – SGGW Forestry and Wood Technology № 114. Sular V., Mesegul C., Kefsiz H., Seki, Y., 2015. A comparative study on seam performance of cotton and polyester woven fabrics, The Journal of the Textile Institute, Vol. 106 No. 1, pp. 19-30. Ünal Z., 2012. The prediction of seam strength of denim fabrics with mathematical equations. Journal of the Textile Institute, Vol. 103 No. 7, pp. 744-751. Vilhanová A., 2021. Čalúnenie nábytku [Upholstery of furniture]. 1. vyd. Zvolen: Technická univerzita vo Zvolene. 124s. ISBN 978-80-228-3309-7. Yildirim K., 2010. Predicting Seam Opening Behavior of Woven Seat Fabrics. Textile Research Journal Vol 80(5). Zubauskienė D., 2017. Upholstery materials behavior evaluation method. Doctoral dissertation Technological Sciences, Materials Engineering, 124 s, ISBN 978-609-02-1393-3). ACKNOWLEDGMENT

This work was supported by the Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic under the research project VEGA 1/0450/25. AUTHORS’ ADDRESSES Ing. Anna Vilhanová, PhD. doc. Ing. Nadežda Langová, PhD. Ing. Marek Vojtkuliak, PhD. Technical University in Zvolen Faculty of Wood Sciences and Technology Department of Furniture and Wood Products T.G. Masaryka 24, 960 53 Zvolen, Slovakia vilhanova@tuzvo.sk langova@tuzvo.sk vojtkuliak@tuzvo.sk

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ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 127−140, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.12

INTERPERSONAL RELATIONSHIPS, CONFLICTS, AND NEPOTISM IN WOOD-PROCESSING BUSINESSES Denis Pinka – Mariana Sedliačiková – Martin Synák-Varga ABSTRACT The article is aimed at defining the quality of interpersonal relationships, the frequency of conflicts, and the degree of nepotism occurring in family businesses operating in the Slovak wood-processing industry. The research was conducted through a questionnaire survey of 362 family businesses, and the collected data were analyzed using statistical methods, specifically a hypothesis test of relative frequency and a modal analysis. The results revealed that positive relationships between family members and employees prevail in most family businesses, conflicts occur rarely, and nepotism is eliminated chiefly through transparent management practices. Confirmed hypotheses indicate a strong connection among relationship quality, conflict levels, and the occurrence of nepotism. The findings suggest that social aspects represent a significant factor in ensuring the stability and competitiveness of family businesses in the analyzed sector, contributing to theoretical knowledge and offering practical recommendations for human resource management and strategic development within family businesses in the wood-processing industry. Keywords: family business; wood-processing industry; conflicts; nepotism.

INTRODUCTION Family businesses (FBs) are recognized as the dominant and most prevalent organizational form within the structure of economies across the world (Rovelli et al., 2022). They are considered one of the fundamental driving forces of the economy, as they provide stability, direction, and a strong sense of responsible connection between family owners and the business itself (Aguinis et al., 2020). Family businesses are value-oriented, aiming not only for economic profit but also for the well-being of all stakeholders (Astrachan et al., 2020). Particular emphasis is placed on relationships with employees, who are among the key groups influencing the success of family businesses (Santoro, 2021). Qi Wang (2024) defines FBs as entrepreneurial entities that serve as both organic family units and entrepreneurial entities. They are not only economic organizations of family members oriented toward profit generation, but also environments in which family traditions, values, and relationships significantly shape how the business is managed. Aguinis et al. (2020) defined family businesses as enterprises in which several family members are involved in ownership or managerial roles, with one family member usually playing a key role in the business's management. The importance of family ties and values influencing managerial decisions, resource allocation, and overall business performance must be emphasized (Santoro, 2021). The presence of moral values fundamentally affects decision-making 127

processes and the ethical norms by which the business is governed. This value-based foundation permeates the functioning of the business, shaping its corporate culture and influencing the behavior of individuals as well as the organization as a whole (Astrachan et al., 2020). The long-term and traditional orientation characteristic of family businesses provides stability; however, in an environment of rapid technological or market changes, such stability may also become an obstacle to flexibility, which must be addressed promptly in a competitive setting (Škare and Soriano, 2021). In recent decades, family businesses have undergone significant institutional, legal, and managerial transformations, while their importance as key economic actors has been steadily increasing worldwide (Ahmed and Uddin, 2024). A major shift in family entrepreneurship in the Slovak Republic occurred in 2022, when a proposal to amend Act No. 112/2018 Coll. on the Social Economy and Social Enterprises was submitted and subsequently adopted, taking effect in July 2023. This amendment led to the legislative definition of family entrepreneurship within the Slovak Republic. According to this definition, a family business is characterized as a commercial company, cooperative, or sole trader, provided that multiple members of a typical family hold legally defined ties to the business. Members of a typical family are considered to include spouses, direct relatives, siblings, persons related up to the fourth degree, and their spouses, while the relationship of family members to the business must meet specific legal conditions (NRSR, 2022). For this research, the legislatively anchored definition described above is applied. Family businesses face specific challenges associated with the interconnection between family and business environments. This unique combination provides not only stability but also the potential for conflict. Conflicts in family businesses may take the form of disagreements over decisions, work content, as well as personal and emotional disputes among family members or employees (Gavrić, 2021). A conflict is defined as the awareness of interpersonal incompatibilities that involve emotional components, such as tension and disagreement, between participants (Mismetti et al., 2025). In family businesses, two hierarchies coexist the family hierarchy and the business hierarchy. A family member may hold a high position within the family but a low one within the business, or vice versa. This misalignment creates space for conflicts regarding relative positions and generates tensions that do not typically occur in non-family businesses (Kubíček and Machek, 2022). Conflicts in the workplace increase negative emotions and stress, which are subsequently transferred into family life, leading to tension, a decline in relationship quality, and family conflicts. Due to their specific needs, family businesses must face several challenges: attracting qualified employees, adapting them to a changing environment, and addressing weaknesses in hierarchical structures, where the owner often manages all business processes (Aguinis et al., 2020). In family businesses, participation in discussions about goals and strategies is usually lacking, leading to poor decision-making and conflicts. The dominant leader of a family business often avoids succession planning, seeking to retain decision-making authority and being reluctant to share accumulated know-how. Therefore, one of the most critical organizational changes faced by family businesses is succession and the transfer of leadership to the next generation (Gavrić, 2021). Succession planning is a fundamental and urgent issue in the field of family businesses, with only about 10% of them surviving into the third generation (Bağiş et al., 2023). Conflict is not static but evolves through processes that may lead to its escalation, spillover into other areas, or gradual resolution (Mismetti et al., 2025). If a business fails to provide adequate support, employees experiencing workplace conflicts are likely to feel negative emotional tension. Similarly, the behavior of family owners seeking to enhance the positions of other family members may provoke resentment among non-family employees, who perceive unfair treatment and limited opportunities for 128

career advancement (Bağiş et al., 2023). Family businesses that can manage such conflicts effectively are more likely to survive the process of transferring leadership to the next generation, as avoiding conflicts often leads to stagnation within the business and hinders the development of new strategies, future planning, business growth, and employee career progression (Gavrić, 2021). Factors that may reduce autocratic business performance include conservatism, weak strategic planning, nepotism (favoring family members who may not be sufficiently qualified), founder autocratic leadership, unclear division of roles, and rivalry among family members, particularly among siblings (Moresová et al., 2021). According to Noisette (2024), employing family members is a common way to share business resources and know-how within the family. Yet it may simultaneously harm the business by selecting unproductive family members and demotivating non-family employees—a negative aspect known as nepotism. Although the involvement of family members in the business may support the company’s tradition and values, nepotism can also generate feelings of injustice among employees who are not part of the family (Shatila et al., 2024). Shatila et al. (2024) state that nepotism increases turnover intentions and reduces job satisfaction and trust in the business among non-family employees. Fries et al. (2021) note that an essential balancing factor is the participation of non-family members in the management of family businesses, as they can actively participate in selecting new employees. Despite these negative aspects, the legal regulation of nepotism remains limited. The reason is that such prohibitions could lead to discrimination, as they would also restrict the employment of qualified family members (Ignatowski et al., 2021). Social stability in family businesses results from a systemic interaction among relationship quality, conflicts, and workplace fairness. Family businesses function as complex social systems in which the quality of relationships influences the emergence of disputes and the manner in which decisions are made across both the family and the enterprise. The level of trust, communication, and fair leadership fundamentally shapes social stability, the degree of tension, and the effectiveness of management (Clauß et al., 2022). Zhang et al. (2025) emphasize that family values, fairness, and equitable decisionmaking represent the main elements of social stability. Family businesses function as an interconnected system in which changes in one area are immediately reflected in behaviours across others. This means that relationships, conflicts, and social processes need to be examined within an integrated concept rather than in isolation. This systemic framework, therefore, provides an adequate theoretical basis for the concept of social stability, which can subsequently be tested through empirical analyses. The wood-processing industry (WPI) forms an integral part of the forestry–wood complex and represents one of the main pillars of bioeconomy development. Its primary function is to transform inputs (raw wood) into outputs (a wide range of value-added products) (Lorincová, 2024). According to Tao et al. (2024), wood is characterized by its biodegradability, renewability, recyclability, and economic efficiency, which fundamentally distinguish it from traditional industrial materials such as steel or plastic. These properties make wood an ecologically and economically significant resource that can replace energyintensive materials, thereby contributing to a sustainable economy. In the Slovak Republic, the forestry sector is an important employer, with approximately 70,000 people employed in this industry (Kolesárová et al., 2021). Supporting the development of the wood-processing industry contributes not only to economic stability but also to improving environmental quality (Gejdoš et al., 2023); however, within the framework of strategic management in the Slovak Republic, a comprehensive and systematically developed strategy focused on the development of the wood-processing industry is still lacking, resulting in the sector’s 129

potential not being fully utilized (Moravčík et al., 2021). The concentration of businesses within the wood-processing industry creates favorable conditions for labor market development, more efficient use of inputs, and more intensive knowledge and technology transfer. These factors significantly support the overall growth of the sector (Tao et al., 2024). Zhang et al. (2024) state that the wood-processing industry is currently undergoing a process of profound transformation. This development is determined by the implementation of modern technologies and the intensive digitalization of production processes, which fundamentally reshape its strategic orientation within the context of the contemporary economy (Sedliačiková et al., 2023). According to Lorincová (2024), the global demand for wood products opens new development opportunities but simultaneously imposes high demands on the responsible use of raw materials. Therefore, achieving a balance between economic and environmental factors is an essential condition for the long-term, stable development of the entire sector. The main scientific aim of this study is to define the quality of relationships between family members and employees in family businesses operating in the Slovak woodprocessing industry, which significantly influence the level of cooperation and the organizational climate in these businesses.

MATERIALS AND METHODS The methodological framework of the paper was designed to ensure a clear structure, logical coherence, and the ability to achieve the stated scientific objective systematically. The research process was divided into three interrelated stages. The first stage was focused on the theoretical analysis of family business issues with a specific emphasis on conflicts, their resolution, and manifestations of nepotism in the context of family businesses, including the focus on the wood-processing industry. For the research, an extensive analysis of secondary sources was conducted. Various scientific methods were applied in processing the information, particularly description, comparison, analogy, summarization, and synthesis of findings. Based on the identified aspects of family entrepreneurship, business conflicts, nepotism, and the quality of relationships influencing business activities in the wood-processing industry among family businesses in the Slovak Republic, the following hypotheses were formulated: H1: It was assumed that in the majority of family businesses operating within the Slovak wood-processing industry, positive relationships prevail between family members and their employees. Family businesses are characterized by high levels of trust, loyalty, and mutual support among family members and employees, which contribute to more stable and harmonious workplace relationships (Danes and Brewton, 2012). Emphasis on long-term objectives, personal bonds, and generational continuity creates positive social capital, mitigating conflicts and strengthening an organizational culture based on cooperation and trust (Memili et al., 2015). H2: It was assumed that the frequency of conflicts between employees and family members in family businesses operating within the Slovak wood-processing industry is minor. A strong emphasis on trust, mutual respect, and long-term interpersonal relationships prevails in family businesses, contributing to reduced workplace conflict. Due to a high level of social capital and the family’s long-term orientation, a culture of trust and mutual loyalty is built within family businesses, which decreases the likelihood of frequent open conflicts 130

between employees and family members (Rosecká, 2022). Family governance systems and effective internal communication within family businesses serve as tools to prevent the escalation of internal disputes (Pieper, 2010). H3: It was assumed that the majority of family businesses operating within the Slovak wood-processing industry avoid nepotism in the recruitment and promotion of employees. Transparent personnel decision-making and the professionalization of management in family businesses are increasingly perceived as key factors of long-term stability and reputation (Calabrò et al., 2019). Modern family businesses strive to maintain a balance between family ties and professional competence, thereby minimizing the risk of favoring relatives over qualified candidates. Moreover, the implementation of formal governance rules and transparent human resource processes helps limit manifestations of nepotism (Berent-Braun et al., 2021). Before launching the primary survey, a pretest of the questionnaire was conducted in January 2025 to verify its clarity, content relevance, and technical functionality. The pretest was administered via Google Forms, and respondents were selected at random using a random number generator. A total of 21 respondents participated, and their feedback enabled the refinement and clarification of several items, thereby increasing the validity and reliability of the final research instrument. The second stage of the research was then focused on obtaining current empirical data directly from Slovak wood-processing family businesses. The final version of the structured questionnaire was distributed to these enterprises via the Google Forms online platform from 3 February 2025 to 9 May 2025. The selected approach enabled reaching a larger number of respondents across different regions of the Slovak Republic while ensuring anonymity, which is essential for obtaining honest responses on sensitive topics such as conflicts and nepotism. The questions were designed to provide participants with multiple response options. The questionnaire was divided into two thematic sections: the first contained classification questions aimed at identifying the business's basic characteristics, while the second included questions about relationships between family members and employees, as well as perceptions of nepotism. According to the FinStat portal (2024), at the time of the survey, 5.316 companies were operating in the wood-processing industry in Slovakia. A total of 4.571 businesses were contacted as part of the research. In the initial phase of data evaluation, a data matrix was created in Microsoft Excel, serving as the basis for obtaining summary outputs. Before testing the formulated hypotheses, it was necessary to verify compliance with the minimum sample size (n) requirement, which is a key prerequisite for generalizing the obtained results to the entire population of the woodprocessing industry. The calculation of the minimum number of observations was carried out with an acceptable error level of 5 % (e = 0.05), a confidence level of 95 % (z = 1.96), a known population size (N = 5.116), and a parameter p = 0.5, according to the methodology presented by Faeron (2017). The value was determined using the following formula: 𝑝 𝑥 (1 − 𝑝) 𝑛≥ 2 (1) 𝑒 𝑝 𝑥 (1 − 𝑝) + 𝑁 𝑧2 The next step involved the verification of the formulated hypotheses. The data obtained from the questionnaire survey were subjected to mathematical and statistical processing using the software Statistica 14. Hypotheses H1, H2, and H3 were verified through a one-tailed hypothesis test of relative frequency using the following test criterion (Pacáková, 2009):

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𝑢=

𝑓 − 𝜑0 √𝑓(1 − 𝑓) 𝑛

(2)

The test was used to verify the hypothesis concerning the equality of the population proportion with a specified constant (50 % under the conditions of the formulated hypotheses). The null hypothesis stated that the population proportion equals the specified constant. In contrast, the alternative hypothesis stated the opposite, namely that the proportion differs and is either greater or smaller than the given constant. The validity of the hypotheses was tested at a significance level (α) of 5 %, meaning that the results were considered reliable at the 95 % confidence level. The acceptance or rejection of the null hypothesis was determined based on the 5 % quantile of the standardized normal distribution, with the decisive factor being the p-value (p-level), which depends on the selected significance level (Pacáková, 2009). After processing and analyzing the data, the hypotheses were evaluated numerically, graphically, and descriptively. The methods of analogy, summarization, comparison, description, and logical–systematic reasoning were applied, along with a systems approach that enabled the comprehensive quantification of relationships and the dynamics of conflicts in family businesses. As part of the hypothesis verification, the mathematical–statistical indicator, the mode, was also utilized. The mode, also referred to as the modal or most probable value, is the value of a variable in a statistical dataset that occurs with the highest relative frequency. In processing questionnaire data, the mode was determined from a frequency table that summarized the distribution of respondents’ answers. This value indicates the most typical response within the analyzed variable and enables a better understanding of the preferences or opinions of respondents within the examined dataset (Hindl et al., 2012). The final stage focused on synthesizing findings and formulating recommendations for practice and future research. The methods of deduction, analogy, and summarization were applied. The chosen approach provided a basis for proposing strategic directions for further study of conflicts in family businesses and the impact of nepotism in the woodprocessing industry in the Slovak Republic.

RESULTS AND DISCUSSION The introductory section of the questionnaire focused on identifying the research sample. Based on the calculations, a minimum of 358 respondents (FBs) was required to ensure statistical significance. In the research, a total of 4,571 respondents were contacted, and 479 businesses completed the questionnaire, of which 362 were family businesses. This represents a response rate of 10.48 %. The obtained data confirmed that the questionnaire return rate exceeded the minimum requirement for the sample size, thereby ensuring representativeness for the population of family businesses operating within the Slovak woodprocessing industry. Table 1 presents the basic characteristics of the family businesses in the wood-processing sector that participated in the survey (n = 362), categorized by company size, legal form, and duration of market operation. The summary of these data represents the initial step of the research, as it provides a more precise overview of the composition of the research sample.

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Tab. 1 Basic identification of FBs. Questions Position in the enterprise Enterprise size

Answers Manager Employee 27.90 % 25.97 % 10 – 49 50 – 249 employees 1 – 9 employees employees (small (medium-sized (micro enterprise) enterprise) enterprise) 41.44 % 40.88 % 14.09 % Owner 44.20 %

Enterprise legal form

Self-employment 11.05 %

Ltd. 80.66 %

Join Stock 6.35 %

Enterprise active state

< 1 year 1.66 %

1 – 5 years 13.81 %

6 – 10 years 20.72 %

Other 1.93 % 250 or more employees (large enterprise) 3.59 % General Partnership 0.28 % 11 – 20 years 21 years > 29.56 % 34.25 % Cooperative 1.66 %

The central part of the study focused on evaluating responses from the questionnaire survey, which concentrated on relationships, conflicts, and nepotism, and their occurrence in business practices within family businesses operating in the wood-processing industry. For the presented research, the key responses were related to the following three questions: Question 1: How would you describe the relationships between family members and employees in your business?

Fig. 1 Relationships between family members and employees.

In the analysis of responses to Question 1 (Figure 1), the majority of respondents (50.83%; 184 FBs) perceive the relationships between family members and employees in their enterprises as positive, indicating an excellent level of stability in workplace relationships. Almost the same proportion of respondents (46.96%; 170 FBs) described these relationships as neutral, suggesting a more pragmatic rather than emotionally supportive character of cooperation. Only a small group of respondents (2.21%; FBs) evaluated these relationships negatively, suggesting that conflicts or tensions between family members and employees occur only rarely within the examined sample. For the statistical verification of Hypothesis H1, a hypothesis test of relative frequency was performed. The hypothesis was set at a 50% level of significance. Based on the resulting p-level value (p = 0.000), which was lower than the significance level α (α = 0.05), Hypothesis H1 was accepted. This indicates that in the majority of family businesses operating within the Slovak woodprocessing industry, positive relationships prevail between family members and their employees. The stated result can be confirmed with a 95 % confidence level. The mode of responses reached a value of 3, which further confirms the predominance of highly positive 133

perceptions of relationships and the existence of a stable and trust-based working environment in most Slovak family businesses in the wood-processing industry. Question 2: How often do conflicts occur between employees and family members in your business?

Fig. 2 Frequency of conflicts between employees and family members.

From Figure 2, it can be observed that the majority of respondents (60.50 %; 219 FBs) stated that conflicts between employees and family members occur rarely or never in their enterprises. Occasional conflicts were reported by 36.46 % (132 FBs), while only a small portion of respondents (3.04 %; 11 FBs) indicated that conflicts occur frequently. These results point to a relatively stable and cooperative atmosphere in most family businesses, where efforts to prevent tension are supported by open communication and a clear division of responsibilities. For the statistical verification of Hypothesis H2, a one-tailed hypothesis test of relative frequency was applied, with the proportion value set at 50 %. The resulting p-value (p = 0.000) was lower than the selected significance level α = 0.05, confirming the acceptance of Hypothesis H2. Based on these results, it can be stated with 95% confidence that the frequency of conflicts between employees and family members in family businesses operating in the Slovak wood-processing industry is low. The mode of responses reached 3, thereby confirming that family businesses in the Slovak wood-processing industry experience minimal conflicts, while a harmonious working environment characterized by trust and mutual respect between family and non-family employees predominates. Question 3: Do conflicts related to nepotism occur in your business during recruitment and promotion processes?

Figure 3: Nepotism in family businesses.

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Based on the analysis of the results (Figure 3), the majority of respondents (64.92%; 235 FBs) stated that they avoid nepotism in recruitment and promotion within their enterprises entirely. A significant portion (30.11 %; 109 FBs) expressed only a partial preference for family members, while still considering professional qualifications, and only a small percentage (4.97 %; 18 FBs) reported that nepotism is a common practice. For the statistical verification of Hypothesis H3, a hypothesis test of relative frequency was also performed. Based on the resulting p-level value (p = 0.000), which was lower than the significance level α (α = 0.05), Hypothesis H3 was confirmed. This indicates that the majority of family businesses in the Slovak wood-processing industry avoid nepotism in employee recruitment and promotion. The mode of responses reached 1, indicating the predominance of family businesses that use transparent, merit-based human resource management mechanisms, thereby effectively eliminating the risk of interpersonal conflicts arising from nepotism. The synthesis of the empirical results revealed a strong interconnection among the three key areas of examination: the quality of relationships, the frequency of conflicts, and the degree of nepotism occurrence (Figure 4).

Fig. 4 Concept of social stability in family businesses.

The results, schematically illustrated in Figure 4, confirmed that positive relationships between family members and employees constitute a decisive stabilizing element of the internal corporate culture. Trust, loyalty, and cooperation form the foundation that significantly reduces conflicts and minimizes the risk of nepotism. A low level of disputes subsequently contributes to a harmonious working environment that promotes transparent and fair human resource management. Nepotism, understood as the favoritism of family members regardless of their qualifications, appears in the context of the examined enterprises as a factor disrupting organizational balance. The mutual interaction among positive relationships, low conflict, and the absence of nepotism creates a mechanism that enhances organizational performance and generational continuity in family businesses. From a scientific perspective, the responses to Question 1 are consistent with the findings of Santoro (2021) and Aguinis et al. (2020), who emphasize that family businesses tend to be more value-oriented and to demonstrate a higher level of responsibility toward their employees. Family ties may foster loyalty and trust, which are essential for team stability and the long-term performance of the enterprise (Leppäaho and Ritala, 2022). In family businesses operating in the wood-processing industry, interpersonal relationships often have a long-term, personal character, as these enterprises operate in an environment characterized by stability and cooperation. The wood-processing industry, as a sector, is characterized by a close connection between people and the production process, from craftsmanship to production management, which naturally strengthens the sense of belonging and responsibility toward the enterprise. Therefore, Hypothesis H1 was accepted and confirmed. This context may explain why the majority of respondents perceive the relationships between family members and employees as positive and without significant tension. Positive relationships represent an important prerequisite for preventing conflicts 135

and fostering cooperation between family and non-family employees. For family businesses, it is therefore essential to systematically develop a corporate culture based on transparent communication, fairness, and a clear division of competencies to prevent future conflicts. The research findings revealed that in most family businesses in the Slovak Republic, cooperation between family and non-family employees is relatively stable and free from significant tension. Hypothesis H2 was confirmed, and this result aligns with the findings of Gavrić (2021) and Mismetti et al. (2025), who found that effectively managed family businesses can prevent the escalation of conflicts through clear task allocation and open communication. It should be emphasized that more than one-third of respondents admitted the occasional occurrence of conflicts, which may indicate the existence of tensions that could, under certain circumstances, intensify. The rare occurrence of conflicts in family businesses in the wood-processing industry can be interpreted as a manifestation of a functional corporate culture that combines personal relationships with a professional approach to management. According to Sedliačiková et al. (2023), the implementation of modern managerial practices in the wood-processing industry contributes to improved communication and reduced tensions between family and non-family employees. Family businesses must not approach these occasional conflicts passively; instead, they should introduce mechanisms for their timely resolution. These include clearly defined communication rules, transparent work processes, and, where appropriate, the involvement of independent experts in conflict resolution. Conflicts, if left unaddressed, may over time escalate into emotional strain, reduce productivity, and negatively affect the employees involved. Effective conflict management can contribute to more harmonious relationships, long-term stability, and improved competitiveness of family businesses. The research confirmed the validity of Hypothesis H3, indicating a relatively high level of professionalization among Slovak family businesses, as the majority strive to maintain fairness and consider professional competence when making personnel decisions. The results obtained are consistent with the recommendations of Ignatowski et al. (2021), who argue that employing professional managers from outside the family is an appropriate solution when the family lacks sufficiently qualified members. Family businesses in the wood-processing industry often operate in smaller teams, where work quality and reliability are crucial to the continuity of production; therefore, employee selection is more often based on practical experience than on family ties. It can be concluded that, under the conditions in the Slovak Republic, a professional approach to human resource management prevails in family businesses in the wood-processing industry. The fact that approximately one-third of respondents reported some form of preferential treatment toward family members indicates the persistent presence of family ties in key personnel decisions. According to Shatila et al. (2024) and Chen et al. (2020), even partial nepotism may negatively influence perceptions of fairness among non-family employees, reduce their motivation and loyalty, and, consequently, lead to higher dissatisfaction and turnover. Moresová et al. (2021) and Fries et al. (2021) also emphasize that autocratic management and favoritism toward family members may undermine strategic planning and long-term business performance. Family businesses that strive to avoid nepotism or at least link it to professional competence have the potential to build fair enterprises and maintain employee loyalty.

CONCLUSION Family businesses represent a key structural component of modern market economies, and their importance extends beyond individual sectors. In an era of increasing emphasis on 136

sustainability, they play a crucial role in balancing economic objectives, generational continuity, and social responsibility. Properly designed strategic management, based on planning, innovation, and flexibility, enables family businesses to contribute to sustainable development over the long term. Given that the research was conducted within the woodprocessing industry, its specific characteristics must be taken into account, namely technological complexity, reliance on renewable resources, and strong alignment with sustainability principles. The wood-processing industry holds strategic importance for the Slovak economy, as it utilizes a renewable material – wood, which can be regarded as the material of the future. Due to its renewability, ecological nature, and low carbon footprint, wood serves as a foundation for long-term sustainable development and the strengthening of the Slovak Republic’s competitiveness within the green economy. The aim of the study was to analyze the quality of relationships between family members and employees in familyowned wood-processing businesses, identify the frequency of conflicts, and reveal specific factors, such as nepotism, that significantly influence cooperation and the organizational climate in family businesses. For the statistical verification of Hypotheses H1, H2, and H3, a one-tailed hypothesis test of relative frequency was performed. The results of the research confirm that family businesses operating in the Slovak wood-processing industry are characterized by a high level of social stability, stemming from the quality of interpersonal relationships, trust, and loyalty among family members and employees. The majority of respondents perceive the internal business environment as positive and harmonious, thereby confirming Hypothesis H1. The stability of interpersonal relationships is also reflected in the low frequency of conflicts, which occur only sporadically in most enterprises. Thus, Hypothesis H2 was confirmed, indicating that conflicts are rare and that family businesses employ preventive mechanisms grounded in communication, trust, and a clear division of competencies. The third hypothesis (H3) confirmed that the majority of the examined family businesses avoid nepotism in employee recruitment and promotion, emphasizing professional competence and fair treatment. Nevertheless, in some cases, a partial preference for family members was observed, indicating the persistent influence of family ties in personnel decision-making. The interconnection of all three examined factors, relationships, conflicts, and nepotism, creates a comprehensive picture of the social system of family businesses, functioning as a dynamic balance between personal relationships and professional management. It was confirmed that positive relationships directly contribute to reducing conflicts, while fair personnel decisions decrease the risk of tension and promote long-term stability. These findings confirm that social capital represents an essential source of competitive advantage for family businesses in the wood-processing industry. From a practical perspective, it is recommended to strengthen professional management, transparent HR processes, and internal communication, all of which help maintain a balance between the family and business environments. FBs that successfully combine family values with modern management principles achieve a higher degree of resilience, adaptability, and generational continuity. The main limitation of the conducted research is the relatively low response rate to the questionnaires, which, despite meeting the minimum required sample size, may affect the accuracy and representativeness of the findings. Given the voluntary participation of respondents, there is a potential risk of selection bias, as enterprises with a higher interest in development, stability, and professional management may have been more likely to participate, resulting in their overrepresentation in the final sample. For this reason, the results should be interpreted with some caution when generalized to the entire population of Slovak family businesses in the wood-processing industry. 137

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This research was supported by projects VEGA no. 1/0011/24, APVV-21-0051, APVV-220238, APVV-23-0116, COST CA23117, COST CA23157, IPA no. 2/2025 and by EU 139

NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I03-03-V05-00016 (IPA ESG no. 3/2024, IPA ESG no. 4/2024). AUTHORS’ ADDRESSES Ing. Denis Pinka prof. Ing. Mariana Sedliačiková, PhD. Ing. Martin Synák-Varga Technical University in Zvolen Faculty of Wood Sciences and Technology, Department of Business Economics T. G. Masaryka 24, 960 01 Zvolen, Slovakia xpinkad@is.tuzvo.sk sedliacikova@tuzvo.sk xsynakvarga@is.tuzvo.sk

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ACTA FACULTATIS XYLOLOGIAE ZVOLEN, 67(2): 141−154, 2025 Zvolen, Technická univerzita vo Zvolene DOI: 10.17423/afx.2025.67.2.13

CONTROLLING IN WOODWORKING AND FURNITURE MANUFACTURING ENTERPRISES: DOES PERFORMANCE INFLUENCE ITS ESSENCE AND APPLICATION? Marek Potkány – Jarmila Schmidtová – Petra Lesníková ABSTRACT Controlling represents an essential tool for performance management and planning in industrial enterprises, particularly in the woodworking and furniture manufacturing sectors, which play a significant role in the Slovak economy. The aim of this study was to examine whether the extent of controlling tool usage (measured by the Return on Sales indicator) is affected by company performance influences, and whether the capital structure of companies relates to the complexity of their controlling reports. The research was conducted with a sample of 405 manufacturing companies in Slovakia, using a standardized questionnaire and structured interviews to examine the link between controlling practices and enterprise performance in this sector. The analysis included Pearson’s chi-square goodness-of-fit test, which was also part of the frequency analysis. The results confirmed statistically significant differences in the extent of controlling tool usage across sectors. Although hypothesis H1 concerning the relationship between performance and the scope of controlling was not statistically significant, the observed trend may not be entirely random, and its potential relevance could emerge with a larger research sample. Hypothesis H2 was confirmed: companies with foreign or mixed capital showed higher complexity in their controlling reports. The findings have practical implications for managers when deciding whether to expand their control tools. The study also lays the groundwork for further research into the connection between performance and controlling practices. Keywords: controlling, controlling tools, controlling report; performance, Return on Sales, woodworking industry, furniture manufacturing.

INTRODUCTION In the context of rapidly evolving markets and increasing competitive pressure, all enterprises face growing demands for adaptability, cost efficiency, and strategic decisionmaking. This trend also affects woodworking and furniture manufacturing enterprises, which have a long-standing tradition in the Slovak business environment and use a unique, domestically available renewable raw material. These enterprises must respond flexibly not only to fluctuations in input material prices and labor costs but also to changing customer expectations and sustainability requirements. In this environment, controlling emerges as a key managerial concept that supports the coordination of planning, monitoring, and performance evaluation (Eschenbach, 2004; Horvath, 2009; Reichmann, 2012; Kotapski, 2022). 141

Despite its growing importance, the concept of controlling is often misunderstood or narrowly interpreted, especially in practice, where it is sometimes confused with simple monitoring or cost supervision. This ambiguity may stem from the linguistic origin of the word “to control,” yet controlling as a managerial function encompasses a much broader strategic role. Historically, its development in Europe was influenced by post-war economic restructuring, particularly in German-speaking countries, where it was adapted from American business practice. Over time, controlling evolved into an independent managerial discipline, with significant differences between the American financial-accounting approach and the German cost-oriented perspective (Guenther, 2013; Pavlovska and KuzminaMerlino, 2013). While control focuses on reactive monitoring of standards, controlling emphasizes proactive planning and strategic direction. Robbins and Coulter (2018) define it as a process of monitoring, comparing, and correcting performance, while Tworek and Sałamacha (2019) highlight its role as a management-support tool. In the context of the outlined theoretical framework, it is appropriate to examine the specifics of controlling application in the woodworking and furniture manufacturing industry, which holds a distinctive position within the Slovak business environment. In the woodworking and furniture industry, controlling can be applied across various areas from cost management and investment planning to quality assurance and workforce optimization (Behúnová et al., 2022; Dobrovič et al., 2019; Agarwal and Chaudhry, 2022). However, the scope and depth of its application vary significantly among enterprises, influenced by internal factors such as organizational structure, capital composition, and performance orientation. The academic literature has yet to offer a clear classification framework linking controlling practices to enterprise performance in this sector. For example, the study by Sedliačiková et al. (2024) examined the use of various control tools in family and non-family businesses within the woodworking and furniture industry but did not specifically analyze their performance using financial indicators. In Europe, particularly in our regional context, the German approach to developing and applying controlling is more commonly adopted. Founders and proponents of the German model (Horvath, 2006; Eschenbach, 2004) describe controlling as a goal-oriented enterprise management system supported by secondary coordination, integrating planning, control, and information subsystems. Contemporary authors increasingly perceive controlling as qualified decision-making support (Schöning and Mendel, 2023; Behúnová et al., 2022; Kotapski, 2022), emphasizing its strategic and integrative function. Previous research has examined controlling tools across various industries. In logistics, strategic tools such as cost analysis and the Balanced Scorecard are emphasized (Reta et al., 2018). SWOT, GAP, and portfolio analyses are commonly used in manufacturing and commercial enterprises (Benzaghta et al., 2021), while Mazaraki and Fomina (2016) prefer tools based on managerial functions. Štefko et al. (2019) studied operational controlling in the tourism sector, where break-even analysis and bottleneck identification dominate. Lositska et al. (2022) highlight the use of benchmarking and profitability matrices in commercial enterprises. The diversity of tools reflects the complexity of controlling, influenced by investor know-how, managerial expertise, sector specialization, enterprise size, and especially the philosophy behind the application. According to Weber and Schäffer (2019), controlling has significantly advanced in recent decades, delivering measurable benefits in efficiency and competitiveness (Bienkowska, 2020). Research on the use of controlling tools in industrial enterprises is presented in studies by Potkany et al. (2022, 2024). Controlling reports play a key role in management and controlling itself, as they transform historical data into predictive information. They should include Key Performance Indicators (Gallo et al., 2024) and follow a plan–actual–deviation structure, with advanced versions incorporating 142

flexible planning. Deviations, defined as the difference between expected and actual outcomes, are central to evaluating enterprise performance (Fazal, 2022; Swapnil and Asma, 2019). Despite the importance of the topic, the literature only marginally addresses the impact of controlling complexity on enterprise performance. Some studies point to the significance of financial controlling for efficiency (Kozarevic and Vehabovic, 2020; Khudyakova et al., 2019), but broader empirical evidence is lacking (Vuko and Ojvan, 2013). The aim of this study is to examine whether statistically significant differences exist in the scope of controlling tools used among industrial enterprises operating in different sectors in Slovakia. Additionally, the study investigates whether the performance level of woodworking and furniture manufacturing enterprises, measured by the Return on Sales (ROS) indicator, serves as a classification factor for the practical application and complexity of controlling. The research specifically focuses on two dimensions: (1) the relationship between the range of controlling tools used and enterprise profitability, and (2) the link between capital structure and the sophistication of controlling reports. The study contributes to a deeper understanding of the role of controlling in enhancing decision-making quality and flexibility, as well as operational efficiency within this sector. At the same time, it seeks to systematically address a research gap, as the existing literature has not yet provided a comprehensive framework connecting enterprise performance with the practical use of controlling. This lack of a classification framework represents a challenge for empirical investigation of the link between enterprise performance and the practical application of controlling, which is also one of the main objectives of this study. The innovative aspect of the study lies in combining a quantitative approach to performance measurement with a qualitative analysis of controlling practices, creating space for new insights into managerial behavior in the woodworking and furniture manufacturing sector. Furthermore, the study lays the groundwork for future research and comparative analyses in the field of controlling, performance, and organizational design in industrial enterprises. The article is structured as follows: it begins with a review of relevant literature, followed by a methodological section outlining the research design, statistical procedures, and the formulation of the research question and hypotheses. The results are analyzed and discussed, and the final section provides a summary and recommendations for future research.

MATERIALS AND METHODS The research was conducted among manufacturing enterprises operating in the Slovak Republic, with a specific focus on the woodworking and furniture manufacturing industry. The selection of companies was purposeful, taking into account their technological advancement and competitive environment, which creates favorable conditions for the application of controlling tools. Particular attention was given to enterprises classified under NACE codes 16 (Manufacture of wood) and 31 (Manufacture of furniture), which represent the core of the study. Data collection took place from April to June 2025 through a standardized electronic questionnaire, supplemented by structured telephone interviews with representatives of selected companies. This combined approach helped increase the response rate while deepening the understanding of qualitative aspects of controlling practices. The research included small, medium, and large enterprises with more than 10 employees, located within the territory of the Slovak Republic. Company size categorization was based on the European Commission Recommendation No. 2003/361/EC (2003), while 143

industry classification followed NACE codes, Section C – Manufacturing. The target population was identified using data from the Statistical Office of the Slovak Republic, resulting in 3,585 manufacturing enterprises meeting the selection criteria. To calculate the minimum sample size with a maximum allowable error of 5%, the Taro Yamane method was used, which is suitable for research involving a finite population (Chanuan et al., 2021). The calculation is based on the following formula (1): 𝑁 𝑛 = 1+𝑁∙𝐸 2 (1) Where: n = required minimum sample size N = population size (3,585 enterprises), e = specified acceptable margin of error (0.05). Based on the quantification of variables and the application of formula (1), the minimum required sample size was determined to be 360 enterprises. A total of 405 enterprises participated in the research, which represents a sufficiently large sample given the size of the target population. To assess the representativeness of the research sample, the chi-square goodness-offit test was applied. This test is used to verify whether the distribution of empirical frequencies in the sample differs statistically significantly from the distribution in the population. The chi-square test statistic was applied according to Labudová et al. (2021), using formula (2): 𝜒2 = ∑

(𝑓0 −𝑓𝑒 )2

Where: f_0 = observed frequency, f_e = expected frequency.

𝑓𝑒

(2)

The chi-square test statistic was also applied to examine the investigated dependencies within the framework of contingency analysis, providing an informational basis for testing the stated hypotheses and addressing the defined research question. A commonly accepted 5% significance level was used as the decision rule in hypothesis testing. All calculations were performed using the statistical software STATISTICA 14, and tabular and graphical outputs were edited in Microsoft Excel 365. Company performance was measured using the Return on Sales (ROS) indicator, which represents a traditional, easily identifiable, and comparable financial metric across industries. ROS expresses business efficiency in relation to revenue and is particularly suitable for manufacturing enterprises, where the ratio between net profit and sales revenue is monitored. The formula for calculating ROS is as follows (Hayes, 2023): ROS = (Net Profit / Revenue) × 100

(3)

Based on the defined objective of the study and the current state of knowledge, the following research question (RQ1) and research hypotheses (H1–H2) were formulated: RQ: Are there statistically significant differences in the scope of controlling tools used among industrial enterprises operating in different sectors in Slovakia? H1: It is assumed that woodworking and furniture manufacturing enterprises that apply a broader range of controlling tools achieve higher performance, measured by the Return on Sales (ROS) indicator. H2: It is assumed that woodworking and furniture manufacturing enterprises with different capital structures exhibit statistically significant differences in the complexity of controlling reports. 144

RESULTS AND DISCUSSION The issue of controlling, particularly in relation to company performance and the complexity of its application, has not yet been sufficiently explored, at the international level or within the Slovak business environment. This study, therefore, addresses an identified research gap and provides empirical insights from manufacturing enterprises, with a focus on the wood processing and furniture production sectors. The analysis was based on a final dataset comprising a comprehensive information database of responses from 405 manufacturing companies, meeting the minimum sample size requirement at a maximum allowable error of 5%. The representativeness of the research sample was verified using Pearson’s chi-square goodness-of-fit test, based on a sectoral classification according to the SK NACE system. The test results confirmed (p level = 0.199) that the distribution of companies in the sample does not differ statistically significantly from the distribution across the entire sectoral population, allowing the research sample to be considered representative (Table 1). The percentage representation of individual sectors is shown in the column “Observed (Oi).” A similar approach was used to verify the sample's representativeness across company size categories. The research sample included 265 small, 108 medium-sized, and 32 large enterprises, of which 27 operated in the Manufacture of Wood sector and 20 in the Manufacture of Furniture sector. The test results (p level = 0.630) again confirmed that the distribution of companies by size in the sample corresponds to the distribution in the population, without statistically significant deviations (Table 2). These findings provide a methodological basis for further analysis of the relationship between company performance and the application of controlling tools. Tab.1 Results of the representativeness test according to NACE classification. Manufacturing sector Other manufacturing NACE 32 Manufacture of furniture NACE 31 Manufacture of motor vehicles NACE 29 Manufacture of motor vehicles NACE 28 Manufacture of electrical equipment NACE 27 Manufacture of computer products NACE 26 Manufacture of fabricated and metal NACE 24+25 Manufacture of other non-metallic mineral products NACE 23 Manufacture of rubber products NACE 22 Manufacture of basic pharmaceutical products NACE 21 Manufacture of chemicals NACE 20 Manufacture of paper and paper products NACE 17 Manufacture of wood NACE 16 Manufacture of leather and related products NACE 15 Manufacture of textiles and wearing apparel NACE 13+14 Manufacture of food products and beverages NACE 10+11 Total

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χ2 = 19.34 sv = 15 p = 0.199 Observed Expected (E-O)2 (/O) (Oi) (Ei) 10 8 0.500 20 13 3.769 20 21 0.048 32 35 0.2570 17 21 0.762 14 11 0.819 102 97 0.258 17 19 0.211 26 31 0.806 6 2 8.000 11 8 1.125 9 7 0.571 27 31 0.516 7 5 0.800 19 22 0.409 68 74 0.486 405 405 19.337

Tab. 2 Results of the representativeness test by enterprise size. Enterprise Size Large Medium Small Total

Observed (Oi) 32 108 265 405

χ2 = 0.91 sv =2 p = 0.630 Expected (Ei) 30 101 274 405

(E-O)2 (/O) 0.134 0.486 0.296 0.915

Research Question 1 (RQ1) sought to determine whether statistically significant differences exist in the extent of controlling tool use among industrial enterprises operating across various sectors in Slovakia. For analysis, the collected data were adjusted to enable classification of companies by the extent of their use of controlling approaches and tools. In this study, companies with a broader scope of implementation are defined as those applying at least two or more tools from the provided list: planning and variance analysis (plan vs. actual), cost consumption monitoring, quality and production volume control, product pricing, benchmarking, budgeting, and others. Companies using only one or none of these tools were classified into the lower-level controlling application category, that is, a narrower range of controlling approaches and tools. Figure 1 visualizes the intensity of controlling tool usage using quartile box plots by sector, classified according to the NACE code.

Fig. 1 Use of wider scale of controlling tools in industrial sectors classified by NACE code.

The highest proportion of companies was recorded in sector NACE 17 – Manufacture of paper and paper products, where 100% of enterprises reported using a broader range of controlling tools and approaches, such as planning and variance analysis (plan vs. actual), cost consumption monitoring, quality and production volume control, product pricing, benchmarking, and budgeting. These companies apply foreign know-how in their management practices, supported by a relatively precise system of reporting and budgeting. A similarly high proportion of broader controlling tool usage was observed in sector NACE 20 – Manufacture of chemicals (91%). Sectors such as NACE 26 – Manufacture of computer products, NACE 21 – Manufacture of basic pharmaceutical products, and especially NACE 29 – Manufacture of 146

motor vehicles, which constitutes a dominant part of Slovakia’s GDP, also showed noteworthy results. In this sector, the extent of controlling application was above average, reaching 70%. In the wood-processing industry sectors NACE 16 and NACE 31, the share of companies using at least two or more controlling tools (as specified in the methodological section above) was approximately 60%. Compared to previous research (Potkany et al., 2022), this represents a certain degree of progress, which is a positive signal for the future. In terms of implications, it can be assumed that these wood-processing sectors are likely to experience an increased level of technological modernization in the coming years, including the implementation of robotic systems, the digitalization of production processes, and the expansion of management information systems. This development will likely be accompanied by a growing need for the application of advanced controlling tools, which will be essential to support decision-making, planning, and effective management in a dynamically changing competitive environment. In most other sectors, more than 50% of companies were also observed to use a broader range of controlling tools, defined in the methodological section as the application of at least two or more tools from the provided list. In contrast, sectors with a lower proportion of companies applying a wider range of controlling tools included NACE 13+14 – Manufacture of textiles and apparel, with 21% of companies, and NACE 15 – Manufacture of leather and related products, with 25%. This situation may be influenced by a lower degree of automation, a higher share of manual labor, smaller company size, limited investment capacity, lower regulatory burden, and limited know-how in the area of controlling. Based on the results from the research sample, the significance of the observed differences between industrial sectors was tested in relation to the entire population of Slovak manufacturing companies. Table 3 presents the results of the contingency analysis. Based on the p-value (p = 0.003) corresponding to the calculated chi-square test statistic, it can be concluded that there are statistically significant differences between industrial sectors in Slovakia regarding the use of a broader range of controlling approaches and tools. The degree of dependence, expressed by the contingency coefficient, reached a value of 0.35, which can be interpreted as a moderate strength of relationship. Tab. 3 Results of the Chi-square test of significant differences in the use of controlling tools and aproaches across individual industrial sectors. Chi-square test

Degree of freedom

p-level

Contingency coefficient

56.13

0.000

0.35

The level of automation and informatization, higher investment capacity in information systems, and increased requirements for output standardization create favorable conditions for the systematic implementation of controlling tools and approaches. These tools serve not only to monitor costs and performance but also to support strategic decisionmaking, planning, and process optimization. In such sectors, controlling functions as an integrated management system that is essential for maintaining competitiveness and ensuring effective operations in a dynamic business environment. Supporting evidence for these claims can be found in the results of several independent studies, such as Poniščiaková et al. (2017), Kuzmynchuk et al. (2024), and Polyakova et al. (2023). In the context of Hypothesis H1, it was assumed that woodworking and furniture manufacturing enterprises applying a broader range of controlling tools would achieve higher performance, measured by the Return on Sales (ROS) indicator. The research 147

underlying this hypothesis was presented in studies by several authors (Horváthová and Mokrišová, 2017; Isibor et al., 2022). The relationship between the level of controlling tool implementation and company performance is illustrated by the bar chart in Figure 2. The performance of each enterprise was quantified using a ROS scale ranging from 0 to 1. Based on the graphical interpretation of the observed data, a quasi-positive trend was identified: 50% of companies with negative ROS values applied a broader range of controlling tools, followed by 58% and 71% of companies with increasing ROS levels (up to 1.5% and up to 5%), and reaching 100% in the group of companies with ROS values above 5%. From these findings, manufacturing enterprises with higher performance also showed a higher proportion of companies applying a broader range of controlling approaches and methods. Similar conclusions were reported by Sedliačiková et al. (2022) in a study focused on family businesses in the wood and furniture industries, which confirmed a positive relationship between the extent of controlling tool usage and company performance. Bazimya and Erorita (2024) also reached similar conclusions, analyzing the financial performance of manufacturing enterprises and stating that effective use of controlling leads to higher ROS. Likewise, Susanty et al. (2023) developed a simulation model for the furniture sector in Indonesia, which confirmed that controlling and sound decision-making enhance performance and sustainability during the pandemic.

Fig. 2 Use of controlling tools and approaches in wood and furniture manufacturing enterprises of with different level of ROS.

The observed trend was subsequently subjected to a statistical significance test. However, the statistical significance of the observed differences was not confirmed by the test results. The calculated p-value of p = 0.318 exceeds the defined 5% significance level of the test (Table 4). This conclusion can be attributed to the insufficient size of the empirical sample, as the hypothesis focused only on companies from two industrial sectors: NACE 31 – Manufacture of furniture and NACE 16 – Manufacture of wood and products of wood and cork, which led to a reduction in the amount of data included in the analysis. It is therefore reasonable to assume that expanding the research sample to include additional industrial sectors and increasing the number of analyzed companies could enhance the statistical robustness of the results and potentially confirm the validity of Hypothesis H1. 148

Including companies with varying levels of technological advancement, investment capacity, and managerial know-how would also allow for better identification of structural factors that influence the effectiveness of controlling tool application in practice. Tab. 4 Results of the Chi-square test of significant differences in the implementation of controlling tools and approaches across groups of manufacturing enterprises with different level of ROS. Chi-square test

Degree of freedom

p-level

Contingency coefficient

3.52

0.318

0.26

In the context of Hypothesis H2, it was assumed that companies in the woodworking and furniture manufacturing sectors with different capital structures exhibit statistically significant differences in the complexity of their controlling reports. The complexity of these reports was defined based on a synthesis of expert sources (Rajnoha, 2002; Däumler and Grabe, 2002; Pavković et al., 2022; Babaali, 2022), distinguishing three levels: 1. Basic structure – focused on retrospective analysis (e.g., plan vs. actual deviations) 2. Extended structure – includes a forward-looking dimension (forecasting) 3. Comprehensive structure – incorporates flexible budgeting and advanced analytical elements.

Fig. 3 Capital structure versus level of controlling report complexity in wood and furniture manufacturing enterprises.

For visualization purposes, Figure 3 also includes a fourth category, representing companies that do not use any controlling reports. The relationship between capital structure and the complexity of controlling reports in the research sample is illustrated in a 3D bar chart (Figure 3). The results of the chi-square test of dependence are presented in Table 5. The test confirmed statistically significant differences between groups of companies with different capital structures (p-value = 0.003; contingency coefficient = 0.48). The identified degree of dependence was evaluated as moderate. Tab. 5 Results of the Chi-square test of dependence between capital structure and level of complexity report in wood and furniture manufacturing enterprises. Chi-square test

Degree of freedom

p-level

Contingency coefficient

14.31

0.003

0.48

149

Based on the analysis of residual frequencies, it can be concluded that companies with mixed capital, especially those with a predominance of foreign capital, exhibit greater complexity in their controlling reports. These companies more frequently incorporate a future-oriented time dimension into their outputs, forecast monitored parameters, and transition to comprehensive structures with flexible budgeting. Hypothesis H2 was confirmed. Rajnoha (2002) presented the basic and extended structures of controlling reports within the temporal dimensions of the past and the future, highlighting their relationship to company performance. In a similar context, Däumler and Grabe (2002) emphasized the importance of a comprehensive structure in controlling reports. Pavković et al. (2022) confirmed that high-quality reporting based on Enterprise Resource Planning principles directly influences company performance, as measured by ROS and ROA indicators. An interesting finding was also reported by Jha and Kumar (2024), who examined the capital structure of Indian SMEs and found that financing type significantly affects ROA and ROE, which, in turn, impact controlling-related planning. Similar conclusions were drawn by Mansour et al. (2023), who analyzed companies in Jordan. The authors found that capital structure positively correlates with company performance, as measured by market share, with this relationship more pronounced in larger firms. This connection suggests that a more robust capital base can support more sophisticated controlling planning and reporting, particularly in the context of strategic decision-making. CONCLUSION The results of the study confirm that the extent of controlling tool usage differs statistically significantly across industrial sectors in Slovakia. Sectors with a higher degree of automation, digitalization, and investment capacity demonstrate more systematic application of controlling approaches, highlighting their importance in strategic management and process optimization. Although the hypothesis regarding the relationship between company performance (ROS) and the extent of controlling was not statistically confirmed, the observed trend suggests a potential connection that warrants further investigation. The findings also indicate that company performance may influence not only the scope of controlling tool usage but also its strategic essence. Hypothesis H2 was confirmed, companies with foreign or mixed capital structures exhibited greater complexity in their controlling reports, including elements of forecasting and flexible budgeting. These companies more frequently incorporate a future-oriented time dimension into their outputs, apply advanced analytical tools, and transition to comprehensive reporting structures. Capital structure thus plays a significant role in shaping the depth and quality of controlling outputs. Despite the robustness of the sample and the use of validated statistical methods, the study has certain limitations. The analysis focused exclusively on enterprises within two industrial sectors (NACE 16 and NACE 31), which may restrict the generalizability of the findings. Additionally, performance was measured using a single financial indicator (ROS), which, although suitable for manufacturing, does not capture broader dimensions such as operational efficiency or innovation capacity. Future research could benefit from incorporating additional performance metrics and expanding the sectoral scope to validate the observed trends. Expanding the research to include additional sectors with varying levels 150

of technological advancement, investment capacity, and managerial know-how could enhance statistical robustness and help identify structural factors that influence the effectiveness of controlling in practice. The study contributes to a deeper understanding of the role of controlling in improving decision-making quality and flexibility, as well as operational efficiency in the woodworking and furniture manufacturing industries. It also systematically addresses a research gap, as the existing literature has not yet provided a comprehensive framework linking company performance with the practical use of controlling. The innovative aspect of the study lies in its combination of a quantitative approach to performance measurement with qualitative analysis of controlling practices, creating space for new insights into managerial behavior. The findings also lay the groundwork for future research and comparative analyses in the areas of controlling, performance, and organizational design of industrial enterprises. These insights may serve as a basis for managers when making decisions about investments in controlling systems and when structuring capital to enhance company performance. Based on the findings, managers in woodworking and furniture manufacturing enterprises are encouraged to adopt a broader range of controlling tools, especially in areas such as cost monitoring, forecasting, and benchmarking. Enterprises with foreign or mixed capital structures may serve as examples of best practice in implementing more complex controlling reports. Investing in digital reporting systems and training in strategic controlling can enhance decision-making quality and improve overall performance. Managers should also consider aligning controlling practices with the specific needs of their organizational structure and market positioning REFERENCES Agarwal, A., Chaudhry, N., 2022. Foreign controlling shareholders and corporate investment. Journal of International Financial Markets, Institutions and Money 80(3). https://doi.org/10.1016/j.intfin.2022.101613 Babaali, A., Achour, F.Z., 2022. Impact evaluation of the internal control system on the sales function performance within Moroccan companies’ context. International Journal of Multidisciplinary Research and Analysis 5(2), 1–8. https://doi.org/10.47191/ijmra/v5-i2-02 Bazimya, S., Erorita, S.M., 2024. Analyzing the financial performance of manufacturing firms: a focus on return on equity, return on assets and return on sales. The International Journal of Humanities & Social Studies 12(6), 1–10. https://doi.org/10.24940/theijhss/2024/v12/i6/HS2406-005 Behúnová, A., Knapciková, L., Behún, M., 2021. Company controlling. Springer, Berlin. Benzaghta, M.A., Elwalda, A., Mousa, M.M., Erkan, I., Rahman, M., 2021. SWOT analysis applications: an integrative literature review. Journal of Global Business Insights 6(1), 55–73. https://doi.org/10.5038/2640-6489.6.1.1148 Bieńkowska, A., Tworek, K., Zabłocka-Kluczka, A., 2019. IT reliability and its influence on the results of controlling: comparative analysis of organizations functioning in Poland and Switzerland. Information Systems Management 37(1), 33–51. https://doi.org/10.1080/10580530.2020.1696545 Däumler, K.D., Grabe, J., 2002. Kostenrechnung 2, Deckungsbeitragsrechnung. 7th edn. Herne, Berlin. Dobrovič, J., Kmeco, L., Gallo, P., Gallo jr., P., 2019. Implications of the model EFQM as a strategic management tool in practice: a case of Slovak tourism sector. Journal of Tourism and Services 10(18), 47–62. https://doi.org/10.29036/jots.v10i18.91 Eschenbach, R., 2004. Controlling. ASPI Publishing, Praha. Fazal, H., 2022. What is meant by deviation from controls [WWW Document]. URL https://pakaccountants.com/what-is-meant-by-deviation-from-controls/

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This contribution is a part of the work on the project VEGA no. 1/0093/23 “Research of the potential of the circular economy in the Slovak business environment in the production of innovative products based on recycled materials wood - rubber – plastic“ and project VEGA no. 1/0111/26 Research on the potential of utilizing quality management approaches in industrial enterprises with a specific focus on the woodworking and furniture industry in the context of increasing their competitiveness. 153

AUTHORS’ ADDRESSES prof. Ing. Marek Potkány, PhD. Ing. Petra Lesníková, PhD. Technical University in Zvolen Faculty of Wood Sciences and Technology, Department of Economics, Mamagement and Business, T. G. Masaryka 24, 960 01 Zvolen, Slovakia potkany@tuzvo.sk lesnikova@tuzvo.sk Mgr. Jarmila Schmidtová, PhD. Technical University in Zvolen Faculty of Wood Science and Technology, Department of Mathematics and Descriptive Geometry T.G. Masaryka 24, 960 01 Zvolen, Slovakia jarmila.schmidtova@tuzvo.sk

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