Cover Image

A physics-augmented neural network framework for modeling and detecting thermo-visco-plastic behavior

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jones, Reese E., Jadoon, Asghar, Seidl, D. Thomas, Fuhg, Jan N.
Format:	Preprint
Published:	2025
Subjects:	Materials Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An attention-based neural ordinary differential equation framework for modeling inelastic processes
by: Jones, Reese E., et al.
Published: (2025)

Inverse design of anisotropic microstructures using physics-augmented neural networks
by: Jadoon, Asghar A., et al.
Published: (2024)

Polyconvex neural network models of thermoelasticity
by: Fuhg, Jan N., et al.
Published: (2024)

A hierarchy of thermodynamics learning frameworks for inelastic constitutive modeling
by: Jones, Reese E., et al.
Published: (2026)

Multiscale topology optimization of compressible and nearly incompressible anisotropic hyperelastic structures using physics-augmented neural networks
by: Jadoon, Asghar A., et al.
Published: (2026)

Input Specific Neural Networks
by: Jadoon, Asghar A., et al.
Published: (2025)

Differentiable neural network representation of multi-well, locally-convex potentials
by: Jones, Reese E., et al.
Published: (2025)

A General, Automated Method for Building Structural Tensors of Arbitrary Order for Anisotropic Function Representations
by: Patel, Ravi G., et al.
Published: (2025)

Thermodynamically Consistent Hybrid and Permutation-Invariant Neural Yield Functions for Anisotropic Plasticity
by: Jadoon, Asghar A., et al.
Published: (2025)

Automated model discovery of finite strain elastoplasticity from uniaxial experiments
by: Jadoon, Asghar A., et al.
Published: (2024)

Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models
by: Padmanabha, Govinda Anantha, et al.
Published: (2024)

Polyconvex Physics-Augmented Neural Network Constitutive Models in Principal Stretches
by: Tepole, Adrian Buganza, et al.
Published: (2025)

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response
by: Patel, Ravi, et al.
Published: (2024)

Precise, efficient and flexible modeling of crystallizing elastomers based on physics-augmented neural networks
by: Friedrichs, Konrad, et al.
Published: (2025)

Microstructure sensitive recurrent neural network surrogate model of crystal plasticity
by: Atkinson, Michael D., et al.
Published: (2025)

Stress relaxation and thermo-visco-elastic effects in fluid-filled slits and fluid-loaded plates
by: Neefjes, Erik García, et al.
Published: (2024)

Establishing the relationship between generalized crystallographic texture and macroscopic yield surfaces using partial input convex neural networks
by: van Wees, Lloyd, et al.
Published: (2024)

Composition effect in the thermo-mechanical behavior of glasses, and its modelization
by: Alvarez-Donado, Rene, et al.
Published: (2025)

Multiscale simulation of spatially correlated microstructure via a latent space representation
by: Jones, Reese E., et al.
Published: (2024)

Recurrent neural networks and transfer learning for elasto-plasticity in woven composites
by: Ghane, Ehsan, et al.
Published: (2023)

A reactive neural network framework for water-loaded acidic zeolites
by: Erlebach, Andreas, et al.
Published: (2023)

A physics-informed neural network approach to the point defect model for electrochemical oxide film growth
by: Farooqi, Mohid, et al.
Published: (2025)

Physics and chemistry-based constitutive framework for thermo-chemically aged elastomer using phase-field approach
by: Najmeddine, Aimane, et al.
Published: (2022)

Incorporation of physics-based strengthening coefficients into phenomenological crystal plasticity models
by: Prabhu, Nikhil, et al.
Published: (2025)

A physics-augmented neural network framework for finite strain incompressible viscoelasticity
by: Kalina, Karl A., et al.
Published: (2025)

A comparative study of calibration techniques for finite strain elastoplasticity: Numerically-exact sensitivities for FEMU and VFM
by: Kumar, Sanjeev, et al.
Published: (2025)

Bubble Dynamics Transformer: Microrheology at Ultra-High Strain Rates
by: Bu, Lehu, et al.
Published: (2025)

Elasto-plastic residual stress analysis of selective laser sintered porous materials based on 3D-multilayer thermo-structural phase-field simulations
by: Yang, Yangyiwei, et al.
Published: (2023)

A Direct-adjoint Approach for Material Point Model Calibration with Application to Plasticity
by: Yan, Ryan, et al.
Published: (2025)

FE-PINNs: finite-element-based physics-informed neural networks for surrogate modeling
by: Sunil, Pranav, et al.
Published: (2024)

Microscale bending plasticity and fracture behavior of amorphous aluminum oxide films
by: Mathews, Nidhin George, et al.
Published: (2026)

Physics-informed neural network framework for solving forward and inverse flexoelectric problems
by: Moon, Hyeonbin, et al.
Published: (2025)

Virp: neural network-accelerated prediction of physical properties in site-disordered materials
by: Chen, Andy Paul, et al.
Published: (2026)

Phase-field thermo-electromechanical modelling of lead-free BNT-based piezoelectric materials
by: Akshayveer, et al.
Published: (2024)

Unsupervised learning for structure detection in plastically deformed crystals
by: Barbot, Armand, et al.
Published: (2022)

Probabilistic calibration of crystal plasticity material models with synthetic global and local data
by: Pribe, Joshua D., et al.
Published: (2026)

Symmetry-enforcing neural networks with applications to constitutive modeling
by: Garanger, Kévin, et al.
Published: (2023)

Generalized model of incipient plasticity with parametric variations
by: Kumari, Sweta, et al.
Published: (2023)

Incorporating precipitation-related effects on plastic anisotropy of age-hardenable aluminium alloys into crystal plasticity constitutive models
by: Wessel, Alexander, et al.
Published: (2024)

Prediction of local elasto-plastic stress and strain fields in a two-phase composite microstructure using a deep convolutional neural network
by: Saha, Indrashish, et al.
Published: (2023)