Copertina

A data-driven multiscale scheme for anisotropic finite strain magneto-elasticity

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Roth, Heinrich T., Gebhart, Philipp, Kalina, Karl A., Wallmersperger, Thomas, Kästner, Markus
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computational Engineering, Finance, and Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

A dual-stage constitutive modeling framework based on finite strain data-driven identification and physics-augmented neural networks
di: Linden, Lennart, et al.
Pubblicazione: (2025)

Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functions
di: Kalina, Karl A., et al.
Pubblicazione: (2024)

Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables
di: Rosenkranz, Max, et al.
Pubblicazione: (2024)

A comparative study of micromorphic gradient-extensions for anisotropic damage at finite strains
di: van der Velden, Tim, et al.
Pubblicazione: (2023)

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

Solving strategies for data-driven one-dimensional elasticity exhibiting nonlinear strains
di: Nguyen, Thi-Hoa, et al.
Pubblicazione: (2025)

An anisotropic, brittle damage model for finite strains with a generic damage tensor regularization
di: van der Velden, Tim, et al.
Pubblicazione: (2024)

What do Large Language Models know about materials?
di: Ehrenhofer, Adrian, et al.
Pubblicazione: (2025)

Data-efficient inverse design of spinodoid metamaterials
di: Rosenkranz, Max, et al.
Pubblicazione: (2025)

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

Experiment-informed finite-strain inverse design of spinodal metamaterials
di: Thakolkaran, Prakash, et al.
Pubblicazione: (2023)

Variational multiscale enrichment method for dynamic response of hyperelastic materials at finite deformation
di: Arora, Abhishek, et al.
Pubblicazione: (2025)

A finite strain model for fiber angle plasticity of textile fabrics based on isogeometric shell finite elements
di: Duong, Thang Xuan, et al.
Pubblicazione: (2024)

A predictor-corrector scheme for approximating signed distances using finite element methods
di: Bachari, Amina El, et al.
Pubblicazione: (2025)

Nonlinear electro-elastic finite element analysis with neural network constitutive models
di: Klein, Dominik K., et al.
Pubblicazione: (2024)

An Efficient Bayesian Framework for Inverse Problems via Optimization and Inversion: Surrogate Modeling, Parameter Inference, and Uncertainty Quantification
di: Chiappetta, Mihaela, et al.
Pubblicazione: (2026)

Micromechanically motivated finite-strain phase-field fracture model to investigate damage in crosslinked elastomers
di: Josyula, S. P., et al.
Pubblicazione: (2024)

A continuum multi-species biofilm model with a novel interaction scheme
di: Klempt, Felix, et al.
Pubblicazione: (2025)

A comparative analysis for different finite element types in strain-gradient elasticity simulations performed on Firedrake and FEniCS
di: Sarar, B. Cagri, et al.
Pubblicazione: (2024)

Investigations of effect of temperature and strain dependent material properties on thermoelastic damping -- A generalized 3-D finite element formulation
di: Dixit, Saurabh
Pubblicazione: (2024)

Conservative data-driven finite element framework
di: Kuliková, Adriana, et al.
Pubblicazione: (2025)

Identification of microstructure from macroscopic measurement using inverse multiscale analysis
di: Mukherjee, Anjan, et al.
Pubblicazione: (2024)

Convolutional neural network based reduced order modeling for multiscale problems
di: Zhang, Xuhan, et al.
Pubblicazione: (2024)

A finite operator learning technique for mapping the elastic properties of microstructures to their mechanical deformations
di: Rezaei, Shahed, et al.
Pubblicazione: (2024)

Multimaterial topology optimization for finite strain elastoplasticity: theory, methods, and applications
di: Jia, Yingqi, et al.
Pubblicazione: (2025)

Set-based queries for multiscale shape-material modeling
di: Igouchkine, Oleg, et al.
Pubblicazione: (2024)

A comparative analysis of transient finite-strain coupled diffusion-deformation theories for hydrogels
di: Urrea-Quintero, Jorge-Humberto, et al.
Pubblicazione: (2024)

Simulating anisotropic diffusion processes with smoothed particle hydrodynamics
di: Tang, Xiaojing, et al.
Pubblicazione: (2024)

Convolution finite element based digital image correlation for displacement and strain measurements
di: Lu, Ye, et al.
Pubblicazione: (2023)

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

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

Cosserat micropolar and couple-stress elasticity models of flexomagnetism at finite deformations
di: Sky, Adam, et al.
Pubblicazione: (2025)

A Hybrid High-Order method for finite elastoplastic deformations within a logarithmic strain framework
di: Abbas, Mickaël, et al.
Pubblicazione: (2019)

A CFL condition for the finite cell method
di: Bürchner, Tim, et al.
Pubblicazione: (2025)

Quantum computing with error mitigation for data-driven computational homogenization
di: Kuang, Zengtao, et al.
Pubblicazione: (2023)

A novel, finite-element-based framework for sparse data solution reconstruction and multiple choices
di: Bielajewa, Wiera, et al.
Pubblicazione: (2024)

A surrogate model for computational homogenization of elastostatics at finite strain using the HDMR-based neural network approximator
di: Nguyen-Thanh, Vien Minh, et al.
Pubblicazione: (2019)

Higher-order, mixed-hybrid finite elements for Kirchhoff-Love shells
di: Neumeyer, Jonas, et al.
Pubblicazione: (2025)

Essentially non-hourglass and non-tensile-instability SPH elastic dynamics
di: Zhang, Shuaihao, et al.
Pubblicazione: (2023)