Convergence Properties of Iteratively Coupled Surface-Subsurface Models

Fuente: arXiv
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Main Authors: Schüller, Valentina, Birken, Philipp, Dedner, Andreas
Format: Preprint
Published: 2024
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author Schüller, Valentina
Birken, Philipp
Dedner, Andreas
author_facet Schüller, Valentina
Birken, Philipp
Dedner, Andreas
contents Surface-subsurface flow models for hydrological applications solve a coupled multiphysics problem. This usually consists of some form of the Richards and shallow water equations. A typical setup couples these two nonlinear partial differential equations in a partitioned approach via boundary conditions. Full interaction between the subsolvers is ensured by an iterative coupling procedure. This can be accelerated using relaxation. In this paper, we apply continuous and fully discrete linear analysis techniques to study an idealized, linear, 1D-0D version of a surface-subsurface model. These result in explicit expressions for the convergence factor and an optimal relaxation parameter, depending on material and discretization parameters. We test our analysis results numerically for fully nonlinear 2D-1D experiments based on existing benchmark problems. The linear analysis can explain fast convergence of iterations observed in practice for different materials and test cases, even though we are not able to capture various nonlinear effects.
format Preprint
id arxiv_https___arxiv_org_abs_2408_12582
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence Properties of Iteratively Coupled Surface-Subsurface Models
Schüller, Valentina
Birken, Philipp
Dedner, Andreas
Numerical Analysis
65M22
G.1.8
Surface-subsurface flow models for hydrological applications solve a coupled multiphysics problem. This usually consists of some form of the Richards and shallow water equations. A typical setup couples these two nonlinear partial differential equations in a partitioned approach via boundary conditions. Full interaction between the subsolvers is ensured by an iterative coupling procedure. This can be accelerated using relaxation. In this paper, we apply continuous and fully discrete linear analysis techniques to study an idealized, linear, 1D-0D version of a surface-subsurface model. These result in explicit expressions for the convergence factor and an optimal relaxation parameter, depending on material and discretization parameters. We test our analysis results numerically for fully nonlinear 2D-1D experiments based on existing benchmark problems. The linear analysis can explain fast convergence of iterations observed in practice for different materials and test cases, even though we are not able to capture various nonlinear effects.
title Convergence Properties of Iteratively Coupled Surface-Subsurface Models
topic Numerical Analysis
65M22
G.1.8
url https://arxiv.org/abs/2408.12582