On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

Trend · papers per month

count % of corpus

10 results for “Hyperelasticity”

A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materialsstat.ML

A hybrid model combines diffusion and neural operator methods for stress prediction in hyperelastic materials.

problem Challenges in predicting stress fields in hyperelastic materials with complex microstructures.

method A hybrid surrogate framework combining a conditional denoising diffusion probabilistic model (cDDPM) and a modified DeepONet.

result The hybrid model consistently outperforms traditional methods by one to two orders of magnitude.

stress prediction hyperelastic materials diffusion models DeepONet conditional denoising

2026-03-18abs ↗pdf ↗

Tensor Basis Gaussian Process Models of Hyperelastic Materialsstat.ML

The paper develops GPR models for hyperelastic materials, improving accuracy and rotational invariance.

problem Modeling stress tensors of hyperelastic materials with fewer training examples and higher accuracy.

method Developed three approaches: direct stress tensor modeling, embedding rotational invariance, and recovering strain-energy density.

result Improved GPR models achieve higher accuracy and rotational invariance with fewer training examples.

Gaussian process regression hyperelastic materials stress tensor strain-energy density machine learning

2019-12-23abs ↗pdf ↗

Curvature-Induced Force Fields in Hyperelasticitymath.NA

Hyperelastic bodies in Riemannian manifolds can levitate due to curvature-induced forces.

problem Hyperelastic bodies in Riemannian manifolds can levitate due to curvature-induced forces.

method Numerical simulations of static solutions to a particular class of problems in hyperelastic mechanics.

result Hyperelastic bodies in Riemannian manifolds can levitate due to curvature-induced forces.

hyperelasticity Riemannian manifolds gravitational potential levitation curvature-induced forces

2026-06-10abs ↗pdf ↗

On the stability of POD Basis Interpolation via Grassmann Manifolds for Parametric Model Order Reduction in Hyperelasticitymath.DG

This work ensures stability in POD basis interpolation for pMOR in hyperelasticity.

problem Stability of POD basis interpolation on Grassmann manifolds for pMOR in hyperelasticity.

method Stability conditions derived from Grassmannian Exponential map and principal angles.

result Explicit stability conditions for practical pMOR applications and non-monotonic error behavior.

POD basis interpolation Grassmann manifolds Model Order Reduction Hyperelasticity Stability conditions

2020-12-16abs ↗pdf ↗

On material-uniform elastic bodies with disclinations and their homogenizationmath-ph

Study on materials with disclinations, limiting their size.

problem Limiting the size of disclinations in materials with symmetries.

method Defining material-uniform hyperelastic bodies with disclinations, rigorously analyzing their properties.

result The size of disclinations is limited by the symmetries of the constitutive relation.

disclinations hyperelastic bodies material uniformity symmetry constraints

2024-12-18abs ↗pdf ↗

Data-efficient Bayesian-guided design selection from large candidate sets: Application to hyperelastic stochastic metamaterialscs.CE

Bayesian-guided method selects optimal design from large candidate pool.

problem Optimizing complex structures with high-fidelity evaluations.

method Bayesian active learning with surrogate modeling.

result Optimal design identified with minimal oracle evaluations.

Bayesian optimization active learning hyperelastic materials Gaussian process design selection

2026-03-16abs ↗pdf ↗

Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networkscs.CE

Local laGPR speeds up multiscale mechanics simulations without neural networks.

problem High computational costs in multiscale mechanics simulations.

method Local approximate Gaussian process regression (laGPR) combined with FE schemes.

result laGPR offers better accuracy than neural networks for stress predictions.

Gaussian process regression FE-FFT FE$^2$neural networks multiscale mechanics

2021-05-07abs ↗pdf ↗

Generalized Finsler geometry and the anisotropic tearing of skincond-mat.soft

Continuum mechanics theory describes skin's complex anisotropic behavior.

problem Modeling the anisotropic tearing of skin.

method Finsler geometry fiber bundle approach, variational method, phase-field mechanics.

result Analytical solutions capture experimental data on skin tearing.

Finsler geometry continuum mechanics skin tearing phase-field mechanics anisotropic behavior

2023-09-17abs ↗pdf ↗

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problemsmath.NA

Neural operators correct PDE residuals to improve BIP solutions.

problem Reducing error in infinite-dimensional Bayesian inverse problems with neural operators.

method Error correction using PDE residuals to improve neural operator approximation.

result Trained neural operators with error correction achieve a quadratic reduction in approximation error.

Bayesian inverse problems Neural operators PDE residuals Error correction Infinite-dimensional problems

2022-10-06abs ↗pdf ↗

A geometric formulation of Schaefer's theory of Cosserat solidsmath-ph

Geometrically reformulates Cosserat solid mechanics using differential geometry.

problem Formalizing Cosserat solid mechanics in modern differential geometry.

method Formulation as a principal fibre bundle, using Cartan's magic formula, and integrating infinitesimal strains.

result Reveals strain as a Lie algebra-valued one-form and finite strain through integration.

Cosserat solids differential geometry exterior calculus fiber bundles Lie algebra

2023-09-25abs ↗pdf ↗