Abstract
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.
Highlights
Plan: 1. Density-driven groundwater flow problem 2
As groundwater is an essential nutrition and irrigation resource, its pollution may lead to catastrophic consequences
Use well-known model, see [1,2,3]: Domain D is filled with two phases: solid porous matrix and solution of salt in water
Summary
Major Goal: estimate propagation of uncertainties in the density-driven groundwater flow.
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