Experimental assessment on durability properties of fly ash aggregate concrete with SVM modelling
Concrete is one of the most synthesised material in the construction sector in which it has aggregate as one of its components. The use of natural aggregates in concrete preparation uses a significant amount of non renewable resources and energy, having a significant environmental impact. Numerous r...
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creator | Reddy, C. Ritvik Lalitha, G. |
description | Concrete is one of the most synthesised material in the construction sector in which it has aggregate as one of its components. The use of natural aggregates in concrete preparation uses a significant amount of non renewable resources and energy, having a significant environmental impact. Numerous research has been carried out in order to safeguard natural reserves, seeking a solution to the waste disposal issue, and reduce construction costs by utilizing waste materials. FA(Fly Ash) aggregate is one such material that can be a substitute for natural aggregate. The durability parameters of concrete with Fly Ash (FA) aggregate are investigated in this study as a substitute for natural fine aggregates. In this study, five concrete mixes were prepared utilizing FA aggregate in percentage substitution of 0%, 10%, 20%, 30%, and 40% for each. The quantity of cement, compaction, curing rate, concrete cover, and porosity all influence the durability of the concrete. Concrete properties such as compressive strength, resistance to abrasion and half cell potentials are investigated. Durability parameters of the specimens were tested after 90-day curing. The results revealed that concrete with 30% FA aggregate had the highest compressive strength, improved resistance towards abrasion and least half cell potential values. Experimentation data were used to develop comprehensive prediction models by applying support vector machine (SVM) algorithm. The SVM model analyses R2 values with an accuracy of over 97%. As a result, we can use SVM to efficiently execute prediction modelling in construction area. |
doi_str_mv | 10.1063/5.0161077 |
format | Conference Proceeding |
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Ritvik ; Lalitha, G.</creator><contributor>Nikhare, Chetan P ; Haider, Julfikar ; Singh, Swadesh Kumar ; Perveen, Asma ; Purohit, Rajesh</contributor><creatorcontrib>Reddy, C. Ritvik ; Lalitha, G. ; Nikhare, Chetan P ; Haider, Julfikar ; Singh, Swadesh Kumar ; Perveen, Asma ; Purohit, Rajesh</creatorcontrib><description>Concrete is one of the most synthesised material in the construction sector in which it has aggregate as one of its components. The use of natural aggregates in concrete preparation uses a significant amount of non renewable resources and energy, having a significant environmental impact. Numerous research has been carried out in order to safeguard natural reserves, seeking a solution to the waste disposal issue, and reduce construction costs by utilizing waste materials. FA(Fly Ash) aggregate is one such material that can be a substitute for natural aggregate. The durability parameters of concrete with Fly Ash (FA) aggregate are investigated in this study as a substitute for natural fine aggregates. In this study, five concrete mixes were prepared utilizing FA aggregate in percentage substitution of 0%, 10%, 20%, 30%, and 40% for each. The quantity of cement, compaction, curing rate, concrete cover, and porosity all influence the durability of the concrete. Concrete properties such as compressive strength, resistance to abrasion and half cell potentials are investigated. Durability parameters of the specimens were tested after 90-day curing. The results revealed that concrete with 30% FA aggregate had the highest compressive strength, improved resistance towards abrasion and least half cell potential values. Experimentation data were used to develop comprehensive prediction models by applying support vector machine (SVM) algorithm. The SVM model analyses R2 values with an accuracy of over 97%. As a result, we can use SVM to efficiently execute prediction modelling in construction area.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0161077</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Abrasion resistance ; Algorithms ; Compressive strength ; Concrete aggregates ; Concrete properties ; Construction costs ; Curing ; Durability ; Environmental impact ; Fly ash ; Mathematical models ; Modelling ; Nonrenewable resources ; Parameters ; Prediction models ; Substitutes ; Support vector machines ; Waste disposal</subject><ispartof>AIP Conference Proceedings, 2023, Vol.2754 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/acp/article-lookup/doi/10.1063/5.0161077$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,794,4512,23930,23931,25140,27924,27925,76384</link.rule.ids></links><search><contributor>Nikhare, Chetan P</contributor><contributor>Haider, Julfikar</contributor><contributor>Singh, Swadesh Kumar</contributor><contributor>Perveen, Asma</contributor><contributor>Purohit, Rajesh</contributor><creatorcontrib>Reddy, C. Ritvik</creatorcontrib><creatorcontrib>Lalitha, G.</creatorcontrib><title>Experimental assessment on durability properties of fly ash aggregate concrete with SVM modelling</title><title>AIP Conference Proceedings</title><description>Concrete is one of the most synthesised material in the construction sector in which it has aggregate as one of its components. The use of natural aggregates in concrete preparation uses a significant amount of non renewable resources and energy, having a significant environmental impact. Numerous research has been carried out in order to safeguard natural reserves, seeking a solution to the waste disposal issue, and reduce construction costs by utilizing waste materials. FA(Fly Ash) aggregate is one such material that can be a substitute for natural aggregate. The durability parameters of concrete with Fly Ash (FA) aggregate are investigated in this study as a substitute for natural fine aggregates. In this study, five concrete mixes were prepared utilizing FA aggregate in percentage substitution of 0%, 10%, 20%, 30%, and 40% for each. The quantity of cement, compaction, curing rate, concrete cover, and porosity all influence the durability of the concrete. Concrete properties such as compressive strength, resistance to abrasion and half cell potentials are investigated. Durability parameters of the specimens were tested after 90-day curing. The results revealed that concrete with 30% FA aggregate had the highest compressive strength, improved resistance towards abrasion and least half cell potential values. Experimentation data were used to develop comprehensive prediction models by applying support vector machine (SVM) algorithm. The SVM model analyses R2 values with an accuracy of over 97%. As a result, we can use SVM to efficiently execute prediction modelling in construction area.</description><subject>Abrasion resistance</subject><subject>Algorithms</subject><subject>Compressive strength</subject><subject>Concrete aggregates</subject><subject>Concrete properties</subject><subject>Construction costs</subject><subject>Curing</subject><subject>Durability</subject><subject>Environmental impact</subject><subject>Fly ash</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Nonrenewable resources</subject><subject>Parameters</subject><subject>Prediction models</subject><subject>Substitutes</subject><subject>Support vector machines</subject><subject>Waste disposal</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkFFLwzAUhYMoOKcP_oOAb0JnbpumzaOMOYWJDw7xraTpTZfRtTXJ0P17M7aney583HPuIeQe2AyYyJ7yGQMBrCguyATyHJJCgLgkE8YkT1KefV-TG--3jKWyKMoJUYu_EZ3dYR9UR5X36P1xoUNPm71Tte1sONDRDRELFj0dDDXdIaIbqtrWYasCUj302mEUvzZs6OfXO90NDXad7dtbcmVU5_HuPKdk_bJYz1-T1cfybf68SkYpYkzIjM7BcFBSmKJGwzVDUKY2KdeqkbUGjg1kOmdMYKlTSBujeYlSImcmm5KH09kY9WePPlTbYe_66FilpWCyLCDNIvV4ory2QQU79NUYv1fuUAGrjg1WeXVuMPsHpHFk0w</recordid><startdate>20230905</startdate><enddate>20230905</enddate><creator>Reddy, C. Ritvik</creator><creator>Lalitha, G.</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230905</creationdate><title>Experimental assessment on durability properties of fly ash aggregate concrete with SVM modelling</title><author>Reddy, C. Ritvik ; Lalitha, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p961-713fc51f41a96f7bef4c0e1afbf24cad9bc14ed13c5006e8c212dfc48e99e40f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Abrasion resistance</topic><topic>Algorithms</topic><topic>Compressive strength</topic><topic>Concrete aggregates</topic><topic>Concrete properties</topic><topic>Construction costs</topic><topic>Curing</topic><topic>Durability</topic><topic>Environmental impact</topic><topic>Fly ash</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>Nonrenewable resources</topic><topic>Parameters</topic><topic>Prediction models</topic><topic>Substitutes</topic><topic>Support vector machines</topic><topic>Waste disposal</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reddy, C. Ritvik</creatorcontrib><creatorcontrib>Lalitha, G.</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reddy, C. Ritvik</au><au>Lalitha, G.</au><au>Nikhare, Chetan P</au><au>Haider, Julfikar</au><au>Singh, Swadesh Kumar</au><au>Perveen, Asma</au><au>Purohit, Rajesh</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Experimental assessment on durability properties of fly ash aggregate concrete with SVM modelling</atitle><btitle>AIP Conference Proceedings</btitle><date>2023-09-05</date><risdate>2023</risdate><volume>2754</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Concrete is one of the most synthesised material in the construction sector in which it has aggregate as one of its components. The use of natural aggregates in concrete preparation uses a significant amount of non renewable resources and energy, having a significant environmental impact. Numerous research has been carried out in order to safeguard natural reserves, seeking a solution to the waste disposal issue, and reduce construction costs by utilizing waste materials. FA(Fly Ash) aggregate is one such material that can be a substitute for natural aggregate. The durability parameters of concrete with Fly Ash (FA) aggregate are investigated in this study as a substitute for natural fine aggregates. In this study, five concrete mixes were prepared utilizing FA aggregate in percentage substitution of 0%, 10%, 20%, 30%, and 40% for each. The quantity of cement, compaction, curing rate, concrete cover, and porosity all influence the durability of the concrete. Concrete properties such as compressive strength, resistance to abrasion and half cell potentials are investigated. Durability parameters of the specimens were tested after 90-day curing. The results revealed that concrete with 30% FA aggregate had the highest compressive strength, improved resistance towards abrasion and least half cell potential values. Experimentation data were used to develop comprehensive prediction models by applying support vector machine (SVM) algorithm. The SVM model analyses R2 values with an accuracy of over 97%. As a result, we can use SVM to efficiently execute prediction modelling in construction area.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0161077</doi><tpages>14</tpages></addata></record> |
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source | AIP Journals |
subjects | Abrasion resistance Algorithms Compressive strength Concrete aggregates Concrete properties Construction costs Curing Durability Environmental impact Fly ash Mathematical models Modelling Nonrenewable resources Parameters Prediction models Substitutes Support vector machines Waste disposal |
title | Experimental assessment on durability properties of fly ash aggregate concrete with SVM modelling |
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