IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Fanglei Hu, Stephen Niezgoda, Tianju Xue, Jian Cao
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引用次数: 0

摘要

我们介绍了开源、GPU 加速和可微分三维晶体塑性有限元法(CPFEM)软件包 JAX-CPFEM 的制定和应用。利用现代计算架构 JAX,JAX-CPFEM 通过阵列编程和 GPU 加速实现了高性能,与使用 MPI 的 MOOSE(8 核)相比,在具有 ~52,000 自由度的多晶体案例中实现了 39 倍的速度提升。此外,JAX-CPFEM 还采用了自动微分技术,使用户能够处理复杂的非线性材料构成规律,而无需手动推导特定情况下的雅各布矩阵。除了解决正向问题外,JAX-CPFEM 还展示了其在逆向设计管道中的潜力,在逆向设计管道中,多晶体铜的初始晶体学取向得到了优化,从而在变形条件下实现了目标机械性能。JAX-CPFEM 的端到端可微分性允许使用梯度优化进行自动灵敏度计算和高维逆向设计。可微分 JAX-CPFEM 的概念提供了一种经济、灵活、多用途的工具,为智能制造中的逆向设计提供了高效、易用的计算工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Efficient GPU-computing simulation platform JAX-CPFEM for differentiable crystal plasticity finite element method

Efficient GPU-computing simulation platform JAX-CPFEM for differentiable crystal plasticity finite element method

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.

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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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