基于遗传算法的高速列车头型多目标优化

Multi-objective Optimization of High-speed Train Head Based on Genetic Algorithm

高速列车的气动阻力与列车的外形,特别是头部外形有着密切的关系。为了改善列车气动性能降低列车运行的气动阻力,建立高速列车的三维参数化模型,以高速列车头部所受的阻力和升力为优化目标,通过FLUENT软件与Isight软件多学科优化联合仿真分析方法,利用Sculptor软件对车头部分网格自动变形,基于计算流体力学,实现对高速列车流线型头型进行减阻的多目标自动优化设计。优化完成后,得到影响优化目标阻力和升力的关键设计变量,并对优化设计变量和优化目标之间的非线性相关性进行分析。通过对比原始流线型列车气动性能发现,列车头部的长度对阻力的影响比较大,列车头部的高度能够对列车所受到的升力产生较大的影响。

The aerodynamic drag of a high-speed train is closely related to the shape of the train,especially the shape of the train head.In order to improve the aerodynamic performance of the train and reduce the aerodynamic resistance of the train opera⁃tion,a three-dimensional parameterized model of high-speed train is established.Taking the drag and lift of the head of high-speed train as the optimization objective,the streamlined head of high-speed train is automatically deformed by using Sculptor software through the joint simulation analysis method of FLUENT software and Isight software.Based on computational fluid dynamics,streamlined head of high-speed train is realized.A multi-objective automatic optimization design for drag reduction is carried out.After the optimization is completed,the key design variables affecting the optimization target resistance and lift are obtained,and the nonlinear correlation between the optimized design variables and the optimization targets is analyzed.By comparing the aerody⁃namic performance of the original streamlined train,it is found that the length of the train head has a greater influence on the resis⁃tance,and the height of the train head can have a greater impact on the lift of the train.