Low-carbon design: Building optimization considering carbon emission, material utilization, and daylighting

被引:14
作者
Zhong, Yuting [1 ,2 ]
Qin, Zesheng [3 ]
Feng, Ruoqiang [1 ,2 ]
Liu, Yingkai [3 ]
机构
[1] Southeast Univ, Key Lab Concrete & Prestressed Concrete Struct, Minist Educ, Nanjing 211189, Jiangsu, Peoples R China
[2] Southeast Univ, Sch Civil Engn, Nanjing 211189, Jiangsu, Peoples R China
[3] Hunan Univ, Coll Civil Engn, Changsha 410082, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Low-carbon design; Architectural optimization; Multi-objective optimization; ARTIFICIAL NEURAL-NETWORK; SHAPE OPTIMIZATION; ENERGY PERFORMANCE; SPACE; CONSTRUCTION; ALGORITHMS; EFFICIENCY; ENVELOPE; STAGE;
D O I
10.1016/j.jclepro.2023.140087
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this study, a low-carbon architectural design method is proposed. With the proposed method, it is possible to minimize the carbon emissions of the building while optimizing its material utilization and daylighting. The design process consists of three main steps: Firstly, a parametric model of the building was constructed to determine its material utilization, daylighting, and carbon emission under different parameters. The model's accuracy was then experimentally validated. Secondly, establish neural networks between structural parameters (geometry and window-to-wall ratio) and material utilization, daylighting, and carbon emissions. Subsequently, perform a multi-objective optimization of the building's carbon emissions, material utilization and daylighting based on the established neural network. Finally, a modified "Technique for Order Preference by Similarity to an Ideal Solution" (TOPSIS) is proposed to determine the optimal solution among multiple optimization results. To illustrate the optimization process of the proposed method in detail, it is applied to a real case of greenhouse optimization. To holistically evaluate the optimization, a comprehensive evaluation index, Pc, that considers material utilization, daylighting, and carbon emissions, is proposed. The study reveals that upon utilizing the proposed low-carbon optimal design method, the Pc of the greenhouse sees a 7.67-fold increase, while simultaneously reducing carbon emissions by 23% compared to original levels. Additionally, specific greenhouse designs were optimized to demonstrate the method's practicality.
引用
收藏
页数:17
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