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Efficient surface water flow simulation on static Cartesian grid with local refinement according to key topographic features
journal contributionposted on 2019-01-14, 13:27 authored by Jingming Hou, Run Wang, Qiuhua LiangQiuhua Liang, Zhanbin Li, Mian Song Huang, Reihnard Hinkelmann
Aiming at improving the computational efficiency without accuracy losses for surface water flow simulation, this paper presents a structured but non-uniform grid system incorporated into a Godunov-type finite volume scheme. The proposed grid system can detect the key topographic features in the computational domain where high-resolution mesh is in need for reliably solving the shallow water equations. The mesh refinement is automatically carried out in these areas while the mesh in the rest of the domain remains coarse. The criterion determining the refinement is suggested by a dimensionless number with a fixed value of 0.2 after sensitivity analysis. Three laboratory and field-scale test cases are employed to demonstrate the performance of the model for flow simulations on the new non-uniform grids. In all of the tests, the grid system is shown to successfully generate high-resolution mesh only in those areas with abruptly changing topographic features that dominate the flooding processes. To produce numerical solutions of similar accuracy, the non-uniform grid based model is able to accelerate by about two times comparing with the fine uniform grid based counterpart.
This work is partly supported by the National Natural Science Foundation of China (19672016); State Key Program of National Natural Science Foundation of China (grant no. 41330858) ; Natural Science Foundation of Qinghai Province (grant no. 2015-ZJ-936Q) and the UK Natural Environment Research Council (NERC) (grant no. NE/K008781/1).
- Architecture, Building and Civil Engineering
Published inComputers & Fluids
Pages117 - 134
CitationHOU, J. ... et al, 2018. Efficient surface water flow simulation on static Cartesian grid with local refinement according to key topographic features. Computers & Fluids, 176, pp.117-134.
- AM (Accepted Manuscript)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesThis paper was published in the journal Computers & Fluids and the definitive published version is available at https://doi.org/10.1016/j.compfluid.2018.03.024.