Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1562979 | Computational Materials Science | 2010 | 7 Pages |
Abstract
Statistical correlation function, including two-point function, is one of the popular methods to digitize microstructure quantitatively. This paper investigated how to represent statistical correlations using layered fast spherical harmonics expansion. A set of spherical harmonics coefficients may be used to represent the corresponding microstructures. It is applied to represent carbon nanotube composite microstructures to demonstrate how efficiently and precisely the harmonics coefficients will characterize the microstructure. This microstructure representation methodology will dramatically improve the computational efficiencies for future works in microstructure reconstruction and property prediction.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Dongsheng Li, Moe Khaleel, Xin Sun, Hamid Garmestani,