Statistical Estimation of Strain Using Spatial Correlation Functions

Patxi Fernandez-Zelaia, Yousub Lee, Quinn Campbell, Sebastien Dryepondt, Michael Kirka, Andrés Márquez Rossy

Research output: Contribution to journalArticlepeer-review

Abstract

Ex-situ estimation of strains from deformed micrographs is not possible as there are no persistent features which can be tracked. Two point spatial statistics enable the rigorous quantification of spatial patterns in heterogeneous media. In this paper, we propose a novel method for estimating strains directly from dissimilar micrographs using a continuum mechanics approach. Rather than operating directly on images from sequential frames, as is done in digital image correlation, we operate on different microstructure realizations. This is made possible by comparing the spatial autocorrelation maps of deformed and undeformed micrographs rather than direct comparison of images. A Bayesian framework is proposed for quantifying uncertainty. We first illustrate the efficacy of this method on speckle pattern images from digital image correlation experiments. Then, we demonstrate that the method is capable of operating on dissimilar micrographs using deformed synthetic binary microstructures. Finally, we present a case study on polycrystalline additively manufactured 316L deformed via tension. The proposed method works well and we discuss implications and limitations of the presented work.

Original languageEnglish
Pages (from-to)276-295
Number of pages20
JournalIntegrating Materials and Manufacturing Innovation
Volume11
Issue number2
DOIs
StatePublished - Jun 2022

Funding

Research was sponsored by the US Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office, and the Office of Fossil Energy, Crosscutting Research Program, under contract DE-AC05-00OR22725 with UT-Battelle LLC and performed in partiality at the Oak Ridge National Laboratory’s Manufacturing Demonstration Facility, an Office of Energy Efficiency and Renewable Energy user facility. Notice of Copyright . This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

  • Bayesian statistics
  • Continuum mechanics
  • Deformation
  • Experimental mechanics
  • Spatial statistics

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