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

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

Abstract

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

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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