Oscillation-free numerical schemes for Biot's model and their iterative coupling solution
Álvaro Pé de la Riva, Francisco J. Gaspar, Xiaozhe Hu, James Adler, Carmen Rodrigo, Ludmil Zikatanov
TL;DR
This work tackles non-physical pressure oscillations in Biot's poroelasticity models at low permeability or small time steps by introducing a novel stabilization that does not depend on the mesh size. The stabilization, combined with a fixed-stress–like iterative coupling, yields a convergent, parameter-robust sequential solver for FE discretizations (P1-P1 and MINI) of Biot's model, without requiring additional stabilization for convergence. A thorough one-dimensional analysis (Terzaghi's problem) identifies optimal stabilization and coupling parameters that guarantee two-iteration convergence, with near-optimal performance extending to two- and three-dimensional benchmarks (Barry & Mercer test and a 3D footing problem). The approach also generalizes to broader fluid regimes by introducing a two-parameter coupling scheme, maintaining robustness with respect to discretization and physical parameters. Practically, the method offers stable, efficient solvers for poroelastic simulations across a wide range of settings.
Abstract
In this work, we present a new stabilization method aimed at removing spurious oscillations in the pressure approximation of Biot's model for poroelasticity with low permeabilities and/or small time steps. We consider different finite-element discretizations and illustrate how not only does such a stabilized scheme provide numerical solutions that are free of non-physical oscillations, but it also allows one to iterate the fluid and mechanics problems in a fashion similar to the well-known fixed-stress split method. The resulting solution method is convergent without the necessity for additional terms to stabilize the iteration. Finally, we present numerical results illustrating the robust behavior of both the stabilization and iterative solver with respect to the physical and discretization parameters of the model.
