Show simple item record

dc.contributor.authorLitvinenko, Alexander
dc.contributor.authorLogashenko, Dmitry
dc.contributor.authorTempone, Raul
dc.contributor.authorWittum, Gabriel
dc.contributor.authorKeyes, David E.
dc.date.accessioned2019-06-10T06:25:10Z
dc.date.available2019-06-10T06:25:10Z
dc.date.issued2019-06-01
dc.identifier.urihttp://hdl.handle.net/10754/655509
dc.description.abstractAs groundwater is an essential nutrition and irrigation resource, its pollution may lead to catastrophic consequences. Therefore, accurate modeling of the pollution of the soil and groundwater aquifer is highly important. As a model, we consider a density-driven groundwater flow problem with uncertain porosity and permeability. This problem may arise in geothermal reservoir simulation, natural saline-disposal basins, modeling of contaminant plumes, and subsurface flow. This strongly nonlinear time-dependent problem describes the convection of the two-phase flow. This liquid streams under the gravity force, building so-called ``fingers''. The accurate numerical solution requires fine spatial resolution with an unstructured mesh and, therefore, high computational resources. Consequently, we run the parallelized simulation toolbox \myug with the geometric multigrid solver on Shaheen II supercomputer. The parallelization is done in physical and stochastic spaces. Additionally, we demonstrate how the \myug toolbox can be run in a black-box fashion for testing different scenarios in the density-driven flow. As a benchmark, we solve the Elder-like problem in a 3D domain. For approximations in the stochastic space, we use the generalized polynomial chaos expansion. We compute the mean, variance, and exceedance probabilities of the mass fraction. As a reference solution, we use the solution, obtained from the quasi-Monte Carlo method.
dc.description.sponsorshipWe would like to thank KAUST HPC support team for the assistance with Shaheen II. This work was supported by the Extreme Computing Research Center, by the SRI-UQ Strategic Initiative and by Computational Bayesian group at King Abdullah University of Science and Technology.
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/abs/1906.01632
dc.relation.urlhttps://arxiv.org/pdf/1906.01632
dc.rightsArchived with thanks to arXiv
dc.subjectug4
dc.subjectuncertainty quantification
dc.subjectmultigrid
dc.subjectparallel
dc.subjectdensity driven flow
dc.subjectreservoir
dc.subjectgroundwater
dc.subjectsalt formations
dc.titleSolution of the 3D density-driven groundwater flow problem with uncertain porosity and permeability
dc.typePreprint
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentExtreme Computing Research Center
dc.contributor.departmentKAUST, Thuwal/Jeddah, Saudi Arabia
dc.eprint.versionPre-print
dc.contributor.institutionRWTH Aachen, Kackertstr. 9C, Aachen, Germany
dc.contributor.institutionG-CSC, Frankfurt University, Kettenhofweg 139, Frankfurt, Germany
dc.identifier.arxividarXiv:1906.01632
kaust.personLogashenko, Dmitry
kaust.personTempone, Raul
kaust.personWittum, Gabriel
kaust.personKeyes, David E.
refterms.dateFOA2019-06-10T06:25:11Z


Files in this item

Thumbnail
Name:
submitted2Arxiv.pdf
Size:
6.645Mb
Format:
PDF
Description:
Preprint

This item appears in the following Collection(s)

Show simple item record