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A Scalable Numerical Method for Simulating Flows Around High-Speed Train Under Crosswind Conditions

Published online by Cambridge University Press:  03 June 2015

Zhengzheng Yan ,
Rongliang Chen ,
Yubo Zhao  and
Xiao-Chuan Cai
Zhengzheng Yan*
Affiliation:
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
Rongliang Chen*
Affiliation:
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
Yubo Zhao*
Affiliation:
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, P.R. China
Xiao-Chuan Cai*
Affiliation:
Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA
*
Email:zz.yan@siat.ac.cn
Email:rl.chen@siat.ac.cn
Email:yb.zhao@siat.ac.cn
Corresponding author.Email:cai@cs.colorado.edu
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Abstract

This paper presents a parallel Newton-Krylov-Schwarz method for the numerical simulation of unsteady flows at high Reynolds number around a high-speed train under crosswind. With a realistic train geometry, a realistic Reynolds number, and a realistic wind speed, this is a very challenging computational problem. Because of the limited parallel scalability, commercial CFD software is not suitable for supercomputers with a large number of processors. We develop a Newton-Krylov-Schwarz based fully implicit method, and the corresponding parallel software, for the 3D unsteady incompressible Navier-Stokes equations discretized with a stabilized finite element method on very fine unstructured meshes. We test the algorithm and software for flows passing a train modeled after China’s high-speed train CRH380B, and we also compare our results with results obtained from commercial CFD software. Our algorithm shows very good parallel scalability on a supercomputer with over one thousand processors.

Keywords

76D0576F6565M5565Y05Three-dimensional unsteady incompressible flowshigh-speed traincrosswindfull Navier-Stokes equationsNewton-Krylov-Schwarz algorithmparallel computing
Type
Research Article
Information
Communications in Computational Physics , Volume 15 , Issue 4 , April 2014 , pp. 944 - 958
Copyright
Copyright © Global Science Press Limited 2014

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