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    Mesh generation for thin layered domains and its application to parallel multigrid simulation of groundwater flow

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    Type
    Article
    Authors
    Reiter, Sebastian
    Logashenko, Dmitry cc
    Vogel, Andreas cc
    Wittum, Gabriel
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Applied Mathematics and Computational Science Program
    Extreme Computing Research Center
    Date
    2020-04-20
    Online Publication Date
    2020-04-20
    Print Publication Date
    2020-12
    Embargo End Date
    2021-04-20
    Submitted Date
    2017-07-31
    Permanent link to this record
    http://hdl.handle.net/10754/662695
    
    Metadata
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    Abstract
    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/s00791-020-00322-5
    Sponsors
    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 Nature
    Journal
    Computing and Visualization in Science
    DOI
    10.1007/s00791-020-00322-5
    Additional Links
    http://link.springer.com/10.1007/s00791-020-00322-5
    ae974a485f413a2113503eed53cd6c53
    10.1007/s00791-020-00322-5
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; Extreme Computing Research Center; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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