Machine Learning–Based Reduce Order Crystal Plasticity Modeling for ICME Applications

  • Mengfei Yuan
  • Sean Paradiso
  • Bryce Meredig
  • Stephen R. NiezgodaEmail author
Technical Article


Crystal plasticity simulation is a widely used technique for studying the deformation processing of polycrystalline materials. However, inclusion of crystal plasticity simulation into design paradigms such as integrated computational materials engineering (ICME) is hindered by the computational cost of large-scale simulations. In this work, we present a machine learning (ML) framework using the material information platform, Open Citrination, to develop and calibrate a reduced order crystal plasticity model for face-centered cubic (FCC) polycrystalline materials, which can be both rapidly exercised and easily inverted. The reduced order model takes crystallographic texture, constitutive model parameters, and loading condition as inputs and returns the stress-strain curve and final texture. The model can also be inverted and take a stress-strain curve, loading condition, and final texture as inputs and return the initial texture and constitutive model parameters as outputs. Principal component analysis (PCA) is used to develop an efficient description of the crystallographic texture. A viscoplastic self-consistent (VPSC) crystal plasticity solver is used to create the training data by modeling the stress-strain behavior and evolution of texture during deformation processing.


Reduced order model Microstructure quantification Machine learning Crystal plasticity Dimensionality reduction Parameter optimization 


Funding Information

The authors received financial support from the U.S. Department of Energy National Energy Technology Laboratory award DE-FE0027776 and DARPA Young Faculty Award grant D15AP00103 .

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© The Minerals, Metals & Materials Society 2018

Authors and Affiliations

  • Mengfei Yuan
    • 1
  • Sean Paradiso
    • 2
  • Bryce Meredig
    • 3
  • Stephen R. Niezgoda
    • 1
    • 4
    Email author
  1. 1.Department of Materials Science and EngineeringThe Ohio State UniversityColumbusUSA
  2. 2.Scientific Software EngineerCitrine InformaticsRedwood CityUSA
  3. 3.CSOCitrine InformaticsRedwood CityUSA
  4. 4.Department of Mechanical and Aerospace EngineeringThe Ohio State UniversityColumbusUSA

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