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deepmodelingDifferentiable FEM solver for advanced simulations and inverse design
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Summary
Differentiable Finite Element Method with JAX. JAX-FEM is a differentiable finite element package built on JAX, designed for researchers and engineers. It leverages automatic differentiation to enable complex inverse design and mechanistic data science problems, offering a GPU-accelerated solution for simulating various physical phenomena.
How It Works
This package integrates Automatic Differentiation (AD) with the Finite Element Method (FEM) using JAX. This approach allows users to perform gradient-based optimization for inverse problems and design tasks, such as topology optimization, without the need for manual derivation of sensitivities. The use of JAX ensures GPU acceleration and enables seamless integration into modern machine learning workflows.
Quick Start & Requirements
https://www.bohrium.com/apps/jax-fem-express.Highlighted Details
Maintenance & Community
No specific details on community channels (e.g., Discord, Slack), roadmap, or notable contributors are provided in the README. A showcase application, JAX-FEM Express, and an associated video are linked.
Licensing & Compatibility
The project is licensed under the GNU General Public License v3 (GPL-3.0). Commercial use requires direct contact with Tianju Xue, indicating potential restrictions for closed-source applications due to the copyleft nature of GPL-3.0.
Limitations & Caveats
The README does not explicitly list limitations or known issues. The GPL-3.0 license may impose significant restrictions on integration into proprietary, closed-source software.
2 weeks ago
Inactive
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