Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties
KAUST DepartmentApplied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Extreme Computing Research Center
Office of the President
Stochastic Numerics Research Group
Permanent link to this recordhttp://hdl.handle.net/10754/668757
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AbstractAccurate modeling of contamination in subsurface flow and water aquifers is crucial for agriculture and environmental protection. Here, we demonstrate a parallel method to quantify the propagation of the uncertainty in the dispersal of pollution in density-driven flow. We solve an Elder-like problem, where we use random fields to model the limited knowledge on the porosity and permeability. The uncertain solution, mass fraction, is approximated via low-cost generalized polynomial chaos expansion (gPCE). Parallelization is done in both the physical and parametric spaces.
CitationLitvinenko, A., Logashenko, D., Tempone, R., Wittum, G., & Keyes, D. (2019). Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties. PAMM, 19(1). doi:10.1002/pamm.201900023
SponsorsThis work was supported by the King Abdullah University of Science and Technology (KAUST) and by the Alexan-der von Humboldt Foundation. We used the resources of the Supercomputing Laboratory at KAUST, under the development project k1051.
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