剪力墙结构生成式设计与智能优化

Generative design and intelligent optimization of shear wall structure

目前,剪力墙结构的设计主要依赖设计师的设计经验以及不断试错。为了实现快速设计和最优设计,提出了生成式设计和智能优化相融合的剪力墙结构设计方法。基于Stable Diffusion(SD)模型对剪力墙结构进行生成式设计,并基于生成式设计的结果使用禁忌搜索进行智能优化。基于SD模型的生成式设计主要包括使用小样本数据通过低秩适应方法对SD模型进行微调,矢量像素化和像素矢量化;基于禁忌搜索的智能优化包括参数空间的定义,邻域动作的定义,优化目标以及优化流程的设计。通过两个工程实例对所提出的方法进行了对比验证,结果表明,所提出的剪力墙结构生成式设计方法可在约30 s内生成满足基本设计需求的设计结果,智能优化后的设计结果与设计师的方案相似度可达85%,整个智能设计流程达到了辅助设计的目的。

The design of shear wall structures currently relies primarily on the experience of designers and continuous trial and error process.To achieve rapid and optimal design,a method integrating generative design with intelligent optimization has been proposed in this study.Initially,the Stable Diffusion(SD)model is used for the generative design of shear wall structures.Subsequently,based on the results of the generative design,taboo search is employed for intelligent optimization.The SD-based generative design mainly includes fine-tuning of SD by low-rank adaptation methods using small sample data,as well as image processing techniques such as vector pixelation and pixel vectorization.The intelligent optimization based on taboo search includes the definition of parameter space,the definition of domain actions,the optimization objectives and the design of the optimization process.The proposed method is compared and verified with two actual project cases.The results show that the generative design method for shear wall structures can provide designs that meet basic design requirements in approximately 30 seconds.The designs optimized by the intelligent system achieve a similarity of up to 85%compared to the solutions given by designers,fulfilling the purpose of aiding the design process.