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ρ-CP: Open Source Dislocation Density Based Crystal Plasticity Framework for Simulating Temperature- and Strain Rate-Dependent Deformation

Anirban Patra1*, Suketa Chaudhary1, Namit Pai1, Tarakram Ramgopal1, Sarthak Khandelwal1, Adwitiya Rao1, David L. McDowell2,3**

1Department of Metallurgical Engineering and Materials Science, Indian Institute of Technology Bombay, Mumbai, India

2School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, USA

3GWW School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, USA

*[email protected]; [email protected]

**[email protected]

ρ-CP is a crystal plasticity solver that interfaces with the open source finite element solver, MOOSE (https://github.com/idaholab/moose), for crystal plasticity finite element modeling of anisotropic, heterogeneous deformation in polycrystalline ensembles. Source codes for the dislocation density-based crystal plasticity solver are provided in this repository.

There are several constitutive models implemented for the different examples provided: (a) mobile and immobile dislocation density based crystal plasticity model, with threshold lattice resistance (DDCPStressUpdate, DDCPHCPStressUpdate) (Ref. [1]), (b) mobile and immobile dislocation density based crystal plasticity model, without threshold lattice resistance (DDCPTSTStressUpdate) (Ref. [2]), (c) statistically stored dislocation (SSD) density based Kocks-Mecking crystal plasticity model (DDCP_SSD_StressUpdate) (Ref. [3]), (d) mobile and immobile dislocation density based J2 plasticity model (DDJ2StressUpdate) (Refs. [5,6]).

Details of the framework and numerical implementation are available at: https://doi.org/10.1016/j.commatsci.2023.112182
https://arxiv.org/abs/2303.02441

Details of the material properties/model parameters and their input to the model are given in: Model Parameters

Details of pre- and post-processing are given in: Pre- and Post-Processing

Screenshot

All input files tested with MOOSE version: 024e31760a (2024-08-13), PETSc version: 3.21.4, SLEPc version: 3.21.1

Installation

The user needs to install MOOSE first (https://mooseframework.inl.gov/getting_started/installation/index.html), then clone and compile ρ-CP alongside MOOSE in the projects directory:

  • Following installation of MOOSE and the required conda environment, the source files can be obtained either using the following commands from the home directory:
    cd projects
    git clone https://github.com/apatra6/rhocp.git
    or directly downloading the repository from github in the projects directory.
  • The executable can be compiled using:
    cd rhocp
    make -j 4
    to get the executable rhocp-opt (here 4 represents the number of processors used for compiling and can be modified appropriately).
  • If the user wishes to perform code developement and debug the application using gdb, the executable should be compiled in debug mode using the following coomand:
    METHOD=dbg make -j 4
    to get the executable rhocp-dbg (more details can be found at: https://mooseframework.inl.gov/application_development/debugging.html).

Running Simulations

  • The user is suggested to first go through the basics of running MOOSE simulations (https://mooseframework.inl.gov/getting_started/examples_and_tutorials/index.html).
  • Example simulation files for magnesium, copper, tantalum, 304L stainless steel, DX54 ferritic steel and 316 austenitic stainless steel are located in the examples directory.
  • The following input files are required to run a ρ-CP simulation: (a) MOOSE input file, with .i extension, (b) slip system information file (bcc_slip_sys.in, for example), (c) material properties file (bcc_props.in, for example), (d) grain orientations in the form of Bunge Euler angles (orientations.in, for example). Additionally, the mesh may be: (i) created in the MOOSE input file itself, (ii) imported from an Exodus file (64grains_512elements.e, for example), or (iii) imported from an EBSD mesh file (tantalum_input_original_euler.txt in examples/tantalum/EBSD_simulation, for example). For the last case, Euler angles need not be imported separately.
  • The EBSD mesh file can be created using DREAM3D. See: https://mooseframework.inl.gov/source/userobjects/EBSDReader.html and http://www.dream3d.io/2_Tutorials/EBSDReconstruction/ for additional details.
  • Simulations can be run using the following example command:
    mpiexec -n 4 ~/projects/rhocp/rhocp-opt -i Cu_compression_sim.i
    for running the example given in rhocp/examples/copper/strain_rate_effect/compression_sr_1e-1ps/.
  • Output files in the form of .csv files can be used for plotting averaged values of various quantities and Exodus .e files can be visualized using Paraview (https://www.paraview.org/) for the deformation contours (the user is advised to use Paraview version 5.9 or lower).
  • Spatio-temporal data can also be extracted from the .e output files using the Python SEACAS (https://github.com/sandialabs/seacas) libraries (an example script extract_data.py is provided in examples/tantalum/temperature_effect/compression_512/298K_sr_5000_512grains) or using the GUI-based data extraction tools in Paraview.

References

For general details of the ρ-CP framework and numerical implementation: Ref. [1]

For mobile and immobile dislocation density based crystal plasticity model, without threshold lattice resistance: Ref. [2]

For SSD-based Kocks-Mecking crystal plasticity model: Ref. [3]

For thermal Eigen strains and prediction of residual/internal strains: Refs. [3,4]

For the dislocation density-based J2 plasticity model: Refs. [5,6]

For numerical integration of the J2 plasticity model: Ref. [7]

[1] Patra, A., Chaudhary, S., Pai, N., Ramgopal, T., Khandelwal, S., Rao, A., McDowell, D.L., “ρ-CP: Open source dislocation density based crystal plasticity framework for simulating temperature- and strain rate-dependent deformation”, Computational Materials Science, Vol. 224, 2023, 112182.

[2] Patra, A., Tomé, C.N., “A dislocation density-based crystal plasticity constitutive model: Comparison of VPSC effective medium predictions with ρ-CP finite element predictions”, Modelling and Simulation in Materials Science and Engineering, Vol. 32, 2024, 045014.

[3] Pai, N., Samajdar, I., Patra, A., “Study of orientation-dependent residual strains during tensile and cyclic deformation of an austenitic stainless steel”, International Journal of Plasticity, Vol. 185, 2025, 104228.

[4] Pokharel, R., Patra, A., Brown, D.W., Clausen, B., Vogel, S.C., Gray, G.T., “An analysis of phase stresses in additively manufactured 304L stainless steel using neutron diffraction measurements and crystal plasticity finite element simulations”, International Journal of Plasticity, Vol. 121, 2019, pp. 201-217.

[5] Khandelwal, S., Basu, S., Patra, A., “A machine learning-based surrogate modeling framework for predicting the history-dependent deformation of dual phase microstructures”, Materials Today Communications, Vol. 29, 2021, 102914.

[6] Basu, S., Patra, A., Jaya, B.N., Ganguly, S., Dutta, M., Samajdar, I., “Study of microstructure - property correlations in dual phase steels for achieving enhanced strength and reduced strain partitioning”, Materialia, Vol. 25, 2022, 101522.

[7] Patra, A., Pai, N., Sharma, P., “Modeling intrinsic size effects using dislocation density-based strain gradient plasticity”, Mechanics Research Communications, Vol. 127, 2023, 104038.