A multi-objective optimisation approach for activity excitation of waste glass mortar
Waste glass is promising to be recycled and reused in construction for sustainability. Silicon dioxide is the main component of glass, however, its pozzolanic activity is latent mainly due to its stable silica tetrahedron structure. To excite the activation of waste glass, chemical activation and me...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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ELSEVIER
2022
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| Online Access: | http://purl.org/au-research/grants/arc/LP180100222 http://hdl.handle.net/20.500.11937/90919 |
| _version_ | 1848765460656422912 |
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| author | Sun, J. Tang, Y. Wang, J. Wang, Xiangyu Wang, J. Yu, Z. Cheng, Q. Wang, Yufei |
| author_facet | Sun, J. Tang, Y. Wang, J. Wang, Xiangyu Wang, J. Yu, Z. Cheng, Q. Wang, Yufei |
| author_sort | Sun, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Waste glass is promising to be recycled and reused in construction for sustainability. Silicon dioxide is the main component of glass, however, its pozzolanic activity is latent mainly due to its stable silica tetrahedron structure. To excite the activation of waste glass, chemical activation and mechanical grinding of waste glass powder (WGP) were investigated. As the supplementary, hydrothermal and combined (mechanical-chemical-hydrothermal) treatments were conducted on part of the WGP samples. The unconfined compression strength (UCS), expansion caused by alkali–silica reaction (ASR), and the microstructural morphology of WGP were investigated. The results showed the dosage threshold (around 2%) of the chemical activators (alkali and sodium sulfate) and the combined activation were optimal. Besides, a firefly algorithm (FA) based multi-objective optimisation model (MOFA) was applied to seek the Pareto fronts based on three objectives: UCS, ASR expansion, and Cost of mixture proportion. The objective functions of UCS and expansion were established through training the machine learning (ML) models where FA was used to tune the hyperparameters. The cost was calculated by a polynomial function. The ultimate values of root mean square error (RMSE) and correlation coefficient (R) showed the robustness of the ML models. Moreover, the Pareto fronts for mortars containing 300 μm and 75 μm WGPs were successfully obtained, which contributed to the practical application of waste glass in mortar production. In addition, the sensitivity analysis was conducted to rank the importance of input variables. The results showed that curing time, activator's content, and WGP particle size were three essential parameters. |
| first_indexed | 2025-11-14T11:35:36Z |
| format | Journal Article |
| id | curtin-20.500.11937-90919 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:35:36Z |
| publishDate | 2022 |
| publisher | ELSEVIER |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-909192023-05-09T08:02:50Z A multi-objective optimisation approach for activity excitation of waste glass mortar Sun, J. Tang, Y. Wang, J. Wang, Xiangyu Wang, J. Yu, Z. Cheng, Q. Wang, Yufei Science & Technology Technology Materials Science, Multidisciplinary Metallurgy & Metallurgical Engineering Materials Science Waste glass Activation methodology Compressive strength Alkali-silica reaction Machine learning Multi-objective optimisation ALKALI-SILICA REACTION CONCRETE BEHAVIOR DURABILITY CEMENT ASR Waste glass is promising to be recycled and reused in construction for sustainability. Silicon dioxide is the main component of glass, however, its pozzolanic activity is latent mainly due to its stable silica tetrahedron structure. To excite the activation of waste glass, chemical activation and mechanical grinding of waste glass powder (WGP) were investigated. As the supplementary, hydrothermal and combined (mechanical-chemical-hydrothermal) treatments were conducted on part of the WGP samples. The unconfined compression strength (UCS), expansion caused by alkali–silica reaction (ASR), and the microstructural morphology of WGP were investigated. The results showed the dosage threshold (around 2%) of the chemical activators (alkali and sodium sulfate) and the combined activation were optimal. Besides, a firefly algorithm (FA) based multi-objective optimisation model (MOFA) was applied to seek the Pareto fronts based on three objectives: UCS, ASR expansion, and Cost of mixture proportion. The objective functions of UCS and expansion were established through training the machine learning (ML) models where FA was used to tune the hyperparameters. The cost was calculated by a polynomial function. The ultimate values of root mean square error (RMSE) and correlation coefficient (R) showed the robustness of the ML models. Moreover, the Pareto fronts for mortars containing 300 μm and 75 μm WGPs were successfully obtained, which contributed to the practical application of waste glass in mortar production. In addition, the sensitivity analysis was conducted to rank the importance of input variables. The results showed that curing time, activator's content, and WGP particle size were three essential parameters. 2022 Journal Article http://hdl.handle.net/20.500.11937/90919 10.1016/j.jmrt.2022.01.066 English http://purl.org/au-research/grants/arc/LP180100222 http://creativecommons.org/licenses/by-nc-nd/4.0/ ELSEVIER fulltext |
| spellingShingle | Science & Technology Technology Materials Science, Multidisciplinary Metallurgy & Metallurgical Engineering Materials Science Waste glass Activation methodology Compressive strength Alkali-silica reaction Machine learning Multi-objective optimisation ALKALI-SILICA REACTION CONCRETE BEHAVIOR DURABILITY CEMENT ASR Sun, J. Tang, Y. Wang, J. Wang, Xiangyu Wang, J. Yu, Z. Cheng, Q. Wang, Yufei A multi-objective optimisation approach for activity excitation of waste glass mortar |
| title | A multi-objective optimisation approach for activity excitation of waste glass mortar |
| title_full | A multi-objective optimisation approach for activity excitation of waste glass mortar |
| title_fullStr | A multi-objective optimisation approach for activity excitation of waste glass mortar |
| title_full_unstemmed | A multi-objective optimisation approach for activity excitation of waste glass mortar |
| title_short | A multi-objective optimisation approach for activity excitation of waste glass mortar |
| title_sort | multi-objective optimisation approach for activity excitation of waste glass mortar |
| topic | Science & Technology Technology Materials Science, Multidisciplinary Metallurgy & Metallurgical Engineering Materials Science Waste glass Activation methodology Compressive strength Alkali-silica reaction Machine learning Multi-objective optimisation ALKALI-SILICA REACTION CONCRETE BEHAVIOR DURABILITY CEMENT ASR |
| url | http://purl.org/au-research/grants/arc/LP180100222 http://hdl.handle.net/20.500.11937/90919 |