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Model-Free Data-Driven inelasticity

Eggersmann, R. and Kirchdoerfer, T. and Reese, S. and Stainier, L. and Ortiz, M. (2019) Model-Free Data-Driven inelasticity. Computer Methods in Applied Mechanics and Engineering, 350 . pp. 81-99. ISSN 0045-7825. http://resolver.caltech.edu/CaltechAUTHORS:20190304-093042764

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Abstract

We extend the Data-Driven formulation of problems in elasticity of Kirchdoerfer and Ortiz (2016) to inelasticity. This extension differs fundamentally from Data-Driven problems in elasticity in that the material data set evolves in time as a consequence of the history dependence of the material. We investigate three representational paradigms for the evolving material data sets: (i) materials with memory, i. e., conditioning the material data set to the past history of deformation; (ii) differential materials, i. e., conditioning the material data set to short histories of stress and strain; and (iii) history variables, i. e., conditioning the material data set to ad hoc variables encoding partial information about the history of stress and strain. We also consider combinations of the three paradigms thereof and investigate their ability to represent the evolving data sets of different classes of inelastic materials, including viscoelasticity, viscoplasticity and plasticity. We present selected numerical examples that demonstrate the range and scope of Data-Driven inelasticity and the numerical performance of implementations thereof.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.cma.2019.02.016DOIArticle
ORCID:
AuthorORCID
Stainier, L.0000-0001-6719-6616
Additional Information:© 2019 Elsevier. Received 9 September 2018, Revised 26 December 2018, Accepted 10 February 2019, Available online 1 March 2019. MO gratefully acknowledges the support of the Deutsche Forschungsgemeinschaft (DFG) through the Sonderforschungsbereich 1060 “The mathematics of emergent effects”. SR and RE gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG) through the project “Model order reduction in space and parameter dimension — towards damage-based modeling of polymorphic uncertainty in the context of robustness and reliability” within the priority programme SPP 1886 “Polymorphic uncertainty modelling for the numerical design of structures”.
Group:GALCIT
Funders:
Funding AgencyGrant Number
Deutsche Forschungsgemeinschaft (DFG)Sonderforschungsbereich 1060
Deutsche Forschungsgemeinschaft (DFG)SPP 1886
Subject Keywords:Data-Driven computing; Inelasticity; Viscoelasticity; Plasticity
Record Number:CaltechAUTHORS:20190304-093042764
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190304-093042764
Official Citation:R. Eggersmann, T. Kirchdoerfer, S. Reese, L. Stainier, M. Ortiz, Model-Free Data-Driven inelasticity, Computer Methods in Applied Mechanics and Engineering, Volume 350, 2019, Pages 81-99, ISSN 0045-7825, https://doi.org/10.1016/j.cma.2019.02.016. (http://www.sciencedirect.com/science/article/pii/S0045782519300878)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93425
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:04 Mar 2019 17:48
Last Modified:20 Mar 2019 15:38

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