Data-driven and design rule constraint-based intelligent layout design method for steel frame-brace structures
Artificial intelligence algorithm is a key technology to realize the automated and intelligent design of building structures.However,due to the lack of physical rules constraint,artificial intelligence algorithms in practical engineering applications tend to provide unreasonable results.Therefore,in this study,by integrating structural design rules into the generative adversarial network(GAN)in the form of the neural network module,a novel intelligent layout design method for steel frame-brace structures,FrameGAN-sym,was proposed.The basic principles and ideas of this method were first introduced,and then the design results of FrameGAN-sym were compared and analyzed in detail with those of FrameGAN,which proves that FrameGAN-sym can synthesize more symmetric structural drawings according to the requirements of the proposed symmetry constraint network module.The mechanical properties of the design of FrameGAN,FrameGAN-sym and the engineers were compared through three engineering cases of steel frame-brace structures with different heights.The results show that the design of FrameGAN-sym is closer to that of engineers in terms of mechanical properties,and the torsion effect of the FrameGAN-sym-designed structure is reduced compared with the FrameGAN-designed structures.
国家科技期刊平台
NSTL
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