Intelligent Generation Method of Innovative Structures Based on Topology Optimization and Deep Learning

Materials

Hui Wang¹  Wenfeng Du¹  Yingqi Wang¹  Yannan Zhao¹ 

[1] Institute of Steel and Spatial Structures, College of Civil Engineering and Architecture, Henan University, Kaifeng 475004, China;

关键词: innovative structures;    topology optimization;    boundary equilibrium generative adversarial networks;    additive manufacturing;    material consumption;   

DOI  :  10.3390/ma14247680

来源: DOAJ

【 摘 要 】

Computer-aided design has been widely used in structural calculation and analysis, but there are still challenges in generating innovative structures intelligently. Aiming at this issue, a new method was proposed to realize the intelligent generation of innovative structures based on topology optimization and deep learning. Firstly, a large number of structural models obtained from topology optimization under different optimization parameters were extracted to produce the training set images, and the training set labels were defined as the corresponding load cases. Then, the boundary equilibrium generative adversarial networks (BEGAN) deep learning algorithm was applied to generate numerous innovative structures. Finally, the generated structures were evaluated by a series of evaluation indexes, including innovation, aesthetics, machinability, and mechanical performance. Combined with two engineering cases, the application process of the above method is described here in detail. Furthermore, the 3D reconstruction and additive manufacturing techniques were applied to manufacture the structural models. The research results showed that the proposed approach of structural generation based on topology optimization and deep learning is feasible, and can not only generate innovative structures but also optimize the material consumption and mechanical performance further.

【 授权许可】

Unknown