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为探究高速铁路桥梁风屏障高度的多目标优化问题,基于计算流体动力学理论,采用数值模拟方法计算设置有不同高度风障时,列车及桥梁各自的气动力系数。以车辆侧倾稳定性力矩系数及桥梁阻力系数为优化目标,风屏障高度为设计变量,采用多目标遗传算法(NSGA-II)求解Pareto最优解集,采用数据包络分析方法(DEA)评价Pareto解集中各个解的相对效率,得到最优风屏障高度。结果表明:采用NSGA-II&DEA混合算法对风屏障高度进行多目标优化是可行的。该优化设计方法为风屏障高度优化问题提供了一种新思路。
In order to explore the multi-objective optimization problem of wind barrier height of high-speed railway bridges, aerodynamic coefficients of trains and bridges are calculated by numerical simulation based on CFD theory. Taking the vehicle roll stability torque coefficient and the bridge resistance coefficient as the optimization targets and the wind barrier height as the design variable, the Pareto optimal solution set was solved by the multi-objective genetic algorithm (NSGA-II) and the DEA The relative efficiency of each solution in the Pareto solution sets gives the optimal height of the wind barrier. The results show that it is feasible to use the NSGA-II & DEA hybrid algorithm to optimize wind barrier height. The optimal design method provides a new idea for the wind barrier height optimization problem.