Data-driven based estimation of waste-derived ceramic concrete from experimental results with its environmental assessment

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dc.contributor.authorChang, Qiuying
dc.contributor.authorLiu, Lanlan
dc.contributor.authorFarooqi, Muhammad Usman
dc.contributor.authorThomas, Blessen
dc.contributor.authorOzkilic, Yasin Onuralp
dc.date.accessioned2024-02-23T14:12:52Z
dc.date.available2024-02-23T14:12:52Z
dc.date.issued2023
dc.departmentNEÜen_US
dc.description.abstractThe significant requirement for natural resources, specifically as ingredients of cement, is accelerating due to the considerable growth of the construction sector. Further, cement production adversely affects climate change due to the generation of bulk CO2 emissions. At the same time, a significant quantum of ceramic waste is generated either in the ceramic production process or due to the demolition of ceramic products each year. The unavailability of an adequate way to dispose of this ceramic waste negatively impacts the environment and landfills. Numerous researchers have explored the potential of utilizing this ceramic waste powder as a partial cement replacement to reduce the allied issues. Hence, in the current study, the supervised machine learning (ML) algorithms, i.e., Decision Tree (DT), AdaBoost (AdB), Bagging (Bg), Random Forest (RF), Gradient Boosting (GB) and XGBoost (XGB) are employed for predicting the Compressive Strength (CS) of ceramic waste powder concrete (CWPC). The performance of models is also assessed by using the coef-ficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Nash Sutcliffe efficiency (NSE). The k-fold cross-validation technique is applied af-terwards to validate the model's performance. For predicting the CS of CWPC, the RF al-gorithm is the most effective among the employed algorithms, with a higher R2 value of 0.97 and significantly lesser RMSE and MAE values of 1.40 and 1.13, respectively. SHAP analysis shows that the curing days feature has the highest influence on the CS of CWPC. As per quantitative Environmental Impact Assessment (EIA), the concrete with 10% CWP content can have 6.78%, 8.68%, 7.18%, and 7.19% reduced impacts on natural resources, climate change, ecosystem quality, and human health, respectively. Moreover, the effects on non-renewable energy resources, depletion of the ozone layer, and global warming can also primarily be reduced by a maximum of 7%, 6%, and 9%, respectively. The application of ML techniques for estimating the CS of CWPC would benefit the field of civil engineering in terms of conserving resources, effort, and time.& COPY; 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.description.sponsorship2023 Scientific research projects of the Education Department of Jilin Province of China [JJKH20231486KJ]en_US
dc.description.sponsorshipThis work was sponsored in part by 2023 Scientific research projects of the Education Department of Jilin Province of China (JJKH20231486KJ) .en_US
dc.identifier.doi10.1016/j.jmrt.2023.04.223
dc.identifier.endpage6368en_US
dc.identifier.issn2238-7854
dc.identifier.issn2214-0697
dc.identifier.scopus2-s2.0-85156262937en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage6348en_US
dc.identifier.urihttps://doi.org/10.1016/j.jmrt.2023.04.223
dc.identifier.urihttps://hdl.handle.net/20.500.12452/12223
dc.identifier.volume24en_US
dc.identifier.wosWOS:001042215100001en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal Of Materials Research And Technology-Jmr&Ten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectConcreteen_US
dc.subjectCeramic Wasteen_US
dc.subjectMachine Learningen_US
dc.subjectPrediction Algorithmsen_US
dc.subjectCompressive Strengthen_US
dc.subjectShapen_US
dc.titleData-driven based estimation of waste-derived ceramic concrete from experimental results with its environmental assessmenten_US
dc.typeArticleen_US

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