{"title":"Experimenting the influence of corncob ash on the mechanical strength of slag-based geopolymer concrete","authors":"Jing Wang, Qian Qu, Suleman Ayub Khan, Badr Saad Alotaibi, Fadi Althoey, Yaser Gamil, Taoufik Najeh","doi":"10.1515/rams-2023-0187","DOIUrl":null,"url":null,"abstract":"The construction sector has been under growing public attention recently as one of the leading causes of climate change and its detrimental effects on local communities. In this regard, geopolymer concrete (GPC) has been proposed as a replacement for conventional concrete. Predicting the concrete’s strength before pouring is, therefore, quite useful. The mechanical strength of slag and corncob ash (SCA–GPC), a GPC made from slag and corncob ash, was predicted utilizing multi-expression programming (MEP). Modeling parameters’ relative importance was determined using sensitivity analysis. When estimating the compressive, flexural, and split tensile strengths of SCA–GPC with MEP, 0.95, 0.93, and 0.92 <jats:italic>R</jats:italic> <jats:sup>2</jats:sup>-values were noted between the target and predicted results. The developed models were validated using statistical tests for error and efficiency. The sensitivity analysis revealed that within the mix proportions, the slag quantity (65%), curing age (25%), and fine aggregate (3.30%) quantity significantly influenced the mechanical strength of SCA–GPC. The MEP models result in distinct empirical equations for the strength characteristics of SCA–GPC, unlike Python-based models, which might aid industry and researchers worldwide in determining optimal mix design proportions, thus eliminating unneeded test repetitions in the laboratory.","PeriodicalId":54484,"journal":{"name":"Reviews on Advanced Materials Science","volume":"20 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reviews on Advanced Materials Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1515/rams-2023-0187","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The construction sector has been under growing public attention recently as one of the leading causes of climate change and its detrimental effects on local communities. In this regard, geopolymer concrete (GPC) has been proposed as a replacement for conventional concrete. Predicting the concrete’s strength before pouring is, therefore, quite useful. The mechanical strength of slag and corncob ash (SCA–GPC), a GPC made from slag and corncob ash, was predicted utilizing multi-expression programming (MEP). Modeling parameters’ relative importance was determined using sensitivity analysis. When estimating the compressive, flexural, and split tensile strengths of SCA–GPC with MEP, 0.95, 0.93, and 0.92 R2-values were noted between the target and predicted results. The developed models were validated using statistical tests for error and efficiency. The sensitivity analysis revealed that within the mix proportions, the slag quantity (65%), curing age (25%), and fine aggregate (3.30%) quantity significantly influenced the mechanical strength of SCA–GPC. The MEP models result in distinct empirical equations for the strength characteristics of SCA–GPC, unlike Python-based models, which might aid industry and researchers worldwide in determining optimal mix design proportions, thus eliminating unneeded test repetitions in the laboratory.
期刊介绍:
Reviews on Advanced Materials Science is a fully peer-reviewed, open access, electronic journal that publishes significant, original and relevant works in the area of theoretical and experimental studies of advanced materials. The journal provides the readers with free, instant, and permanent access to all content worldwide; and the authors with extensive promotion of published articles, long-time preservation, language-correction services, no space constraints and immediate publication.
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