{"ID":2824681,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.23027","arxiv_id":"2512.23027","title":"A Domain Decomposition-based Solver for Acoustic Wave propagation in Two-Dimensional Random Media","abstract":"An acoustic wave propagation problem with a log normal random field approximation for wave speed is solved using a sampling-free intrusive stochastic Galerkin approach. The stochastic partial differential equation with the inputs and outputs expanded using polynomial chaos expansion (PCE) is transformed into a set of deterministic PDEs and further to a system of linear equations. Domain decomposition (DD)-based solvers are utilized to handle the overwhelming computational cost for the resulting system with increasing mesh size, time step and number of random parameters. A conjugate gradient iterative solver with a two-level Neumann-Neumann preconditioner is applied here showing their efficient scalabilities.","short_abstract":"An acoustic wave propagation problem with a log normal random field approximation for wave speed is solved using a sampling-free intrusive stochastic Galerkin approach. The stochastic partial differential equation with the inputs and outputs expanded using polynomial chaos expansion (PCE) is transformed into a set of d...","url_abs":"https://arxiv.org/abs/2512.23027","url_pdf":"https://arxiv.org/pdf/2512.23027v2","authors":"[\"Sudhi Sharma Padillath Vasudevan\"]","published":"2025-12-28T18:02:08Z","proceeding":"cs.CE","tasks":"[\"cs.CE\",\"cs.DC\",\"math.NA\"]","methods":"[]","has_code":false}