Mesh generation for thin layered domains and its application to parallel multigrid simulation of groundwater flow
Type
ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionApplied Mathematics and Computational Science Program
Extreme Computing Research Center
Date
2020-04-20Online Publication Date
2020-04-20Print Publication Date
2020-12Embargo End Date
2021-04-20Submitted Date
2017-07-31Permanent link to this record
http://hdl.handle.net/10754/662695
Metadata
Show full item recordAbstract
The generation of detailed three dimensional meshes for the simulation of groundwater flow in thin layered domains is crucial to capture important properties of the underlying domains and to reach a satisfying accuracy. At the same time, this level of detail poses high demands both on suitable hardware and numerical solver efficiency. Parallel multigrid methods have been shown to exhibit near optimal weak scalability for massively parallel computations of density driven flow. A fully automated parameterized algorithm for prism based meshing of coarse grids from height data of individual layers is presented. Special structures like pinch outs of individual layers are preserved. The resulting grid is used as a starting point for parallel mesh and hierarchy creation through interweaved projected refinement and redistribution. Efficiency and applicability of the proposed approach are demonstrated for a parallel multigrid based simulation of a realistic sample problem.Citation
Reiter, S., Logashenko, D., Vogel, A., & Wittum, G. (2020). Mesh generation for thin layered domains and its application to parallel multigrid simulation of groundwater flow. Computing and Visualization in Science, 23(1-4). doi:10.1007/s00791-020-00322-5Sponsors
This work has been supported by the German Ministry of Economics and Technology (BMWi, 02E11476B) and by the DFG Priority Program 1648 Software for Exascale Computing (SPPEXA) in the project Exasolvers (WI 1037/24-2). We thank the HLRS for the opportunity to use Hazel Hen and their kind support. The authors also gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time through the John von Neumann Institute for Computing (NIC) on the GCS Supercomputer JUQUEEN at Jülich Supercomputing Centre (JSC).Publisher
Springer NatureAdditional Links
http://link.springer.com/10.1007/s00791-020-00322-5ae974a485f413a2113503eed53cd6c53
10.1007/s00791-020-00322-5