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首页> 外文期刊>Advances in Engineering Software >Optimum design of unbraced steel frames to LRFD-AISC using particle swarm optimization
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Optimum design of unbraced steel frames to LRFD-AISC using particle swarm optimization

机译:使用粒子群算法对LRFD-AISC的无支撑钢框架进行优化设计

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Particle Swarm method based optimum design algorithm for unbraced steel frames is presented. The Particle Swarm method is a numerical optimization technique that simulates the social behavior of birds, fishes and bugs. In nature fish school, birds flock and bugs swarm not only for reproduction but for other reasons such as finding food and escaping predators. Similar to birds seek to find food, the optimum design process seeks to find the optimum solution. In the particle swarm optimization each particle in the swarm represents a candidate solution of the optimum design problem. In the optimum design algorithm presented the design constraints are imposed in accordance with LRFD-AISC (Load and Resistance Factor Design, American Institute of Steel Construction). In the design of beam-column members the combined strength constraints are considered that take into account the lateral torsional buckling of the member. The algorithm developed selects optimum W sections for beams and columns of unbraced frame from the list of 272 W-sections list. This selection is carried out such that design constraints imposed by the LRFD are satisfied and the minimum frame weight is obtained. The efficiency of the algorithm is demonstrated considering a number of design examples.
机译:提出了基于粒子群算法的无支撑钢框架优化设计算法。粒子群方法是一种数值优化技术,用于模拟鸟类,鱼类和虫子的社会行为。在自然养鱼学校中,鸟群和虫子蜂拥而至不仅是为了繁殖,而且还有其他原因,例如寻找食物和逃避食肉动物。类似于鸟类寻求食物,最佳设计过程旨在寻找最佳解决方案。在粒子群优化中,粒子群中的每个粒子代表最佳设计问题的候选解决方案。在提出的最佳设计算法中,设计约束是根据LRFD-AISC(美国钢结构学会的载荷和阻力系数设计)施加的。在梁柱构件的设计中,考虑到构件的横向扭转屈曲,考虑了组合强度约束。开发的算法从272个W型截面列表中为无支撑框架的梁和柱选择最佳W型截面。进行该选择,以便满足由L​​RFD施加的设计约束,并获得最小的帧权重。考虑了许多设计实例,证明了该算法的效率。

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