- Author: Jan N Fuhg
- Organization: Cornell University
Here, we propose an extension to the Deep Energy Method (DEM) to resolve stress concentrations for finite strain hyperelasticity[1]. The developed framework termed mixed Deep Energy Method (mDEM) introduces stress measures as an additional output of the neural network to the recently introduced pure displacement formulation[2].
This code requires an Anaconda or Miniconda environment with a recent Python version. The complete repository can be cloned and installed locally. It is recommended to create a conda environment before installation. This can be done by the following the command line instructions
$ git clone https://github.com/FuhgJan/mixedDEM.git ./mixedDEM
$ cd mixedDEM
$ conda env create -f environment.yml
$ conda activate mixedDEM
$ python -m pip install . --user
The provided example can then be run with
$ python -m mdem
Outputs will be written to mixedDEM/outputs/vtk_files/ and can be opened with paraview.
The code requires the following packages as imports:
- NumPy for array handling
- Scipy for numerical solutions
- torch for the neural network and automatic differentiation libraries
- MatPlotLib for graphical output
- pyevtk for graphical output to paraview
- paraview for a graphical user interface
- triangle for numerical integration
If you use part of this code consider citing:
[1] Fuhg, Jan N., and Nikolaos Bouklas. "The mixed deep energy method for resolving concentration features in finite strain hyperelasticity." Journal of Computational Physics 451 (2022): 110839.
[2] Nguyen-Thanh, Vien Minh, Xiaoying Zhuang, and Timon Rabczuk. "A deep energy method for finite deformation hyperelasticity." European Journal of Mechanics-A/Solids 80 (2020): 103874.
This package comes with ABSOLUTELY NO WARRANTY. This is free software, and you are welcome to redistribute it under the conditions of the GNU General Public License (GPLv3)
The contents are published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)