2019/05/06 by Alexander Litvinenko, Litvinenko, Alexander, Dmitry Logashenko +7 · 1 citation
Decision Sciences · Earth and Planetary Sciences · Environmental Science · #Applications (stat.AP) #FOS: Computer and information sciences #FOS: Mathematics #Meteorological Phenomena and Simulations #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design #Wind and Air Flow Studies
paper · pdf · doi:10.48550/arxiv.1905.01770
openalex publication_date 2019/05/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 subsurface flow. Specifically, we consider the density-driven flow and estimate how uncertainty from permeability and porosity propagates to the solution. We take an Elder-like problem as a numerical benchmark and we use random fields to model the limited knowledge on the porosity and permeability. We construct a low-cost generalized polynomial chaos expansion (gPC) surrogate model, where the gPC coefficients are computed by projection on sparse and full tensor grids. We parallelize both the numerical solver for the deterministic problem based on the multigrid method, and the quadrature over the parametric space