How to combine different types of prefabricated components in a building to reduce construction costs and carbon emissions?

被引:0
|
作者
Su, Shu [1 ,2 ]
Li, Lei [1 ]
Sun, Ao [1 ]
Cao, Xinying [3 ]
Yuan, Jingfeng [1 ]
机构
[1] Southeast Univ, Sch Civil Engn, Dept Construct & Real Estate, Nanjing 211189, Peoples R China
[2] Minist Educ, Engn Res Ctr Bldg Equipment Energy & Environm, Beijing, Peoples R China
[3] Hainan Univ, Sch Civil & Architectural Engn, Haikou 570228, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Components combination; Prefabricated concrete building; Construction costs; Carbon emission; Dual-objective optimization; OPTIMIZATION; PERFORMANCE;
D O I
10.1016/j.jobe.2024.111114
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In the context of industrialized construction and carbon emission reduction globally, prefabrication has gained considerable attention. However, most studies cared the carbon emissions and construction costs from the perspective of a whole prefabricated building rather than the prefabricated components. It makes it difficult to understand the role of prefabricated components play and make improvements from the prefabricated components level. To fill this gap, this study proposes a model to optimize the selection and combination of prefabricated components in a building project to simultaneously reduce the construction costs and carbon emissions. Six common component types were considered: shear wall, beam, floor slab, stair, balcony, and air-conditioning slab. Their costs and carbon emissions were quantified when adopting prefabrication and cast-in-situ technologies. To obtain the optimal solution, we developed an improved multi-objective mayfly algorithm (IMOMA), which incorporates enhanced circle chaos mapping and a global best guiding strategy to generate Pareto solution sets. The performance of IMOMA was evaluated using the Zitzler-Deb-Thiele series test functions, demonstrating its advantages in convergence, diversity, and comprehensive performance through metrics such as generation distance, diversity metric Delta, and inverse generational distance. A case study validated the effectiveness of this proposed method, demonstrating an average reduction of 9.05 % in total construction costs and 8.04 % in carbon emissions when compared to the initial scheme. Further study revealed that different prefabrication rates correspond to different optimal components combination schemes, with different trends in the costs and carbon emission curves as the prefabrication rate increases. Additionally, carbon trading policies influence the components combination, with construction costs reduced by 10.88 % at a carbon trading price of 42.80 CNY/t CO(2)eq. This study provides valuable guidance for general contractors to design optimal component combinations and for governments to promote the sustainable development of prefabricated construction.
引用
收藏
页数:17
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