摘要
为进一步改善高速列车明线运行的气动性能和噪声性能,降低空气阻力、空气升力和列车表面噪声源声功率,对高速列车流线型头型进行多目标优化设计.在列车垂向、横向、纵向三个方向上选择7组优化设计变量,采用最优拉丁超立方法进行采样,运用网格驱动变形技术(ASD)快速得到计算样本.基于三维不可压缩控制方程和k-ε湍流模型,对列车进行模拟计算.构造关于空气阻力、空气升力和列车表面噪声源声功率的响应面近似模型,运用NSGA-II遗传算法对高速列车头型进行多目标优化,得到Pareto前沿解集.与原列车相比,优化后列车的空气阻力减小5.20%,空气升力减小36.68%,列车表面噪声源声功率减小2.11%.
To improve further the aerodynamic and noise performance of high-speed trains running in open air and reduce the aerodynamic drag,aerodynamic lift and sound power of the train surface noise source,the multi-objective optimization design of high-speed train head shape was implemented.Seven groups of optimization design variables were selected in vertical,horizontal and vertical directions of the train.The optimal Latin hypercube design was used to sample,and the grid driven deformation(ASD)technique was used to obtain the sample quickly.Based on the three-dimensional incompressible governing equations andturbulence model,the train was simulated.The response surface functions of design variables were constructed with respect to aerodynamic drag,aerodynamic lift and sound power of the train surface noise source.Through the genetic algorithm NSGA-II to optimize the streamline shape of high-speed train,a series of Pareto optimal head shapes were obtained.Compared with the original train,the aerodynamic drag of the optimized train is reduced by 5.20%,the aerodynamic lift is reduced by 36.68%,and the sound power of the train surface noise source is reduced by 2.11%.
作者
季玲
刘海东
陈秉智
JI Ling;LIU Haidong;CHENG Bingzhi(School of Locomotive and Ralling Stock Engineering,Dalian Jiaotong University,Dalian 116028,China)
出处
《大连交通大学学报》
CAS
2022年第5期35-40,共6页
Journal of Dalian Jiaotong University
基金
大连市科技创新基金计划资助项目(2019J11CY017)
中国国家铁路集团有限公司科技研究开发计划资助项目(N2020J027)。
关键词
网格驱动变形技术
响应面近似模型
多目标优化
列车表面噪声源声功率
grid driven deformation
response surface method
multi-objective optimization
sound power of train surface noise source
