A matrix-free, GPU-compatible PyTorch implementation of phase-field fracture with explicit dynamics, custom differentiable implicit damage solve, benchmarks on dynamic and quasi-static cases, and inverse recovery of fracture energy G_c via L-BFGS.
JAX-FEM: A differen- tiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
roles
background 1polarities
background 1representative citing papers
JAX-AMG is a new library that exposes AmgX AMG and Krylov methods as JAX primitives supporting JIT, reverse-mode AD, batched solves, and distributed execution.
A differentiable contact mechanics engine embedded in a neural network and quadratic optimizer discovers axisymmetric asperity topographies that produce target nonlinear friction laws, validated against BEM simulations.
GLUE orchestrates frozen pre-trained generative models into a system-level design generator that enforces feasibility, performance, and diversity, with data-driven and data-free variants benchmarked on UAV design.
Mosaic is a benchmark suite evaluating 14 differentiable PDE solvers across fluids, structures, and heat transfer, showing large variations in cost and conditioning but similar convergence behavior.
LEIA is a world model for autoregressive 3D simulation of architected materials under interactive loading, benchmarked on MicroPlate and applied to surrogate-guided de novo design search with finite-element validation.
The authors implement a GPU-accelerated total Lagrangian FE framework for multibody dynamics with implicit backward-Euler stepping, augmented Lagrangian constraints, and a two-stage parallelization strategy, reporting up to 10x speedup over CPU for large meshes and validating frictional contact.
citing papers explorer
-
A matrix-free, differentiable PyTorch solver for phase-field fracture: Formulation, benchmarks, and inverse analysis
A matrix-free, GPU-compatible PyTorch implementation of phase-field fracture with explicit dynamics, custom differentiable implicit damage solve, benchmarks on dynamic and quasi-static cases, and inverse recovery of fracture energy G_c via L-BFGS.
-
JAX-AMG: A GPU-Accelerated Differentiable Sparse Linear Solver Library for JAX
JAX-AMG is a new library that exposes AmgX AMG and Krylov methods as JAX primitives supporting JIT, reverse-mode AD, batched solves, and distributed execution.
-
Inverse Design of Metainterfaces for Static Friction Control: Beyond the Hertzian Limit
A differentiable contact mechanics engine embedded in a neural network and quadratic optimizer discovers axisymmetric asperity topographies that produce target nonlinear friction laws, validated against BEM simulations.
-
GLUE: Coordinating Pre-Trained Generative Models for System-Level Design
GLUE orchestrates frozen pre-trained generative models into a system-level design generator that enforces feasibility, performance, and diversity, with data-driven and data-free variants benchmarked on UAV design.
-
Mosaic: A Benchmark Suite for Differentiable Physics Solvers
Mosaic is a benchmark suite evaluating 14 differentiable PDE solvers across fluids, structures, and heat transfer, showing large variations in cost and conditioning but similar convergence behavior.
-
LEIA: Learned Environment for Interactive Architected Materials
LEIA is a world model for autoregressive 3D simulation of architected materials under interactive loading, benchmarked on MicroPlate and applied to surrogate-guided de novo design search with finite-element validation.
-
A Total Lagrangian Finite Element Framework for Multibody Dynamics: Part II -- GPU Implementation and Numerical Experiments
The authors implement a GPU-accelerated total Lagrangian FE framework for multibody dynamics with implicit backward-Euler stepping, augmented Lagrangian constraints, and a two-stage parallelization strategy, reporting up to 10x speedup over CPU for large meshes and validating frictional contact.