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A robust method for optimization of semi-rigid steel frames subject to seismic loading

机译:承受地震载荷的半刚性钢框架优化的鲁棒方法

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In this study, we develop a seismic optimization method to minimize the semi-rigid steel frame cost. In the proposed method, cross-sections of columns and beams and types of beam-to-column and base restraint semirigid joints are considered as the design variables of the optimization. The nonlinear seismic behaviors of the structure are carried out by using plastic-hinge beam-column elements for beams and columns, zero-length elements for semi-rigid connections, and time-history dynamic analysis. An effective implementation of harmony search technique (HS) is presented to find the global optimal solution of the optimization. In order to improve HS, a multi-comparison technique (MCT) is proposed that significantly reduces the useless timeconsuming evaluations in the optimization. The robustness and efficiency of the proposed method are demonstrated through three optimization problems of semi-rigid steel frames. Compared with particle swarm optimization (PSO), micro-genetic algorithm (micro-GA), and genetic algorithm (GA), the proposed method is found to significantly reduce the number of structural analyses required and yield the better optimum frame designs. (C) 2017 Elsevier Ltd. All rights reserved.
机译:在这项研究中,我们开发了一种地震优化方法来最小化半刚性钢框架的成本。在该方法中,将柱和梁的横截面以及梁-柱和基础约束半刚性连接的类型视为优化的设计变量。该结构的非线性地震行为是通过对梁和柱使用塑性铰梁-柱单元,对于半刚性连接使用零长度单元以及时程动力学分析来进行的。提出了和声搜索技术(HS)的有效实现,以找到优化的全局最优解。为了提高HS,提出了一种多比较技术(MCT),该技术可大大减少优化过程中无用的耗时评估。通过对半刚性钢框架的三个优化问题证明了该方法的鲁棒性和有效性。与粒子群优化(PSO),微遗传算法(micro-GA)和遗传算法(GA)相比,该方法显着减少了所需的结构分析次数,并产生了更好的最佳框架设计。 (C)2017 Elsevier Ltd.保留所有权利。

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