摘要
人工智能算法是实现建筑结构自动化、智能化设计的关键技术。然而,由于缺乏物理规则的约束,人工智能算法在实际工程的应用中时而会生成不合理的结果。因此,将结构设计规则以神经网络模块的形式融合到生成对抗网络(GAN)中,提出一种钢框架-支撑结构平面布置智能设计方法(FrameGAN-sym)。对该方法的基本原理和思路进行介绍,并将FrameGAN-sym的设计结果与FrameGAN进行详细的对比和分析,证明其能够按照所提出的对称约束网络模块的要求,生成对称性更强的结构图纸。通过不同高度的3个钢框架-支撑结构工程算例,对比FrameGAN、FrameGAN-sym以及人工设计平面布置方案的力学性能,结果表明,FrameGAN-sym布置方案在力学性能上更加接近人工设计布置方案,且较FrameGAN布置方案降低了结构的扭转效应。
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.
作者
王伟
付柏超
WANG Wei;FU Bochao(State Key Laboratory of Disaster Reduction in Civil Engineering,Tongji University,Shanghai 200092,China;Department of Structural Engineering,Tongji University,Shanghai 200092,China)
出处
《建筑结构学报》
EI
CAS
CSCD
北大核心
2024年第7期13-21,共9页
Journal of Building Structures
基金
国家自然科学基金项目(52378182)
“十四五”国家重点研发计划(2022YFC3801900)
上海市科技创新行动计划(22dz1201700)。
