TY - JOUR
T1 - Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties
AU - Litvinenko, Alexander
AU - Logashenko, Dmitry
AU - Tempone, Raul
AU - Wittum, Gabriel
AU - Keyes, David E.
N1 - KAUST Repository Item: Exported on 2021-04-16
Acknowledgements: This 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.
PY - 2019/11/18
Y1 - 2019/11/18
N2 - Accurate 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.
AB - Accurate 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.
UR - http://hdl.handle.net/10754/668757
UR - https://onlinelibrary.wiley.com/doi/10.1002/pamm.201900023
U2 - 10.1002/pamm.201900023
DO - 10.1002/pamm.201900023
M3 - Article
SN - 1617-7061
VL - 19
JO - PAMM
JF - PAMM
IS - 1
ER -