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FEA —— 基于 PyTorch 的有限元分析框架

一个支持非线性材料、接触分析与动力学(隐式/显式)的研究型 FEA 框架。采用模块化设计,装配(Assembly)统一管理几何、材料、载荷与约束,求解器层提供静力隐式、动力隐式(Newmark-β)与动力显式(中心差分)。

特色

  • 装配-求解器分层,接口清晰,易扩展
  • 稀疏矩阵装配与 Pardiso/CG 线性求解
  • 动力学两种积分:Newmark-β(隐式)与中心差分(显式,集总质量)
  • 接触(自接触/体-体接触)、压力、体力等载荷组件
  • 基于 PyTorch,可使用 GPU 与自动微分做灵敏度/优化

快速开始

  1. 安装依赖(略)。推荐 Python 3.10+、PyTorch(float64)。
  2. 运行最小示例脚本(静力 + 表面压力):

在仓库根目录下执行(Windows PowerShell):

python .\Docs\examples\run_static_pressure.py

脚本会读取 tests/pressure_test/C3D4Less.inp,在 final_model 上施加表面压力并固定底部节点,调用静力隐式求解,并将位移向量保存至 out/static_pressure_GC.npy

  1. 更多用法示例:
  • 使用说明(从 INP 到求解、导出与可视化)见:Docs/usage.md
  • 框架架构与数据流见:Docs/structure.md

目录导航

  • src/torchfea:核心代码(装配、元素、载荷、约束、求解器等)
  • examples/:各类算例与验证(元素、压力、接触、动力学、梯度/优化)
  • docs/:架构与使用文档,Docs/examples/ 提供可直接运行的示例脚本

许可

研究用途优先。若用于生产或商业,请先评估并完善必要的数值与工程健壮性保障。

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