FE r method with surrogate localization model for hyperelastic composite materials

Ryo Hatano, Seishiro Matsubara, Shuji Moriguchi, Kenjiro Terada, Julien Yvonnet

Research output: Contribution to journalArticlepeer-review

Abstract

This study presents a method for constructing a surrogate localization model for a periodic microstructure, or equivalently, a unit cell, to efficiently perform micro-macro coupled analyses of hyperelastic composite materials. The offline process in this approach is to make a response data matrix that stores the microscopic stress distributions in response to various patterns of macroscopic deformation gradients, which is followed by the proper orthogonal decomposition (POD) of the matrix to construct a reduced order model (ROM) of the microscopic analysis (localization) with properly extracted POD bases. Then, response surfaces of the POD coefficients are constructed so that the ROM can be continuous with respect to the input datum, namely, the macroscopic deformation gradient. The novel contributions of this study are the application of the L2 regularization to the interpolation approximations of the POD coefficients by use of radial basis functions (RBFs) to make the response surfaces continuous and the combined use of the cross-validation and the Bayesian optimization to search for the optimal set of parameters in both the RBFs and L2regularization formula. The resulting model can be an alternative to microscopic finite element (FE) analyses in the conventional FE 2 method and realizes FE r with 1 < r< < 2 accordingly. Representative numerical examples of micro-macro coupled analysis with the FE r are presented to demonstrate the capability and promise of the surrogate localization model constructed with the proposed approach in comparison with the results with high-fidelity direct FE 2.

Original languageEnglish
Article number39
JournalAdvanced Modeling and Simulation in Engineering Sciences
Volume7
Issue number1
DOIs
Publication statusPublished - 2020 Dec 1

Keywords

  • Hyperelastic composites
  • L2 Regularization
  • Micro-macro coupled analysis
  • Proper orthogonal decomposition
  • Radial basis function interpolation

ASJC Scopus subject areas

  • Modelling and Simulation
  • Engineering (miscellaneous)
  • Computer Science Applications
  • Applied Mathematics

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