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Generative AI design for building structures

delete2024-01-01
delete25
PRE
AI
W
Wenjie Liao
陆新征 封面图
陆新征 (Xinzheng Lu) *
Y
Yifan Fei
Y
Yi Gu
Y
Yuli Huang
DOI:10.1016/j.autcon.2023.105187delete
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摘要

摘要

En 中文
Designing building structures presents various challenges, including inefficient design processes, limited data reuse, and the underutilization of previous design experience. Generative artificial intelligence (AI) has emerged as a powerful tool for learning and creatively using existing data to generate new design ideas. Learning from past experiences, this technique can analyze complex structural drawings, combine requirement texts, integrate mechanical and empirical knowledge, and create fresh designs. In this paper, a comprehensive review of recent research and applications of generative AI in building structural design is provided. The focus is on how data is represented, how intelligent generation algorithms are constructed, methods for evaluating designs, and the integration of generation and optimization. This review reveals the significant progress generative AI has made in building structural design, while also highlighting the key challenges and prospects. The goal is to provide a reference that can help guide the transition towards more intelligent design processes.
Keyword:
Building structural design
Data feature representation
Generative AI algorithm
Design evaluation
Intelligent optimization

期刊

Automation in Construction 封面图
Automation in Construction
IF:
11.5
论文数:
6.3K
被引数:
4.2W

机构

T
tsinghua university
学者数:
11.9W
论文数: 10.0W
被引数: 137
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