Box Girder Optimization by Orthogonal Experiment Design and GA-BP Algorithm in the Gondola Car Body

靠垫 箱梁 遗传算法 工程类 有限元法 结构工程 梁(结构) 算法
作者
Liu Wenfei,Yuanqing Wang,Tianyou Wang
出处
期刊:Processes [MDPI AG]
卷期号:10 (1): 74-74
标识
DOI:10.3390/pr10010074
摘要

Box girder is an important bearing and force transmitting component in the gondola car body; the rationality of its structure directly affects the life of the whole car body. In order to solve disadvantage of the traditional box girder optimization method, which mainly depends on design experience, the combined method of orthogonal experimental design and the genetic algorithm-back propagation (GA-BP) algorithm is used for the structural optimization of bolster beam in this paper. Nine groups of parameters were established by orthogonal experiment, which can give typical samples for GA-BP optimization. Then, the bolster beam is optimized by the GA-BP algorithm, and the new gondola car body model is established with the optimized parameters. The finite element analysis results show that the minimum stress is found by using the GA-BP algorithm, which is basically consistent with the simulation results. Finally, the results show that the combined method of orthogonal experimental design and GA-BP algorithm is feasible to the box girder optimization of the gondola car body. Meanwhile, the optimization results of bolster beam will provide a reference for the structural design of the heavy haul wagon body.

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