Adaptive space-time model order reduction with dual-weighted residual (MORe DWR) error control for poroelasticity

Abstract In this work, the space-time MORe DWR (Model Order Reduction with Dual-Weighted Residual error estimates) framework is extended and further developed for single-phase flow problems in porous media. Specifically, our problem statement is the Biot system which consists of vector-valued displa...

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Bibliographic Details
Main Authors: Hendrik Fischer, Julian Roth, Ludovic Chamoin, Amélie Fau, Mary Wheeler, Thomas Wick
Format: Article
Language:English
Published: SpringerOpen 2024-04-01
Series:Advanced Modeling and Simulation in Engineering Sciences
Online Access:https://doi.org/10.1186/s40323-024-00262-6
Description
Summary:Abstract In this work, the space-time MORe DWR (Model Order Reduction with Dual-Weighted Residual error estimates) framework is extended and further developed for single-phase flow problems in porous media. Specifically, our problem statement is the Biot system which consists of vector-valued displacements (geomechanics) coupled to a Darcy flow pressure equation. The MORe DWR method introduces a goal-oriented adaptive incremental proper orthogonal decomposition (POD) based-reduced-order model (ROM). The error in the reduced goal functional is estimated during the simulation, and the POD basis is enriched on-the-fly if the estimate exceeds a given threshold. This results in a reduction of the total number of full-order-model solves for the simulation of the porous medium, a robust estimation of the quantity of interest and well-suited reduced bases for the problem at hand. We apply a space-time Galerkin discretization with Taylor-Hood elements in space and a discontinuous Galerkin method with piecewise constant functions in time. The latter is well-known to be similar to the backward Euler scheme. We demonstrate the efficiency of our method on the well-known two-dimensional Mandel benchmark and a three-dimensional footing problem.
ISSN:2213-7467