Physics-informed neural networks for modeling rate-and temperature-dependent plasticity
This work presents a physics-informed neural network (PINN) based framework to model the
strain-rate and temperature dependence of the deformation fields in elastic-viscoplastic …
strain-rate and temperature dependence of the deformation fields in elastic-viscoplastic …
Non-local large-strain FFT-based formulation and its application to interface-dominated plasticity of nano-metallic laminates
This paper presents a novel formulation and its robust numerical implementation of strain-
gradient (SG) crystal plasticity within a large-strain (LS) elasto-viscoplastic (EVP) fast Fourier …
gradient (SG) crystal plasticity within a large-strain (LS) elasto-viscoplastic (EVP) fast Fourier …
[HTML][HTML] Understanding the strain localization in additively manufactured materials: Micro-scale tensile tests and crystal plasticity modeling
Metallic parts fabricated by additive manufacturing (AM) usually exhibit unique
microstructures and non-negligible residual stresses compared with the counterparts …
microstructures and non-negligible residual stresses compared with the counterparts …
A unification of finite deformation J2 Von-Mises plasticity and quantitative dislocation mechanics
We present a framework which unifies classical phenomenological J 2 and crystal plasticity
theories with quantitative dislocation mechanics. The theory allows the computation of stress …
theories with quantitative dislocation mechanics. The theory allows the computation of stress …
PhySRNet: Physics informed super-resolution network for application in computational solid mechanics
R Arora - 2022 IEEE/ACM International Workshop on Artificial …, 2022 - ieeexplore.ieee.org
Traditional numerical approaches have been successfully used to model mechanical
behavior of heterogeneous materials (composites, multicomponent alloys, and polycrystals) …
behavior of heterogeneous materials (composites, multicomponent alloys, and polycrystals) …
A hidden convexity in continuum mechanics, with application to classical, continuous-time, rate-(in) dependent plasticity
A Acharya - Mathematics and Mechanics of Solids, 2024 - journals.sagepub.com
A methodology for defining variational principles for a class of PDE (partial differential
equations) models from continuum mechanics is demonstrated, and some of its features are …
equations) models from continuum mechanics is demonstrated, and some of its features are …
[HTML][HTML] Finite element implementation of the thermal field dislocation mechanics model: Study of temperature evolution due to dislocation activity
GD Lima-Chaves, MV Upadhyay - Computer Methods in Applied …, 2024 - Elsevier
The small deformation formulation of the thermal field dislocation mechanics model
(Upadhyay, J. Mech. Phys. Solids, 145 (2020) 104150) is numerically implemented using …
(Upadhyay, J. Mech. Phys. Solids, 145 (2020) 104150) is numerically implemented using …
A deep learning framework for solving hyperbolic partial differential equations: Part i
R Arora - arXiv preprint arXiv:2307.04121, 2023 - arxiv.org
Physics informed neural networks (PINNs) have emerged as a powerful tool to provide
robust and accurate approximations of solutions to partial differential equations (PDEs) …
robust and accurate approximations of solutions to partial differential equations (PDEs) …
Generalized grain boundary constitutive description implemented in a strain-gradient large-strain FFT-based formulation: Application to nano-metallic laminates
This paper presents a general treatment of grain boundary constitutive behavior in the
context of strain-gradient (SG) plasticity, and its numerical implementation in a large-strain …
context of strain-gradient (SG) plasticity, and its numerical implementation in a large-strain …
A dual variational principle for nonlinear dislocation dynamics
A Acharya - Journal of Elasticity, 2023 - Springer
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