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Versatile algorithms for the computation of 2-point spatial correlations in quantifying material structure

  • Ahmet Cecen
  • Tony Fast
  • Surya R. KalidindiEmail author
Research

Abstract

This paper presents a generalized framework along with the associated computational strategies for a rigorous quantification of the material structure in a range of different applications using the framework of 2-point spatial correlations. In particular, we focus on applications requiring different assumptions about the periodicity and/or involving irregular domain shapes and potentially extremely large datasets. Important details of the computational algorithms needed to address these challenges are developed and illustrated with example case studies. Algorithms developed and presented in this work are available at http://dx.doi.org/ https://doi.org/10.5281/zenodo.31329.

Keywords

Spatial Correlation Fast Fourier Transform Algorithm Irregular Domain Rigorous Quantification Microstructure Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors gratefully acknowledge support from AFOSR award FA9550-12-1-0458.

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© Cecen et al. 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://doi.org/creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.School of Computational Science & Engineering Georgia Institute of TechnologyAtlantaUSA
  2. 2.George W. Woodruff School of Mechanical EngineeringGeorgia Institute of TechnologyAtlantaUSA

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