横风下高速列车流线型头型多目标气动优化设计

为改善高速列车的横风气动性能，建立高速列车流线型头型的多目标优化设计方法，以横风下高速列车的侧力和升力为优化目标，对高速列车流线型头型进行多目标自动优化设计。建立高速列车流线型头型的参数化模型，提取出5个优化设计变量，利用计算流体动力学方法进行高速列车流场计算，并结合多目标遗传算法，实现横风下高速列车流线型头型的自动寻优设计。通过相关性分析，得到影响侧力和升力的关键优化设计变量，并进一步研究关键优化设计变量和优化目标之间的非线性关系。经过多目标优化设计，获得一系列的Pareto最优头型，这些头型的横风气动性能均得到明显改善。同时为保证无风环境下高速列车的基本气动性能不发生恶化，最终筛选出8个Pareto最优头型。对于这8个Pareto最优头型，相对于原始头型来说，横风下的侧力最多可降低3.06%，横风下的升力最多可降低19.60%，无风时的气动阻力最多可降低4.51%，无风时的气动升力最多可降低9.68%。

Multi-objective Aerodynamic Optimization Design of the Streamlined Head of High-speed Trains under Crosswinds

Multi-objective optimization design method of the streamlined head of high-speed trains is proposed to improve the aerodynamic performance of high-speed trains under crosswinds. The side force and lift force of high-speed trains under crosswinds are set as optimization objectives and the automatic multi-objective optimization design of the streamlined head of high-speed trains is carried out. The parametric model of the streamlined head of high-speed trains is established and 5 optimization design variables are extracted. The flow field around high-speed trains under crosswinds is computed based on computational fluid dynamics(CFD) method. The multi-objective genetic algorithm is used to update optimization design variables to achieve the automatic optimization design of the streamlined head of high-speed trains. The correlation between the optimization objectives and optimization design variables is analyzed to obtain the most important optimization design variables, and further analysis of the nonlinear relationship between the key optimization design variables and the optimization objectives is obtained. After the multi-objective optimization design, a series of Pareto-optimal head types can be obtained, and the aerodynamic performance of Pareto-optimal head types under crosswinds has been significantly improved. Meanwhile, in order to ensure that the basic aerodynamic performance of high-speed trains with zero wind condition does not deteriorate, 8 Pareto-optimal head types are selected. For these 8 Pareto-optimal head types, compared with the aerodynamic performance under crosswinds and the basic aerodynamic performance with zero wind condition of the original train, the side force under crosswinds is reduced up to 3.06%, the lift force under crosswinds is reduced up to 19.60%, the drag force with zero wind condition is reduced up to 4.51% and the lift force with zero condition is reduced up to 9.68%.