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Parameter identification and uncertainty propagation of hydrogel coupled diffusion-deformation using POD-based reduced-order modeling

  • Gopal Agarwal
  • , Jorge Humberto Urrea-Quintero
  • , Henning Wessels
  • , Thomas Wick

Research output: Contribution to journalArticleResearchpeer review

Abstract

This study explores reduced-order modeling for analyzing time-dependent diffusion-deformation of hydrogels. The full-order model describing hydrogel transient behavior consists of a coupled system of partial differential equations in which the chemical potential and displacements are coupled. This system is formulated in a monolithic fashion and solved using the finite element method. We employ proper orthogonal decomposition as a model order reduction approach. The reduced-order model performance is tested through a benchmark problem on hydrogel swelling and a case study simulating co-axial printing. Then, we embed the reduced-order model into an optimization loop to efficiently identify the coupled problem’s material parameters using full-field data. Finally, a study is conducted on the uncertainty propagation of the material parameter.

Original languageEnglish
Pages (from-to)515–545
Number of pages31
JournalComputational mechanics
Volume75
E-pub ahead of print8 Jul 2024
DOIs
Publication statusPublished - Feb 2025

Keywords

  • FEniCS
  • Hydrogels modeling
  • Model material parameters identification
  • Model-order reduction
  • Proper orthogonal decomposition
  • RBniCS
  • Uncertainty propagation

ASJC Scopus subject areas

  • Computational Mechanics
  • Ocean Engineering
  • Mechanical Engineering
  • Computational Theory and Mathematics
  • Computational Mathematics
  • Applied Mathematics

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