{"title":"基于 RSM-MOPSO-GA 算法的多目标优化和高性能多孔混凝土的协同增强机制","authors":"Guanglei Qu, Mulian Zheng, Chuan Lu, Jiakang Song, Dazhi Dong, Yueming Yuan","doi":"10.1016/j.jclepro.2024.144492","DOIUrl":null,"url":null,"abstract":"Porous concrete (PC) can effectively mitigate various environmental problems associated with road space. Exploring high-performance porous concrete (HPPC) is essential to expanding its applications. However, the current single methods for improvement have almost reached a bottleneck, particularly in terms of mechanical properties. Therefore, this research seeks further breakthroughs from synergistic enhancement and multi-objective optimization. The optimization variables were identified through single-factor experiments, and the optimal solutions for the optimization objectives were subsequently obtained using the response surface methodology (RSM). To address the inherent limitation of RSM in delivering only a single optimal solution, this paper proposed a novel RSM-MOPSO-GA hybrid optimization algorithm. Meanwhile, the synergistic enhancement mechanisms were elucidated through microstructural analysis. The results indicate that the individual enhancement effects of basalt fiber (BF), nano-SiO₂ (NS), and waterborne epoxy resin (WER) are limited. However, the RSM-based optimization significantly improved the performance of HPPC, with compressive strength and flexural strength increased by 51.4% and 69.8%, respectively, and the permeability coefficient enhanced by 33.8%. Furthermore, the application of the RSM-MOPSO-GA algorithm produced a stable Pareto front containing 50 individuals for users' decision-making. The interaction between WER and NS at the microscale, combined with the reinforcement of BF at the mesoscale, establishes a synergistic enhancement mechanism. The research findings provide both a theoretical foundation and experimental basis for the further application of HPPC. Additionally, it also offers a novel solution to address the challenges of multi-objective optimization in concrete performance.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"49 1","pages":""},"PeriodicalIF":9.7000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective Optimization Based on the RSM-MOPSO-GA Algorithm and Synergistic Enhancement Mechanism of High-Performance Porous Concrete\",\"authors\":\"Guanglei Qu, Mulian Zheng, Chuan Lu, Jiakang Song, Dazhi Dong, Yueming Yuan\",\"doi\":\"10.1016/j.jclepro.2024.144492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Porous concrete (PC) can effectively mitigate various environmental problems associated with road space. Exploring high-performance porous concrete (HPPC) is essential to expanding its applications. However, the current single methods for improvement have almost reached a bottleneck, particularly in terms of mechanical properties. Therefore, this research seeks further breakthroughs from synergistic enhancement and multi-objective optimization. The optimization variables were identified through single-factor experiments, and the optimal solutions for the optimization objectives were subsequently obtained using the response surface methodology (RSM). To address the inherent limitation of RSM in delivering only a single optimal solution, this paper proposed a novel RSM-MOPSO-GA hybrid optimization algorithm. Meanwhile, the synergistic enhancement mechanisms were elucidated through microstructural analysis. The results indicate that the individual enhancement effects of basalt fiber (BF), nano-SiO₂ (NS), and waterborne epoxy resin (WER) are limited. However, the RSM-based optimization significantly improved the performance of HPPC, with compressive strength and flexural strength increased by 51.4% and 69.8%, respectively, and the permeability coefficient enhanced by 33.8%. Furthermore, the application of the RSM-MOPSO-GA algorithm produced a stable Pareto front containing 50 individuals for users' decision-making. The interaction between WER and NS at the microscale, combined with the reinforcement of BF at the mesoscale, establishes a synergistic enhancement mechanism. The research findings provide both a theoretical foundation and experimental basis for the further application of HPPC. Additionally, it also offers a novel solution to address the challenges of multi-objective optimization in concrete performance.\",\"PeriodicalId\":349,\"journal\":{\"name\":\"Journal of Cleaner Production\",\"volume\":\"49 1\",\"pages\":\"\"},\"PeriodicalIF\":9.7000,\"publicationDate\":\"2024-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cleaner Production\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jclepro.2024.144492\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cleaner Production","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.jclepro.2024.144492","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Multi-objective Optimization Based on the RSM-MOPSO-GA Algorithm and Synergistic Enhancement Mechanism of High-Performance Porous Concrete
Porous concrete (PC) can effectively mitigate various environmental problems associated with road space. Exploring high-performance porous concrete (HPPC) is essential to expanding its applications. However, the current single methods for improvement have almost reached a bottleneck, particularly in terms of mechanical properties. Therefore, this research seeks further breakthroughs from synergistic enhancement and multi-objective optimization. The optimization variables were identified through single-factor experiments, and the optimal solutions for the optimization objectives were subsequently obtained using the response surface methodology (RSM). To address the inherent limitation of RSM in delivering only a single optimal solution, this paper proposed a novel RSM-MOPSO-GA hybrid optimization algorithm. Meanwhile, the synergistic enhancement mechanisms were elucidated through microstructural analysis. The results indicate that the individual enhancement effects of basalt fiber (BF), nano-SiO₂ (NS), and waterborne epoxy resin (WER) are limited. However, the RSM-based optimization significantly improved the performance of HPPC, with compressive strength and flexural strength increased by 51.4% and 69.8%, respectively, and the permeability coefficient enhanced by 33.8%. Furthermore, the application of the RSM-MOPSO-GA algorithm produced a stable Pareto front containing 50 individuals for users' decision-making. The interaction between WER and NS at the microscale, combined with the reinforcement of BF at the mesoscale, establishes a synergistic enhancement mechanism. The research findings provide both a theoretical foundation and experimental basis for the further application of HPPC. Additionally, it also offers a novel solution to address the challenges of multi-objective optimization in concrete performance.
期刊介绍:
The Journal of Cleaner Production is an international, transdisciplinary journal that addresses and discusses theoretical and practical Cleaner Production, Environmental, and Sustainability issues. It aims to help societies become more sustainable by focusing on the concept of 'Cleaner Production', which aims at preventing waste production and increasing efficiencies in energy, water, resources, and human capital use. The journal serves as a platform for corporations, governments, education institutions, regions, and societies to engage in discussions and research related to Cleaner Production, environmental, and sustainability practices.