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首页> 外文期刊>Journal of Zhejiang University. Science, A >Multi-objective optimization design method of the high-speed train head*
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Multi-objective optimization design method of the high-speed train head*

机译:高速列车头的多目标优化设计方法*

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摘要

With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.
机译:随着火车速度的持续改进,火车的动态环境变为空气动力学统治。解决空气动力学问题已成为高速列车头设计的关键因素之一。鉴于空气动力学阻力是限制火车速度和节能的重要因素,降低空气动力学阻力是高速列车头设计的重要考虑因素。然而,空气动力学阻力的减少可能增加其他空气动力(时刻),可能会使火车的操作安全性恶化。本文提出了高速列车头的多目标优化设计方法,并设定了空气动力学阻力和减少减少因子是优化目标。通过将一系列程序集成到多目标优化算法中,可以实现高速列车头的自动多目标优化设计,例如建立3D参数模型,气动网格生成,流量的计算火车周围的字段,以及车辆系统动态。分析了优化目标和优化变量之间的相关性以获得最重要的优化变量,并获得了关键优化变量与优化目标之间的非线性关系的进一步分析。优化后,优化火车的空气动力学阻力降低了高达4.15%,负载减少因数降低了高达1.72%。

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