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Hauptverfasser: Rothermel, Rebecca, Schuster, Thomas
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2503.13284
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author Rothermel, Rebecca
Schuster, Thomas
author_facet Rothermel, Rebecca
Schuster, Thomas
contents The article considers the nonlinear inverse problem of identifying the material parameters in viscoelastic structures based on a generalized Maxwell model. The aim is to reconstruct the model parameters from stress data acquired from a relaxation experiment, where the number of Maxwell elements, and thus the number of material parameters themselves, are assumed to be unknown. This implies that the forward operator acts on a Cartesian product of a semigroup (of integers) and a Hilbert space and demands for an extension of existing regularization theory. We develop a stable reconstruction procedure by applying Bayesian inversion to this setting. We use an appropriate binomial prior which takes the integer setting for the number of Maxwell elements into account and at the same time computes the underlying material parameters. We extend the regularization theory for inverse problems to this special setup and prove existence, stability and convergence of the computed solution. The theoretical results are evaluated by extensive numerical tests.
format Preprint
id arxiv_https___arxiv_org_abs_2503_13284
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bayesian identification of material parameters in viscoelastic structures as an inverse problem in a semigroup setting
Rothermel, Rebecca
Schuster, Thomas
Numerical Analysis
65L09, 74H75
The article considers the nonlinear inverse problem of identifying the material parameters in viscoelastic structures based on a generalized Maxwell model. The aim is to reconstruct the model parameters from stress data acquired from a relaxation experiment, where the number of Maxwell elements, and thus the number of material parameters themselves, are assumed to be unknown. This implies that the forward operator acts on a Cartesian product of a semigroup (of integers) and a Hilbert space and demands for an extension of existing regularization theory. We develop a stable reconstruction procedure by applying Bayesian inversion to this setting. We use an appropriate binomial prior which takes the integer setting for the number of Maxwell elements into account and at the same time computes the underlying material parameters. We extend the regularization theory for inverse problems to this special setup and prove existence, stability and convergence of the computed solution. The theoretical results are evaluated by extensive numerical tests.
title Bayesian identification of material parameters in viscoelastic structures as an inverse problem in a semigroup setting
topic Numerical Analysis
65L09, 74H75
url https://arxiv.org/abs/2503.13284