Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties

Alexander Litvinenko; Dmitry Logashenko; Raul Tempone; Gabriel Wittum; David E. Keyes

doi:10.1002/pamm.201900023

Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties

Alexander Litvinenko, Dmitry Logashenko, Raul Tempone, Gabriel Wittum, David E. Keyes

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English (US)
Journal	PAMM
Volume	19
Issue number	1
DOIs	https://doi.org/10.1002/pamm.201900023
State	Published - Nov 18 2019

Bibliographical note

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.

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10.1002/pamm.201900023

https://repository.kaust.edu.sa/bitstream/10754/668757/1/pamm.201900023.pdf

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title = "Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties",

abstract = "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.",

author = "Alexander Litvinenko and Dmitry Logashenko and Raul Tempone and Gabriel Wittum and Keyes, {David E.}",

note = "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.",

year = "2019",

month = nov,

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doi = "10.1002/pamm.201900023",

language = "English (US)",

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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

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DO - 10.1002/pamm.201900023

M3 - Article

SN - 1617-7061

VL - 19

JO - PAMM

JF - PAMM

IS - 1

ER -

Efficient Simulations for Contamination of Groundwater Aquifers under Uncertainties

Abstract

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