A note on constitutive artificial neural networks for finite strain plasticity

van der Velden T, Boes B, Brepols T, Kuhl E, Holthusen H (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Mechanics Research Communications Elsevier

Book Volume: 155

Article Number: 104707

DOI: 10.1016/j.mechrescom.2026.104707

Abstract

Data-driven approaches have led to structured constitutive artificial neural network formulations for inelastic phenomena such as viscoelasticity and growth, while the systematic extension to finite-strain plasticity remains an active area of research. In this communication, we extend the previously introduced inelastic constitutive artificial neural network framework to finite-strain elasto-visco-plasticity with combined nonlinear kinematic and isotropic hardening. The proposed formulation ensures thermodynamic consistency within a potential-based architecture by consistently integrating isotropic hardening and viscoplastic evolution mechanisms. In particular, a shared inelastic potential is employed for linear kinematic and isotropic hardening, while two additional potentials govern nonlinear kinematic hardening and the plastic yield function, enabling the modeling of non-associative plasticity. A JAX implementation of the extended framework and the associated simulation results are publicly available at Zenodo.org.

Authors with CRIS profile

Ellen Kuhl Lehrstuhl für Technische Mechanik (LTM) Hagen Holthusen Lehrstuhl für Technische Mechanik (LTM)

Involved external institutions

Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen DE Germany (DE) Bergische Universität Wuppertal DE Germany (DE)

How to cite

APA:

van der Velden, T., Boes, B., Brepols, T., Kuhl, E., & Holthusen, H. (2026). A note on constitutive artificial neural networks for finite strain plasticity. Mechanics Research Communications, 155. https://doi.org/10.1016/j.mechrescom.2026.104707

MLA:

van der Velden, Tim, et al. "A note on constitutive artificial neural networks for finite strain plasticity." Mechanics Research Communications 155 (2026).

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