Surrogate-based aerodynamic shape optimization of high-speed train heads: A review of four key technologies

Author:

Wang Hongbo1,Wang Shuangbu2ORCID,Zhuang Dayuan3,Zhu Zaiping4,You Pengcheng1,Tang Zhao3ORCID,Ding Guofu1

Affiliation:

1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China

2. Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, Chengdu, China

3. State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, China

4. The National Centre for Computer Animation, Bournemouth University, Poole, UK

Abstract

With the increase in running speed, the aerodynamic characteristics of high-speed trains have a significant impact on running stability, energy consumption and passenger comfort. Since the shape of the high-speed train head can directly influence the surrounding airflow, optimizing the head shape is the primary way to improve the aerodynamic performance of the train. This paper reviews current research studies on the surrogate-based aerodynamic shape optimization of high-speed train heads, aiming to provide a comprehensive reference for designers to enhance design efficiency and optimization performance. The entire optimization process is divided into four essential steps, and the key optimization technologies in each step are discussed, including parametric modeling, computational fluid dynamics (CFD) simulation, surrogate model and optimization algorithm. By introducing the practical applications of these technologies, we summarize their advantages and disadvantages and suggest four potential research directions for the future.

Funder

Natural Science Foundation of Sichuan Province

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

SAGE Publications

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