International Journal of High-Rise Buildings (국제초고층학회논문집)

Council on Tall Building and Urban Habitat Korea (한국초고층도시건축학회)
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Generative Artificial Intelligence for Structural Design of Tall Buildings

  • Wenjie Liao (Key Laboratory of Civil Engineering Safety and Durability of China Education Ministry, Department of Civil Engineering, Tsinghua University) ;
  • Xinzheng Lu (Key Laboratory of Civil Engineering Safety and Durability of China Education Ministry, Department of Civil Engineering, Tsinghua University) ;
  • Yifan Fei (Key Laboratory of Civil Engineering Safety and Durability of China Education Ministry, Department of Civil Engineering, Tsinghua University)
  • Published : 2023.09.11
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Abstract

The implementation of artificial intelligence (AI) design for tall building structures is an essential solution for addressing critical challenges in the current structural design industry. Generative AI technology is a crucial technical aid because it can acquire knowledge of design principles from multiple sources, such as architectural and structural design data, empirical knowledge, and mechanical principles. This paper presents a set of AI design techniques for building structures based on two types of generative AI: generative adversarial networks and graph neural networks. Specifically, these techniques effectively master the design of vertical and horizontal component layouts as well as the cross-sectional size of components in reinforced concrete shear walls and frame structures of tall buildings. Consequently, these approaches enable the development of high-quality and high-efficiency AI designs for building structures.

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Acknowledgement

This work is supported by the Research Project of China Civil Engineering Society (2023-05). the China Postdoctoral Science Foun-dation (2022M721879), and the Tencent Foundation through the XPLORER PRIZE.

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