Mesh size refining for a simulation of flow around a generic train model
By using numerical simulation, vast and detailed information and observation of the physics of flow over a train model can be obtained. However, the accuracy of the numerical results is questionable as it is affected by grid convergence error. This paper describes a systematic method of computationa...
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| 主要な著者: | , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Techno-Press, Ltd.
2018
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| 主題: | |
| オンライン･アクセス: | http://eprints.uthm.edu.my/4997/1/AJ%202018%20%28808%29%20Mesh%20size%20refining%20for%20a%20simulation%20of%20flow%20around%20a%20generic%20train%20model.pdf http://eprints.uthm.edu.my/4997/ |
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| 要約: | By using numerical simulation, vast and detailed information and observation of the physics of flow over a train model can be obtained. However, the accuracy of the numerical results is questionable as it is affected by grid convergence error. This paper describes a systematic method of computational grid refinement for the Unsteady Reynolds Navier-Stokes (URANS) of flow around a generic model of trains using the OpenFOAM software. The sensitivity of the computed flow field on different mesh resolutions is investigated in this paper. This involves solutions on three different grid refinements, namely fine, medium, and coarse grids to investigate the effect of grid dependency. The level of grid independence is evaluated using a form of Richardson extrapolation and Grid Convergence Index (GCI). This is done by comparing the GCI results of various parameters between different levels of mesh resolutions. In this study, monotonic convergence criteria were achieved, indicating that the grid convergence error was progressively reduced. The fine grid resolution’s GCI value was less than 1%. The results from a simulation of the finest grid resolution, which includes pressure coefficient, drag coefficient and flow visualization, are presented and compared to previous available data. |
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