TY - JOUR
T1 - Efficient GPU-computing simulation platform JAX-CPFEM for differentiable crystal plasticity finite element method
AU - Hu, Fanglei
AU - Niezgoda, Stephen
AU - Xue, Tianju
AU - Cao, Jian
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/2/22
Y1 - 2025/2/22
N2 - We present the formulation and applications of JAX-CPFEM, an open-source, GPU-accelerated, and differentiable 3-D crystal plasticity finite element method (CPFEM) software package. Leveraging the modern computing architecture JAX, JAX-CPFEM features high performance through array programming and GPU acceleration, achieving a 39× speedup in a polycrystal case with ~52,000 degrees of freedom compared to MOOSE with MPI (8 cores). Furthermore, JAX-CPFEM utilizes the automatic differentiation technique, enabling users to handle complex, non-linear constitutive materials laws without manually deriving the case-specific Jacobian matrix. Beyond solving forward problems, JAX-CPFEM demonstrates its potential in an inverse design pipeline, where initial crystallographic orientations of polycrystal copper are optimized to achieve targeted mechanical properties under deformations. The end-to-end differentiability of JAX-CPFEM allows automatic sensitivity calculations and high-dimensional inverse design using gradient-based optimization. The concept of differentiable JAX-CPFEM provides an affordable, flexible, and multi-purpose tool, advancing efficient and accessible computational tools for inverse design in smart manufacturing.
AB - We present the formulation and applications of JAX-CPFEM, an open-source, GPU-accelerated, and differentiable 3-D crystal plasticity finite element method (CPFEM) software package. Leveraging the modern computing architecture JAX, JAX-CPFEM features high performance through array programming and GPU acceleration, achieving a 39× speedup in a polycrystal case with ~52,000 degrees of freedom compared to MOOSE with MPI (8 cores). Furthermore, JAX-CPFEM utilizes the automatic differentiation technique, enabling users to handle complex, non-linear constitutive materials laws without manually deriving the case-specific Jacobian matrix. Beyond solving forward problems, JAX-CPFEM demonstrates its potential in an inverse design pipeline, where initial crystallographic orientations of polycrystal copper are optimized to achieve targeted mechanical properties under deformations. The end-to-end differentiability of JAX-CPFEM allows automatic sensitivity calculations and high-dimensional inverse design using gradient-based optimization. The concept of differentiable JAX-CPFEM provides an affordable, flexible, and multi-purpose tool, advancing efficient and accessible computational tools for inverse design in smart manufacturing.
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001428618300001
UR - https://openalex.org/W4407857358
UR - https://www.scopus.com/pages/publications/85218418792
U2 - 10.1038/s41524-025-01528-2
DO - 10.1038/s41524-025-01528-2
M3 - Journal Article
SN - 2057-3960
VL - 11
JO - npj Computational Materials
JF - npj Computational Materials
IS - 1
M1 - 46
ER -