高性能并行CFD软件研发及高速列车气动性能预示

doi:10.11871/jfdc.issn.2096-742X.2023.02.009

数据与计算发展前沿 ›› 2023, Vol. 5 ›› Issue (2): 106-118.

CSTR: 32002.14.jfdc.CN10-1649/TP.2023.02.009

doi: 10.11871/jfdc.issn.2096-742X.2023.02.009

高性能并行CFD软件研发及高速列车气动性能预示

张新昕^1,²(),刘夏真^1,^*(),梁姗¹,张鉴^1,²,陆忠华^1,²,高凌云^1,²,张浩源^1,²

1.中国科学院计算机网络信息中心，北京 100083
2.中国科学院大学，北京 100049

收稿日期:2022-03-02 出版日期:2023-04-20 发布日期:2023-04-24
通讯作者: 刘夏真
作者简介:张新昕，中国科学院计算机网络信息中心，博士研究生，主要研究方向为高性能计算中的算法开发与优化，以及高性能计算在计算流体力学中的应用。
本文承担工作为：CCFD v3.0在高速列车仿真实验中的测试。
ZHANG Xinxin is a Ph.D. candidate at CNIC. His activities mainly focus on algorithm development and optimization in high-performance computation, and the application of high-performance computation in computational fluid dynamics.
In this paper, he is mainly responsible for test of CCFD v3.0 in the experiment of the high-speed railway.
E-mail: zhangxinxin@cnic.cn|刘夏真，中国科学院计算机网络信息中心，博士，工程师，主要研究方向为高性能计算、计算流体力学。
本文承担工作为：CCFD v3.0在国产加速器上的移植与优化，以及高速列车仿真实验中的测试。
LIU Xiazhen, Ph.D., is an engineer at CNIC. He works in high-performance computation and comp-utational fluid dynamics.
In this paper, he is mainly responsible for transplantation, optimization of the CCFD V3.0 program on domestic proce-ssors and testing of CCFD v3.0 in the experiment of the high-speed railway.
E-mail: liuxz@sccas.cn
基金资助:
国家重点研发计划“面向复杂装备的CAE云服务平台研发”项目(2020YFB1709500)

Development of High-Performance Parallel CFD Software and Aerodynamic Performance Prediction of High-Speed Trains

ZHANG Xinxin^1,²(),LIU Xiazhen^1,^*(),LIANG Shan¹,ZHANG Jian^1,²,LU Zhonghua^1,²,GAO Lingyun^1,²,ZHANG Haoyuan^1,²

1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China
2. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2022-03-02 Online:2023-04-20 Published:2023-04-24
Contact: LIU Xiazhen

摘要/Abstract

摘要：

【应用背景】面向高速列车在复杂场景中的气动性能仿真与气动外形优化问题，以提高仿真精度与并行计算效率为目的。【方法】自主研发了高性能流体力学计算软件CCFD v3.0，开发了高精度NS方程空间离散算法、高效线性代数求解、湍流模拟、网格并行处理等核心功能模块，并移植到了两款国产异构超算平台，分别针对性地开展了深度并行计算优化。【结果】CCFD v3.0的计算结果表明，在高速列车头部外形中，底阻和摩阻是列车行驶中的最主要阻力来源，分别占比71%与23%；而车体的阻力构成则为摩阻占比89%，型阻占比11%。【结论】CCFD v3.0表现出了良好的并行加速效果，实现了高速列车的气动性能预示与流场机理分析。

关键词: 高性能计算, CCFD v3.0, 并行优化, 高速列车, 气动性能

Abstract:

[Application Background] For aerodynamic performance simulation and aerodynamic shape optimization of high-speed trains in complex scenes, the goal of our work is to improve the simulation accuracy and parallel computing efficiency. [Methods] A high-performance computational fluid dynamics software CCFD v3.0 is independently developed, and the core functional modules such as high-precision NS equation space-discrete algorithm, efficient linear algebra solution, turbulence simulation, and parallel grid processing are developed. It has been ported to two domestic heterogeneous supercomputing platforms and specifically optimized for parallel computing. [Results] The computational results delivered by CCFD v3.0 show that the head shape of the high-speed trains, the bottom resistance and friction are the main sources of resistance of the train in running, accounting for 71% and 23%, respectively. The 89% of the resistance of the trains carriages comes from friction and 11% from form drag. [Conclusions] CCFD v3.0 achieves good parallel acceleration in prediction of the aerodynamic performance of the high-speed trains and analysis of the flow field mechanism.

Key words: high-performance computing, CCFD v3.0, parallel optimization, high-speed train, aerodynamic performance

张新昕,刘夏真,梁姗,张鉴,陆忠华,高凌云,张浩源. 高性能并行CFD软件研发及高速列车气动性能预示[J]. 数据与计算发展前沿, 2023, 5(2): 106-118.

ZHANG Xinxin,LIU Xiazhen,LIANG Shan,ZHANG Jian,LU Zhonghua,GAO Lingyun,ZHANG Haoyuan. Development of High-Performance Parallel CFD Software and Aerodynamic Performance Prediction of High-Speed Trains[J]. Frontiers of Data and Computing, 2023, 5(2): 106-118, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2023.02.009.

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高性能并行CFD软件研发及高速列车气动性能预示

Development of High-Performance Parallel CFD Software and Aerodynamic Performance Prediction of High-Speed Trains

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