Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM)
The use of Coal bottom ash (CBA) as a sand substitute in concrete has become an interesting research topic due to its potential to produce sustainable concrete. However, there is an ongoing need to optimise critical parameters in CBA concrete. Therefore, this research aims to optimise three independ...
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my.uniten.dspace-362112025-03-03T15:41:35Z Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) Ku Meh K.M.F. Mohd Zuki S.S. Algaifi H.A. Omar Z. Shahidan S. Shamsuddin S.-M. Ihsan F. 59296723000 57192910926 57203885467 57576144000 55561483700 57199324380 59296354700 Age hardening Coal research Compressive strength Concrete mixtures Prediction models Bottom ash Coal bottom ash Curing age Hardened concrete Optimisations Optimization models Prediction modelling Research topics Response-surface methodology Sand replacement Coal ash The use of Coal bottom ash (CBA) as a sand substitute in concrete has become an interesting research topic due to its potential to produce sustainable concrete. However, there is an ongoing need to optimise critical parameters in CBA concrete. Therefore, this research aims to optimise three independent variables involving CBA content, water-cement (WC) ratio, and curing ages based on the highest hardened properties, experimentally and theoretically. In particular, based on the face-centered central composite design (FC-CCD) of response surface methodology (RSM), 18 mixes of various combinations of the independent factors (WC ratio: 0.40�0.50, CBA replacement: 5�20%, and curing ages: 28�56 days) were generated, and this investigation primary focused on two responses (compressive strength and water absorption). The proposed models were validated using analysis of variance (ANOVA) and other statistical parameters, and the findings suggested that both models of compressive strength and water absorption were significant and reliable, with p-values less than 0.0001 (p < 0.0001). The coefficient of determination (R2) values discovered were very high, with values of 0.99 and 0.94 for compressive strength and water absorption, respectively, indicating a significant relationship between the actual and predicted values. The results revealed that the compressive strength of CBA concrete was higher than that of the characteristic strength of the control mix (30�MPa) for all levels of replacement percentage. The optimal conditions for compressive strength and minimal water absorption in CBA concrete were achieved when the lowest CBA replacement was 5%, and the WC ratio was 0.40 for 28 and 56 days. The validation findings revealed that the variation data for both models was less than 5%, indicating that the proposed equations had the potential to predict future observations. ? The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. Final 2025-03-03T07:41:35Z 2025-03-03T07:41:35Z 2024 Article 10.1007/s41939-024-00565-6 2-s2.0-85201931405 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201931405&doi=10.1007%2fs41939-024-00565-6&partnerID=40&md5=db4d32ea110943e7cbeb1971e81eec60 https://irepository.uniten.edu.my/handle/123456789/36211 7 6 6113 6128 Springer Science and Business Media B.V. Scopus |
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Age hardening Coal research Compressive strength Concrete mixtures Prediction models Bottom ash Coal bottom ash Curing age Hardened concrete Optimisations Optimization models Prediction modelling Research topics Response-surface methodology Sand replacement Coal ash |
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Age hardening Coal research Compressive strength Concrete mixtures Prediction models Bottom ash Coal bottom ash Curing age Hardened concrete Optimisations Optimization models Prediction modelling Research topics Response-surface methodology Sand replacement Coal ash Ku Meh K.M.F. Mohd Zuki S.S. Algaifi H.A. Omar Z. Shahidan S. Shamsuddin S.-M. Ihsan F. Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) |
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The use of Coal bottom ash (CBA) as a sand substitute in concrete has become an interesting research topic due to its potential to produce sustainable concrete. However, there is an ongoing need to optimise critical parameters in CBA concrete. Therefore, this research aims to optimise three independent variables involving CBA content, water-cement (WC) ratio, and curing ages based on the highest hardened properties, experimentally and theoretically. In particular, based on the face-centered central composite design (FC-CCD) of response surface methodology (RSM), 18 mixes of various combinations of the independent factors (WC ratio: 0.40�0.50, CBA replacement: 5�20%, and curing ages: 28�56 days) were generated, and this investigation primary focused on two responses (compressive strength and water absorption). The proposed models were validated using analysis of variance (ANOVA) and other statistical parameters, and the findings suggested that both models of compressive strength and water absorption were significant and reliable, with p-values less than 0.0001 (p < 0.0001). The coefficient of determination (R2) values discovered were very high, with values of 0.99 and 0.94 for compressive strength and water absorption, respectively, indicating a significant relationship between the actual and predicted values. The results revealed that the compressive strength of CBA concrete was higher than that of the characteristic strength of the control mix (30�MPa) for all levels of replacement percentage. The optimal conditions for compressive strength and minimal water absorption in CBA concrete were achieved when the lowest CBA replacement was 5%, and the WC ratio was 0.40 for 28 and 56 days. The validation findings revealed that the variation data for both models was less than 5%, indicating that the proposed equations had the potential to predict future observations. ? The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. |
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59296723000 Ku Meh K.M.F. Mohd Zuki S.S. Algaifi H.A. Omar Z. Shahidan S. Shamsuddin S.-M. Ihsan F. |
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Ku Meh K.M.F. Mohd Zuki S.S. Algaifi H.A. Omar Z. Shahidan S. Shamsuddin S.-M. Ihsan F. |
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Ku Meh K.M.F. |
title |
Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) |
title_short |
Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) |
title_full |
Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) |
title_fullStr |
Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) |
title_full_unstemmed |
Optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom Ash (CBA) via the response surface methodology (RSM) |
title_sort |
optimisation and prediction modeling of hardened concrete characteristics incorporating coal bottom ash (cba) via the response surface methodology (rsm) |
publisher |
Springer Science and Business Media B.V. |
publishDate |
2025 |
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1825816265472606208 |
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13.244413 |