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CLC number: U271.91; O355

On-line Access: 2017-11-06

Received: 2016-12-06

Revision Accepted: 2017-03-06

Crosschecked: 2017-10-12

Cited: 0

Clicked: 1675

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Liang Zhang

http://orcid.org/0000-0002-7403-7979

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Journal of Zhejiang University SCIENCE A 2017 Vol.18 No.11 P.841-854

10.1631/jzus.A1600764


Multi-objective aerodynamic optimization design of high-speed train head shape


Author(s):  Liang Zhang, Ji-ye Zhang, Tian Li, Ya-dong Zhang

Affiliation(s):  State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China

Corresponding email(s):   swjtu.zl@163.com

Key Words:  High-speed trains (HSTs), Multi-objective optimization, Aerodynamic performance, Parametric model, Kriging model, Genetic algorithm (GA)


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Liang Zhang, Ji-ye Zhang, Tian Li, Ya-dong Zhang. Multi-objective aerodynamic optimization design of high-speed train head shape[J]. Journal of Zhejiang University Science A, 2017, 18(11): 841-854.

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Abstract: 
To improve the aerodynamic performance of high-speed trains (HSTs) running in the open air, a multi-objective aerodynamic optimization design method for the head shape of a HST is proposed in this paper. A parametric model of the HST was established and seven design variables of the head shape were extracted. Sample points and their exact values of optimization objectives were obtained by an optimal Latin hypercube sampling (opt. LHS) plan and computational fluid dynamic (CFD) simulations, respectively. A Kriging surrogate model was constructed based on the sample points and their optimization objectives. Taking the total aerodynamic drag force and the aerodynamic lift force of the tail coach as the optimization objectives, the multi-objective aerodynamic optimization design was performed based on a non-dominated sorting genetic algorithm-II (NSGA-II) and the kriging model. After optimization, a series of Pareto-optimal head shapes were obtained. An optimal head shape was selected from the Pareto-optimal head shapes, and the aerodynamic performance of the HST with the optimal head shape was compared with that of the original train in conditions with and without crosswinds. Compared with the original train, the total aerodynamic drag force is reduced by 2.61% and the lift force of the tail coach is reduced by 9.90% in conditions without crosswind. Moreover, the optimal train benefits from lower fluctuations in aerodynamic loads in crosswind conditions.

This paper used CFD simulations,Kriging surrogate model and NSGA- II to optimize the aerodynamic drag and lift force of a high-speed train. Aerodynamic performance of the original train and optimal train in conditions within and without crosswinds were compared to confirm the improvements.

高速列车头部外形多目标气动优化设计

目的:为改善高速列车明线运行时的气动性能,提出一种基于近似模型的高速列车头部外形多目标气动优化设计方法。
创新点:1. 建立包含转向架区域的高速列车参数化模型;2. 基于近似模型并结合遗传算法,对高速列车头部外形及转向架区域进行多目标气动优化设计。
方法:1. 建立包含转向架区域的原始头型高速列车模型(图2和3),并基于CATIA脚本文件和MATLAB自编程序对列车头部外形进行参数化处理;2. 通过最优拉丁超立方设计方法在设计空间内对优化设计变量进行采样,并采用计算流体动力学方法对样本点中新头型列车气动性能进行计算;3. 基于样本点的列车头型优化设计变量及优化目标(表4),建立优化目标与设计变量之间的近似模型;4. 基于近似模型和多目标遗传算法,对高速列车头部外形进行多目标优化设计,选取其中的一个优化头型与原始头型进行比较,并验证横风下优化头型的可行性。
结论:1. 相较于原始头型列车,无横风时,优化头型列车的整车气动阻力减小2.61%,尾车气动升力减小9.90%;2. 横风下,优化头型列车的整车气动阻力减小2.98%,头车气动侧力减小0.24%;3. 横风下,优化头型列车的头车气动载荷波动幅值有所减小。

关键词:高速列车;多目标优化;气动性能;参数化模型;克里格模型;遗传算法

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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