A method for determining the parameters in a rheological model for viscoelastic materials by minimizing Tikhonov functionals
Rebecca Rothermel, Wladimir Panfilenko, Prateek Sharma, Anne Wald,, Thomas Schuster, Anne Jung, and Stefan Diebels

TL;DR
This paper introduces a novel method for identifying parameters in a viscoelastic rheological model using Tikhonov functional minimization, incorporating a clustering algorithm to determine the number of Maxwell elements from relaxation data.
Contribution
It presents a new approach combining Tikhonov regularization and clustering to accurately identify Maxwell model parameters from relaxation experiments, even with noisy or limited data.
Findings
Effective parameter reconstruction with noisy data
Clustering algorithm resolves the number of Maxwell elements
Shortened data sets still yield reliable parameters
Abstract
Mathematical models describing the behavior of viscoelastic materials are often based on evolution equations that measure the change in stress depending on its material parameters such as stiffness, viscosity or relaxation time. In this article, we introduce a Maxwell-based rheological model, define the associated forward operator and the inverse problem in order to determine the number of Maxwell elements and the material parameters of the underlying viscoelastic material. We perform a relaxation experiment by applying a strain to the material and measure the generated stress. Since the measured data varies with the number of Maxwell elements, the forward operator of the underlying inverse problem depends on parts of the solution. By introducing assumptions on the relaxation times, we propose a clustering algorithm to resolve this problem. We provide the calculations that are necessary…
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Taxonomy
TopicsProbabilistic and Robust Engineering Design · Rheology and Fluid Dynamics Studies · Composite Material Mechanics
