Informing Mechanical Model Development Using Lower-Dimensional Descriptions of Lattice Distortion

Darren C. Pagan, Gideon H. Schmidt, Andy D. Borum, Timothy J. Long, Armand J. Beaudoin

Research output: Contribution to journalArticlepeer-review


This paper describes a method combining in situ X-ray diffraction data and dimensionality reduction (local linear embedding) to inform the development of state variable plasticity models. The method is applied to developing a state variable plasticity model for pure nickel deformed in uniaxial tension in the small strain regime. Prior to model development, connections between state variables representing evolution of mobile dislocations and the lower-dimensional representations of the data are established. Correlations between lower-dimensional representation of data and state variable evolution motivate the introduction of new evolution equation terms to increase alignment between experiment and model. These terms capture dislocation interactions leading to hardening transients prior to steady-state plastic flow. The discussion focuses on interpreting these new evolution terms and outstanding issues associated with linking lower-dimensional representations of data to state variable evolution modeled with ordinary differential equations.

Original languageEnglish (US)
Pages (from-to)459-471
Number of pages13
JournalIntegrating Materials and Manufacturing Innovation
Issue number4
StatePublished - Dec 2020
Externally publishedYes


  • Constitutive modeling
  • Nickel
  • Plasticity
  • Unsupervised learning
  • X-ray diffraction

ASJC Scopus subject areas

  • General Materials Science
  • Industrial and Manufacturing Engineering


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