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Vehicle Aerodynamics Simulation for the Next Generation on the K Computer: Part 2 Use of Dirty CAD Data with Modified Cartesian Grid Approach
ISSN: 1946-3995, e-ISSN: 1946-4002
Published April 01, 2014 by SAE International in United States
Citation: Onishi, K., Tsubokura, M., Obayashi, S., and Nakahashi, K., "Vehicle Aerodynamics Simulation for the Next Generation on the K Computer: Part 2 Use of Dirty CAD Data with Modified Cartesian Grid Approach," SAE Int. J. Passeng. Cars - Mech. Syst. 7(2):528-537, 2014, https://doi.org/10.4271/2014-01-0580.
The applicability of high-performance computing (HPC) to vehicle aerodynamics is presented using a Cartesian grid approach of computational fluid dynamics. Methodology that allows the user to avoid a large amount of manual work in preparing geometry is indispensable in HPC simulation whereas conventional methodologies require much manual work. The new frame work allowing a solver to treat ‘dirty’ computer-aided-design data directly was developed with a modified immersed boundary method. The efficiency of the calculation of the vehicle aerodynamics using HPC is discussed.
The validation case of flow with a high Reynolds number around a sphere is presented. The preparation time for the calculation is approximately 10 minutes. The calculation time for flow computation is approximately one-tenth of that of conventional unstructured code. Results of large eddy simulation with a coarse grid differ greatly from experimental results, but there is an improvement in the prediction of the drag coefficient prediction when using 23 billion cells.
A vehicle aerodynamics simulation was conducted using dirty computer-aided-design data and approximately 19 billion cells. The preparation for the calculation can be completed within a couple of hours. The calculation time for flow computation is approximately one-fifth of that of conventional unstructured code. Reasonable flow results around a vehicle were observed, and there is an improvement in the prediction of the drag coefficient prediction when using 19 billion cells. The possibility of the proposed methodology being an innovative scheme in computational fluid dynamics is shown.