Quantitative characterization of spatial clustering in three-dimensional microstructures using two-point correlation functions

By A. Tewari, A. Gokhale, J. Spowart, Daniel B. Miracle. 2004

173 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Mechanical Engineering, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/24a6b4220a617b4af826590dc9890bf549f2ac56

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Surya R. Kalidindi
2. A. Ayyar
3. S. Niezgoda
4. Nikhilesh Chawla
5. A. Kanjarla

In Mechanical Engineering

1. Surya R. Kalidindi
2. A. Kanjarla
3. A. Ayyar
4. S. Niezgoda
5. Nikhilesh Chawla
6. Franz Roters
7. Dierk Raabe
8. David L. McDowell

In Mechanics of Materials

1. A. Kanjarla
2. S. Niezgoda
3. Surya R. Kalidindi
4. A. Ayyar
5. Nikhilesh Chawla
6. Franz Roters
7. Dierk Raabe
8. Philip Eisenlohr

Citations in the corpus

• Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data (2013, background): “Fortunately, a framework of hierarchical spatial statistics of the microstructure is available in the literature in the form of n-point correlation functions [20-25].”
• Microstructure-based modeling of crack growth in particle reinforced composites (2006, methodology): “techniques have been used to quantify SiC particle clustering in metal–matrix composites [15,36–39].”