Delineation of the space of 2-point correlations in a composite material system
By S. Niezgoda, David T. Fullwood, Surya R. Kalidindi. 2008
145 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/71401a848cd7a77acdaaa574f02356a275046b88
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
In Mechanics of Materials
- Surya R. Kalidindi
- David L. McDowell
- M. Priddy
- Noah H. Paulson
- A. Kanjarla
- S. Niezgoda
- Akash Gupta
- Amarendra K. Singh
Citations in the corpus
- Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches (2020, methodology): “Featurization is the process of extracting parameters (features) from experiment [64, 65], literature [66], or modeling/simulation data [67–69].”
- Structure–property linkages using a data science approach: Application to a non-metallic inclusion/steel composite system (2015, background): “The other points in the plot provide the 2-point statistic of interest for a vector corresponding to the difference between the selected point (where the statistic is shown in the plot) and the center of the plot [26, 27, 29, 30].”
- Reduced-order structure-property linkages for polycrystalline microstructures based on 2-point statistics (2017, background): “In prior work on the multiphase microstructures [87], analytic relationships were derived between the spatial correlations.”
- Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data (2013, background): “Equation (4) is readily identified as a convolution integral which is readily computed via Fourier transform techniques [22, 25].”