Intelligent design of shear wall layout based on diffusion models

IF 8.5 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-05-17 DOI:10.1111/mice.13236
Yi Gu, Yuli Huang, Wenjie Liao, Xinzheng Lu
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Abstract

This study explores artificial intelligence (AI) for shear wall layout design, aiming to overcome challenges in data feature sparsity and the complexity of drawing representations in existing AI‐based methods. We pioneer an innovative method leveraging the potential of diffusion models, establishing a suitable drawing representation, and examining the impact of various conditions. The proposed image‐prompt diffusion model incorporating a mask tensor featuring tailored training methods demonstrates superior feature extraction and design effectiveness. A comparative study reveals the advanced capabilities of the Struct‐Diffusion model in capturing engineering designs and optimizing performance metrics such as inter‐story drift ratio (in elastic analysis), offering significant improvements over previous methods and paving the way for future innovations in intelligent designs.
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基于扩散模型的剪力墙布局智能设计
本研究探讨了剪力墙布局设计的人工智能(AI),旨在克服现有基于人工智能的方法在数据特征稀疏性和绘图表示复杂性方面的挑战。我们利用扩散模型的潜力开创了一种创新方法,建立了合适的绘图表示法,并检验了各种条件的影响。我们提出的图像提示扩散模型结合了面具张量,并采用了量身定制的训练方法,显示出卓越的特征提取和设计效果。对比研究显示,Struct-Diffusion 模型在捕捉工程设计和优化性能指标(如弹性分析中的层间漂移比)方面具有先进的能力,与以前的方法相比有显著的改进,为未来智能设计的创新铺平了道路。
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来源期刊
CiteScore
17.60
自引率
19.80%
发文量
146
审稿时长
1 months
期刊介绍: Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.
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