Model-data-driven constitutive responses

Application to a multiscale computational framework

verfasst von
Jan Niklas Fuhg, Christoph Böhm, Nikolaos Bouklas, Amelie Fau, Peter Wriggers, Michele Marino
Abstract

Computational multiscale methods for analyzing and deriving constitutive responses have been used as a tool in engineering problems because of their ability to combine information at different length scales. However, their application in a nonlinear framework can be limited by high computational costs, numerical difficulties, and/or inaccuracies. In this paper, a hybrid methodology is presented which combines classical constitutive laws (model-based), a data-driven correction component, and computational multiscale approaches. A model-based material representation is locally improved with data from lower scales obtained by means of a nonlinear numerical homogenization procedure, leading to a model-data-driven approach. Therefore, macroscale simulations explicitly incorporate the true microscale response, maintaining the same level of accuracy that would be obtained with online micro-macro simulations but with a computational cost comparable to classical model-driven approaches. In the proposed approach, both model and data play a fundamental role allowing for the synergistic integration between a physics-based response and a machine learning black-box. Numerical applications are implemented in two dimensions for different tests investigating both material and structural responses in large deformations. Overall, the presented model-data-driven methodology proves to be more versatile and accurate than methods based on classical model-driven, as well as pure data-driven techniques. In particular, a lower number of training samples is required and robustness is higher than for simulations which solely rely on data.

Organisationseinheit(en)
Institut für Kontinuumsmechanik
Externe Organisation(en)
Universität Paris-Saclay
Università degli studi di Roma Tor Vergata
Cornell University
Typ
Artikel
Journal
International Journal of Engineering Science
Band
167
ISSN
0020-7225
Publikationsdatum
01.10.2021
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Werkstoffwissenschaften (insg.), Ingenieurwesen (insg.), Werkstoffmechanik, Maschinenbau
Elektronische Version(en)
https://arxiv.org/abs/2104.02650 (Zugang: Offen)
https://doi.org/10.1016/j.ijengsci.2021.103522 (Zugang: Geschlossen)
 

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