基于NSGA-Ⅱ算法的高速铁路声屏障高度多目标优化

Multi-objective optimization of noise barrier height for high-speed railway based on NSGA-II algorithm

为探究高速铁路声屏障高度的多目标优化问题,基于声屏障降噪理论,利用声-振分析软件SYSNOISE计算不同高度声屏障的插入损失。基于非定常、三维、不可压缩N-S方程和k-ε方程湍流模型,利用FLUNT软件,计算不同高度直立型声屏障的最大有效正压力。以插入损失和最大有效正压力为优化目标,声屏障高度作为设计变量,采用非支配排序遗传算法(NSGA-Ⅱ)得到Pareto分布优化解集,对高速铁路声屏障高度进行优化设计,可为高速铁路声屏障高度设置提供更多权衡选择方案。

In order to explore the multi-objective optimization problem of the height of high-speed railway noise barrier,based on the theory of noise reduction,the SYSNOISE was used to calculate the insertion loss of noise barriers at different heights.Based on the unsteady,three-dimensional,incompressible N-S equations and the k-ε equation turbulence model,FLUNT was used to calculate the maximum effective positive pressure of vertical noise barriers at different heights.Taking the insertion loss and the maximum effective positive pressure as the optimization goal,the noise barrier height was used as the design variable,and the non-dominated sorting genetic algorithm (NSGA-II) was used to obtain the Pareto distribution optimization solution set,and the high-speed railway noise barrier height was optimized.More trade-off options can be provided for high-speed railway noise barrier height settings.