Open Source Software and Data 

In order to facilitate collaborations, enable third-party validation and in some cases, fulfill requirements of sponsors, we have provided a number of open source software and data. Unless specified otherwise, those software and data are protected by the Creative Commons Attribution 4.0 International License. Under this license, users must give appropriate credit and indicate if changes are made and are not allowed to apply legal terms and technological measures that legally restrict others from doing anything the license permits. Users must also acknowledge that they are using the software and data at their own risks. This page will be updated periodically. 

Data-driven causal discovery and uncertainty propagations for constitutive laws

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Repository: 
https://github.com/bbhm-90/MultiGraphRNN 
https://github.com/YanxunXu/MaterialLawCausal 

​Related publications/suggested citations:
  • X. Sun, B. Bahmani, N. Vlassis, W.C. Sun, Y. Xu, Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty quantification, Granular Matter, accepted, 2021. [arxiv]

​Last Updated: 1/1/2021

​Implementation of phase field fracture model for micro-polar continua 

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Repository: 
https://github.com/hyoungsuksuh/micropolar_phasefield

​Related publications/suggested citations:
  • H.S. Suh, W.C. Sun, An open source FEniCS implementation of a phase field fracture model for micropolar continua, International Journal of Multiscale Computational Engineering, doi:10.1615/IntJMultCompEng.2020033422, 2019. 
  • H.S. Suh, D. O'Conner, W.C. Sun, A phase field model for cohesive fracture in micropolar continua, Computer Methods in Applied Mechanics and Engineering, doi:10.1016/j.cma.2020.113181, 2020.

​Last Updated: 1/1/2020

Discrete element simulation data for training traction-separation law

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Repository (data):
https://data.mendeley.com/datasets/n5v7hyny8n/1

Repository (software):
​Provided upon request. 

​Related publications/suggested citations:
  • K. Wang, W.C. Sun, Meta-modeling game for deriving theory-consistent, micro-structure-based traction-separation laws via deep reinforcement learning, Computer Methods in Applied Mechanics and Engineering, 346:216-241,  doi:10.1016/j.cma.2018.11.026, 2019. [PDF][Bibtex]​
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​Last Updated: 9/1/2019

MATLAB code for 1D poromechanics problems

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Repository: (source code)
https://bit.ly/3duTsn9

​Related publications/suggested citations:
  • W.C. Sun, J.T. Ostien, A.G. Salinger, A stabilized assumed deformation gradient finite element formulation for strongly coupled poromechanical simulations at finite strain, International Journal for Numerical and Analytical Methods in Geomechanics, 37(16):2755-2788, doi:10.1002/nag.2161, 2013. [PDF] [Bibtex]
  • W.C. Sun, Q. Chen, J.T. Ostien, Modeling hydro-mechanical responses of strip and circular footings on saturated collapsible geomaterials, Acta Geotechnica, 9(5):903-934,  doi:10.1007/s11440-013-0276-x, 2014. [PDF] [Bibtex]
  • W.C. Sun, A stabilized finite element formulation for monolithic thermo-hydro-mechanical simulations at finite strain, International Journal for Numerical Methods in Engineering, 103(11):798-839, doi:10.1002/nme.4910, 2015. [PDF] [Bibtex] (This paper is one of the 5 most cited papers from 2015 to 2016 in IJNME, and is selected for the Zienkiewicz Numerical Methods in Engineering Prize [URL #1][URL #2].

​Last Updated: 9/1/2019
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