TY - JOUR
T1 - Statistical model for characterizing random microstructure of inclusion-matrix composites
AU - Al-Ostaz, Ahmed
AU - Diwakar, Anipindi
AU - Alzebdeh, Khalid I.
N1 - Funding Information:
Acknowledgements The authors wish to acknowledge the partial support for this research from U.S. Air Force Grant # F08637-03-C-6006 with a subcontract # S-29000.23 from Applied Research Associates Inc. Also, the authors would like to acknowledge the collaboration and help they received from Prof. Martin Ostoja-Starzewski.
PY - 2007/8
Y1 - 2007/8
N2 - The variation of arrangement of micro-structural entities (i.e. inclusions) influences local properties of composites. Thus, there is a need to classify and quantify different micro-structural arrangements. In other words, it is necessary to identify descriptors that characterize the spatial dispersion of inclusions in random composites. On the other hand, Delaunay triangulation associated with an arbitrary set of points in a plane is unique which makes it a good candidate for generating such descriptors. This paper presents a framework for establishing a methodology for characterizing microstructure morphology in random composites and correlating that to local stress field. More specifically, in this paper we address three main issues: correlating microstructure morphology to local stress fields, effect of clustering of inclusions on statistical descriptors identified in the paper, and effect of number of realizations of statistical volume elements (SVEs) on statistical descriptors.
AB - The variation of arrangement of micro-structural entities (i.e. inclusions) influences local properties of composites. Thus, there is a need to classify and quantify different micro-structural arrangements. In other words, it is necessary to identify descriptors that characterize the spatial dispersion of inclusions in random composites. On the other hand, Delaunay triangulation associated with an arbitrary set of points in a plane is unique which makes it a good candidate for generating such descriptors. This paper presents a framework for establishing a methodology for characterizing microstructure morphology in random composites and correlating that to local stress field. More specifically, in this paper we address three main issues: correlating microstructure morphology to local stress fields, effect of clustering of inclusions on statistical descriptors identified in the paper, and effect of number of realizations of statistical volume elements (SVEs) on statistical descriptors.
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U2 - 10.1007/s10853-006-1117-1
DO - 10.1007/s10853-006-1117-1
M3 - Article
AN - SCOPUS:34547334466
SN - 0022-2461
VL - 42
SP - 7016
EP - 7030
JO - Journal of Materials Science
JF - Journal of Materials Science
IS - 16
ER -