Review on Optimization of Concrete Mix Proportion by IRJET Journal

Review on Optimization of Concrete Mix Proportion

Anjali

Dewangan1 , Pranali Misar2, Adity Sahare3 , Shriniwas Rayadu4

1U.G. Student, Department of Civil Engineering, KITS, Ramtek Maharashtra, India

2U.G. Student, Department of Civil Engineering, KITS, Ramtek Maharashtra, India

3U.G. Student, Department of Civil Engineering, KITS, Ramtek Maharashtra, India

4Assistant Professor, Department of Civil Engineering, KITS, Ramtek Maharashtra, India

Abstract - The optimization of concrete mix design using locallyavailablematerialsplaysacrucialroleinenhancing the sustainability, cost-efficiency, and environmental impact of construction projects. This study explores the potential of using locally sourced materials such as sand, aggregates, and cement to develop an optimized concrete mixthatmeetsrequiredstrengthanddurabilitystandards while minimizing material costs and environmental footprint. The research focuses on determining the optimal proportions of these materials through experimental trials and statistical analysis, incorporating factors such as compressive strength, workability, and long-term performance. By utilizing locally available materials, the study aims to reduce transportation costs and carbon emissions associated with the production and delivery of materials. This approach promotes resource conservation and contributes to the overall sustainability ofconstructionpracticesintheregion.Theresultsindicate that with proper adjustments, locally available materials can effectively replace more expensive or imported alternatives, leading to cost-effective and eco-friendly concretemixdesignswithoutcompromisingperformance.

Key Words: Concrete mix design, Optimization, Locally availablematerials,Sustainableconstruction,Compressive strength, Workability, Cost-efficiency, Environmental impact,Resourceconservation,Durability.

1. INTRODUCTION

Concrete is one of the most widely used construction materials in the world due to its versatility, strength, and durability. However, the environmental and economic impacts of concrete production, particularly the sourcing andtransportationofmaterials,aresignificant.Traditional concretemixdesignsoften relyon materialsthatmaynot be locally available, leading to increased costs, energy consumption, and carbon emissions associated with transportation. Optimizing concrete mix design using locally available materials has gained attention as a sustainable solution to these challenges. By incorporating materials such as locally sourced aggregates, sand, and cement, construction projects can reduce both material costsandtheenvironmentalfootprint.Theavailabilityand characteristics of these materials, however, can vary regionally, making it essential to develop tailored mix

designs that meet specific performance criteria such as compressivestrength,durability,andworkability.

Thisreviewpaperexploresthemethodsandstrategiesfor optimizing concrete mix design using locally available materials.Itexaminesthebenefitsofusinglocalresources, including reduced costs, improved sustainability, and enhanced project feasibility, while also addressing potential challenges such as variations in material quality and performance. By reviewing recent studies and practical applications, this paper aims to provide insights into the effectiveness of local material usage and offer guidelines for achieving optimal concrete mix designs tailored to regional conditions. The research also highlights the broader implications of adopting locally sourced materials in promoting sustainable constructionpractices.

2. LITERATURE REVIEW

[1] Ikponmwosa, et.al. (2023) investigated the production of high-performance concrete using local materials, examining the effects of varied water-cement ratios (0.3, 0.35, and 0.4) and coarse aggregate particle sizes on concrete workability and strength. Twelve concrete mixes were tested for slump, compressive, flexural, and tensile strength at various curing ages. Results showed that increasing water-cement ratio and aggregateparticlesizereducedstrength, whilea mixwith 0.3 water-cement ratio and 10 mm coarse aggregate achieved the highest strength (52.22 N/mm² at 28 days). Statisticalmodelswereproposedtopredictthestrengthof the optimal mix, concluding that high performance concrete can be produced using local materials with propermixoptimization.

[2] Nilvan T. Araulo, et. al. (2021) have developedhighstrength alkali-activated slag concrete (HSAASC) using ground granulated blast furnace slag and sodium silicate solution as the binder, employing the IPT/EPUSP mix designmethod.TestsrevealedthatHSAASCachievedhigh compressive strengths of 41-58 MPa at 1 day and 86-105 MPa at 28 days, along with favorable dynamic and static modulus of elasticity and splitting tensile strength. The study demonstrates the suitability of the IPT/EPUSP method for producing HSAASC, offering a promising

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alternativetoPortlandcementconcretewithpotentialfor efficientandsustainableconstructionpractices.

[3] Carolina Londero, et.al. (2021) stated that the Cement production is a significant contributor to global carbon emissions, accounting for approximately 7% of CO2 emissions. To mitigate thisimpact,variousstrategies have been proposed, including the development of environmentally sustainable concrete mixtures through partial replacement of cement with mineral admixtures. Recent studies have focused on using particle packing techniques in the design of low-cement concrete (LCC) to optimizematerialuseand minimizecementconsumption. By incorporating materials such as rice husk ash and quartz powder, these methods aim to fill voids in the concrete matrix, thereby improving material efficiency and reducing environmental impact. In a specific study, a mix-design method based on cyclic interactions between particle 4 packing, water demand, and compressive strength prediction was employed to create LCC. The study achieved a 40% reduction in cement usage, leading toafinalconsumptionof164kgofcementpercubicmeter of concrete. The properties of the LCC were evaluated in both fresh and hardened states, with the concrete demonstrating satisfactory performance, including compressivestrengthof31MPaandtensilestrengthof2.9 MPa at 28 days. This indicates the potential of particle packing techniques to produce sustainable concrete with reduced cement content while maintaining acceptable structuralproperties.

[4] Dr. P. Vinayagam (2021) presented a simplified approach to desig High-Performance Concrete (HPC) by integrating methods from both the US and ACI (American Concrete Institute) codes for mix design, along with insights gathered from existing literature on HPC. The main goal is to streamline the process of designing HPC mixes by using a combination of these established methods. As part of the study, two different HPC mixes, labeledMBandM1588,wereexperimentallytested.These mixeswereevaluatedforkeyperformanceindicatorssuch as compressive strength, split tensile strength, flexural strength,andworkability.Thepaperreportsontheresults oftheseexperiments,providinganoverviewofhowthese mixesperformedundervarioustests.

Inadditiontoperformancetesting,thestudyalsoexplored the durability characteristics of the HPC that was developed through this process. These durability features arecriticalforensuringthelong-termsustainabilityofthe concrete in different environmental conditions. The mix designs presented in the paper are still in progress, suggesting that the development of HPC mixtures is an ongoing process, with future adjustments and improvementsexpectedasthestudycontinues.

[5] Anita Jose & Karthick B, et.al. (2020) developed high-performanceconcrete(HPC)usingsilicafume,flyash,

and glass powder, which offer enhanced durability, impermeability, and resistance to chemical attack. The experiment aimed to utilize these waste materials to create M60 grade concrete, evaluating properties like compressive strength, split tensile strength, flexural strength,workability,anddurabilityat7and28days.The results demonstrate the potential of these materials in producing HPC with improved performance and reduced carbondioxideemissions,aligningwiththegrowingglobal awarenessofsustainableconstructionpracticesandwaste materialutilization.

[6] Alaa A. Bashandy, et. al (2017) investigated the behavior of High-Performance Concrete (HPC) incorporating silica fume (SF) and fly ash as mineral admixtures. Seven mix designs (M1-M7) were cast with varying SF replacement levels (0%, 5%, 7.5%, and 10%) andconstant10%flyashreplacement,aimingforatarget strengthof80MPa.Theconcrete'smechanicalproperties, includingcompressivestrength,splittensilestrength, and flexural strength, were evaluated at 7 and 28 days. The study examined the effect of SF and fly ash on HPC's performance, providing insights into optimizing mix designsforimprovedstrengthanddurability.

[7] Dr. S. U. Kannan. (2017) carried experimental study on the behavior of High-Performance Concrete (HPC) when silica fume and fly ash are used as partial replacements for cement. HPC in this investigation was produced using standard materials, including Pozzolanic cement,fineaggregate(sand),coarseaggregate(gravel or crushed stone), potable water, and various admixtures. Bothmineralandchemicaladmixtureswereincorporated, with Silica Fume (SF) and Fly Ash being used at different replacementlevels,incombinationwithaSuperplasticizer toimprove workability. The water-cement ratio(w/c)for all mixes was kept constant at 0.30, which is typical for high-strength concrete, as a lower w/c ratio generally increasesthestrengthand durabilityofconcrete.Theaim of this research was to explore how different proportions ofSilicaFumeandFlyAshaffectthemechanicalproperties of HPC. Specifically, seven different concrete mixes, denoted as M1 through M7, were prepared. These mixes targetedameancompressivestrengthof60MPa.

Inthesemixes,SilicaFumewasreplacedat0%,5%,7.5%, and 10% levels, while the Fly Ash replacement was kept constantat10%throughout.Themechanicalpropertiesof theconcretewereevaluatedbycastingandtestingvarious specimens, including cubes, cylinders, and prism beams. These specimens were tested for compressive strength, tensile strength, and flexural strength to determine how the inclusion of Silica Fume and Fly Ash at different replacementlevelsaffectedtheoverallperformanceofthe concrete. The primary goal of the investigation was to assess the optimal proportion of Silica Fume and Fly Ash that could enhance the strength and durability of HPC without compromising its workability or other important

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properties. By testing a range of mixes, the researchers aimedtofindthebestcombinationofmaterialsthatwould yield the highest performance for high-strength constructionapplications.

[8] Patil S. (2016) investigated the mix design of highperformance concrete (HPC) using various combinations of VSI coarse aggregate, VSI crushed sand, Parzocrete-60 fly ash, and Microsilica 920 D. Twenty-seven trial mixes were conducted with varying percentages of cement replacement (25%, 30%, and 35%) and fly ash replacement (5% and 10%). The study aimed to achieve targeted strength (M-80) and involved aggregate proportioning, water content, and slump optimization. Cubical and cylindrical specimens were tested for compressive strength and permeability at 28 days. The results5werethoroughlyanalyzedtoidentifytheoptimal mix design for HPC, providing insights into the effects of different materials and proportions on concrete performance.

[9] Hengchun Zhang, et. al. (2015) discussedcrucialrole of Mix design in the production and application of highperformance concrete (HPC). Several methods have been developed to optimize the mixture for HPC, each with its ownstrengthsandweaknesses.Areviewofthesemethods highlights the importance of selecting the right design approach based on specific project requirements. Some methods offer simplicity but may lack precision, while others are more complex and tailored for specialized applications. As construction demands grow, there is a clear trend toward using computerized tools and standardizationtostreamlinethedesignprocess,ensuring consistent,high-qualityHPCwiththedesiredproperties.

[10] Sudarsana Rao. Hunchate, et. al. (2014) investigated use of High Performance Concrete (HPC) using globally, leveraging mineral admixtures like silica fume,flyash,andmetakaolin,alongwithsuperplasticizers, toenhancestrengthanddurability.Thisstudyinvestigates theoptimaluseofsilicafume(0,5,10,15,20,and25%)in HPC, examining compressive strength at 7 and 28 days of curing.TheresearchaimstodevelopadesignmixforHPC using silica fume and superplasticizers, exploring the potential for improved performance and sustainability in constructionapplications.

[11] Shamsad Ahmad and Saeid A. Alghamdi (2014) proposed step-by-step statistical approach to optimize concretemixtureproportioningusingdatafromaplanned experimental program. A full factorial experiment design (3^3) was conducted, considering 27 concrete mixtures with three replicates (81 specimens), varying water/cementitious materials ratio, cementitious materials content, and fine/total aggregate ratio. Analysis ofvariance(ANOVA)andpolynomialregressionmodeling were performed to develop a statistical model for compressive strength. The model was used to

demonstrate optimization of concrete mixtures, showcasing the approach's utility in identifying optimal proportioning for desired compressive strength, and highlighting its potential for efficient and effective concretemixdesign.

[12] Rama Shanker & Anil Kumar Sachan (2014) studied Traditional concrete mix design methods, based on empirical relationships, having limitations such as uncertain strength attainment, cumbersome calculations, and reliance on multiple tables. To address these drawbacks, researchers have employed Artificial Neural Networks (ANNs) to optimize mix design. By training ANNswithdatasetsofstandardgradeconcretecubesand their 28-day strength, the networks can predict optimal proportions of cement, fine aggregate, coarse aggregate, andwaterbasedoninputparameterslikeconcretegrade, cement type, and aggregate characteristics. Validation of theseANNshasshownmaximumerrorsof4-5%,enabling rapid and accurate evaluation of mix proportions for specific material properties, offering a promising alternativetotraditionalmethods.

[13] S. A. A. M. Fennis, et. al (2013) introduces a cyclic design method that uses particle packing technology to estimate concrete strength. First, water content is determined based on the desired workability and calculatedpackingdensity.Then,themixture’sstrengthis predicted using the cement spacing factor. The process repeatsuntilthemixturemeetstherequiredstrength.This methodallowsfora57%reductionincement use,cutting CO2 emissions by 25%, as confirmed by tests on compressive and tensilestrength. Concrete's energy consumption and CO2 emissions can be lowered by replacing cement with industrial by-products. To design eco-friendly concrete, accurately predicting its performanceiscrucial.

[14] Laskar A. I. (2011) developed novel mix design procedure for high-performance concrete (HPC) has been proposed,focusingonthecorrelationbetweenrheological parameters (yield stress and plastic viscosity) and compressive strength. Unlike traditional methods using water-cement ratio versus compressive strength, this approach utilizes rheological behavior to determine water-cementratioandaggregatevolumetopastevolume ratio. The designer can estimate rheological parameters and ingredients at the design stage for a target strength, enablinga moreaccurateandefficientmixdesignprocess for HPC. This approach offers a promising alternative to traditional mix design methods, potentially leading to improved concrete performance and reduced trialanderrorprocesses.

[15] S.A.A.M. Fennis & J.C. Walraven (2008) studied particle packing models based on geometric principles which plays a significant role in predicting the water demand in concrete and directly influences its material

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properties. This paper explores how centrifugal consolidation can be employed to accurately measure the packing density of powdered materials used in concrete mixtures. The effectiveness of this method is evaluated throughacombinationofexperimentaldata,mathematical calculations, and microscopic techniques such as polarizationandfluorescencemicroscopy.

The findings reveal that the maximum packing density of particles can be consistently measured, though this value is influenced by several factors. Key among these are the initial ratio of water to powder, the use of additives such assuperplasticizers, the specific mixing proceduresof the paste, and the amount of compaction energy applied. The study also includes viscosity measurements, which demonstrate how the particle packing density affects the overallwaterdemandoftheconcretemix.

Byunderstandingandcontrollingthepackingdensity,itis possibletodesignconcretemixtureswithreducedcement contentwithoutcompromisingthematerial'sperformance. This not only lowers the water demand but also contributes to more sustainable and efficient concrete production methods. Through careful manipulation of these variables, the study shows that concrete mixtures can be optimized, leading to stronger, more durable, and environmentallyfriendlystructures.

[16] I-Cheng Yeh (2006) developed A Computer-Aided Design (CAD) system utilizing neural networks and optimization technologies to search the optimal concrete mixture with the lowest cost and required performance, including strength and slump. The system integrates modeling and optimization modules, using nonlinear programming and genetic algorithms, to solve the optimization formulation. The CAD system was validated by obtaining a set of optimum concrete mixtures with varying workability (15- 25 cm slump) and strength (2555MPacompression).Resultsshowedthatthesystemcan generateaccuratemodelsforstrengthandslump,identify low-costmixturesforawiderangeofrequiredproperties, and demonstrate expected dependencies between required strength, slump, and design parameters, showcasingitspotentialforefficientandeffectiveconcrete mixdesign.

[17] Francois de Larrard and Thierry Sedran (2002)

The paper introduces an innovative method for designing concrete mixtures that integrates a comprehensive set of models. These models aim to establish a relationship between the composition of the concrete and its key engineering properties. By utilizing specialized software linkedtoadatabaseofmaterials,thisapproachallowsfor more efficient and targeted design processes. The paper outlines the core principles behind the various models, most of which center around the granular structure of both fresh and hardened concrete. The proposed methodologyadvocatesforaholisticapproachtoconcrete,

addressing its performance at different stages: fresh, hardening,andhardenedconcrete.Forfreshconcrete,the performance can be defined by parameters such as yield stress, plastic viscosity, slump, and air content. When it comes to hardening concrete, key characteristics include adiabatictemperatureriseandautogenous shrinkage.For thefinal,hardenedconcrete,themodelspredictimportant properties like compressive strength at any given age, tensilestrength, elasticmodulus,aswell astheconcrete's behaviorovertimeintermsofcreepandshrinkage.

One of the key examples highlighted in the paper is the design of a high-performance concrete (HPC) specifically tailored for road applications, where high shrinkage is a critical factor. This demonstrates the flexibility and potential of the approach in addressing specific performance requirements for different uses. However, the current models fall short in addressing all aspects of concrete durability. The paper emphasizes that further research is needed to incorporate durability considerations into these models to ensure a more complete and long-lasting solution for concrete design. This new approach to concrete mixture design presents a forward-thinking framework, promoting performancebasedspecificationsthatcanbefine-tunedforavarietyof applications. By focusing on both the fresh and hardened states of the material, it offers a more dynamic and adaptablewaytomeetthegrowingdemandsinthefieldof concreteengineering.

[18] I-Cheng Yeh (1999) introduced methodology for optimizing high-performance concrete mix proportioning using artificial neural networks and nonlinear programming. The approach involves building accurate models for workability and strength using experimental data, incorporating these models into software for evaluating specified properties, and using nonlinear programming to search for the optimum mix design. A software package has been developed to perform mix simulations covering all important concrete properties simultaneously. Experimental results demonstrate the utility of this methodology in achieving optimal mix designs based on various design requirements, showcasingitspotentialforefficientandeffectiveconcrete mixproportioning.

5. CONCLUSIONS

Optimizing concrete mix design using locally available materials is a crucial endeavor that can significantly enhance the sustainability, cost-effectiveness, and overall performance of concrete in construction projects. As urbanization and infrastructure development continue to accelerate globally, the demand for high-quality concrete remains ever-present. However, the traditional approach toconcretemixdesignoftenreliesonimportedmaterials, whichcanleadtoincreasedcosts,environmentalimpacts, and logistical challenges. By leveraging locally available

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materials, construction professionals can not only reduce reliance on external sources but also tap into the unique properties of these materials to create more resilient and efficientconcretemixes

One of the primary benefits of utilizing local materials is the potential for cost savings. Locally sourced aggregates, supplementary cementitious materials, and additives can significantlylowertransportationcosts,reducethecarbon footprint associated with material logistics, and support the local economy. Moreover, optimizing the mix design with these materials allows for greater flexibility and innovation. For example, the use of local waste materials, such as fly ash, slag, or recycled aggregates, can enhance the performance characteristics of concrete while simultaneously addressing waste management issues in the region. This not only contributes to sustainable construction practices but also aligns with global efforts towardcirculareconomyprinciples.

Furthermore, optimizing concrete mix design with locally available materials necessitates a comprehensive understandingoftheirpropertiesandbehavior.Itrequires rigorous testing and evaluation to determine the optimal proportionsthatwillachievedesiredstrength,workability, durability, and other performance metrics. This approach fosters collaboration between researchers, material suppliers, and construction professionals, leading to a knowledge-sharingenvironmentthatenhancesinnovation and best practices. Additionally, local universities and research institutions can play a pivotal role in advancing thisfield byconductingstudiesanddevelopingguidelines tailoredtospecificregionalconditionsandmaterials.

In conclusion, the optimization of concrete mix design using locally available materials represents a transformative strategy in the construction industry. By embracing locally sourced inputs, we can achieve more sustainable, economical, and high-performance concrete solutions that address the pressing challenges of modern construction. This practice not only contributes to environmental conservation and resource efficiency but also empowers communities by fostering local economies and promoting innovation. As the construction industry continues to evolve, prioritizing the optimization of concrete mix designs with locally available materials will be essential in creating a resilient infrastructure that meetstheneedsoffuturegenerations.

REFERENCES

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[2] Nilvan T. Araulo, et. al. (2021). "Experimental Investigation of mix design for highstrength alkali-

activated slag concrete", Construction and building materials.www.elsevier.com,/locate/conbuildmat

[3] Carolina Londero, et al. (2021) "Study of low-cement concretemix-designthroughparticlepackingtechniques", Journal of Building Engineering.www.elsevier.com/locate/jobe.

[4] Dr. P. Vinayagam (2021) “Experimental Investigation on High Performance Concrete Using Silica Fume and Superplasticizer”, Internatinal Journal of Science, Engineering and Management (IJSEM) Vol 6, Issue 2, Februaryn2021

[5] Anita Jose & Karthick B. (2020) "Experimental investigation on High Performance concrete using silica fume, fly ash and glass powder", International Research JournalofEngineeringandTechnology(IRJET).

[6] Alaa A. Bashandy, et al. (2017) "Recycled Aggregate Self-curing High-strength Concrete", Civil Engineering Journal,Volume10,Issue9

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[9] Hengchun Zhang, et. al. (2015) “Mixture design methods or high performance concrete” 5th International Conference on Advanced Engineering Materials and Technology(AEMT2015)

[10] Sudarsana Rao. Hunchate, et. al. (2014) "Mix Design of High Performance Concrete Using Silica Fume and Superplasticizer", International Journal of Innovation ResearchinScienceEngineeringandtechnology,Volume3, Issue3.

[11] Shamsad Ahmad and Saeid A. Alghamdi, (2014) "A Statistical Approach to Optimizing Concrete Mixture Design", The Scientific World Journal, Volume 2014, ArticleID:561539,Pages7.

[12]S.A.A.M.Fennis, et.al (2013)“Defined-performance design of ecological concrete” RILEM 2012, DOI 10. 1617/s11527-012-9922-2

[13] Wakchaure, M. R., & Gite, B. R. (2012). "Optimization ofmixproportioningforsustainableconcreteusinglocally available materials." International Journal of Civil and StructuralEngineering,3(3),620-627.

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[14] Aminul Islam Laskar, (2011) "Mix Desigen of HighPerformance Concrete", National Institute of Technology, Silchar-788010,India.

[15] S.A.A.M. Fennis & J.C. Walraven (2008) “Measuring the packing density to lower the cement in concrete”, Tailor Made Concrete Srtucture - Walraven & Stoelhorst (eds) @ 2008 Taylor & FrancisGroup, London, ISBN 9780-415-47535-8.

[16] I-Cheng Yeh. (2007) "Computer aided designs for optimum concrete mixtures", ELSEVIER ScienceDirect, Volume29,Issue3.

[17] Francois de Larrard and Thierry Sedran (2002) “Mixture-Proportioning of High-Performance Concrete”, Cwment and Concrete Research 32 (2002) 1699-1704, Laboratoire Central des Ponts et Chaussees - Centre de Nantes, Route de Bouaye, BP 4129 44 341 Bouguenais CedexFrance.

[18] I-Cheng Yeh. (1999), "Desigen of High-Performance Concrete Mixture Using Neural Networks and Nonlinear Programming", Journal of Computing in Civil Engineering /January1999,Vol:8,No:8,2014