Representation of correlation statistics functions in heterogeneous materials using layered fast spherical harmonics expansion

Dongsheng Li, Moe Khaleel, Xin Sun, Hamid Garmestani

Research output: Contribution to journalArticle

10 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)133-139
Number of pages7
JournalComputational Materials Science
Volume48
Issue number1
DOIs
Publication statusPublished - 1 Mar 2010
Externally publishedYes

Fingerprint

Heterogeneous Materials
Spherical Harmonics
spherical harmonics
Microstructure
Statistics
statistics
microstructure
expansion
statistical correlation
Carbon Nanotubes
Coefficient
coefficients
Computational efficiency
Nanotubes
Computational Efficiency
Correlation Function
Carbon nanotubes
Carbon
Harmonic
carbon nanotubes

Keywords

  • Microstructure representation
  • Probability functions
  • Spherical harmonics
  • Statistical continuum mechanics
  • Statistics correlation

ASJC Scopus subject areas

  • Materials Science(all)
  • Chemistry(all)
  • Computer Science(all)
  • Physics and Astronomy(all)
  • Computational Mathematics
  • Mechanics of Materials

Cite this

Representation of correlation statistics functions in heterogeneous materials using layered fast spherical harmonics expansion. / Li, Dongsheng; Khaleel, Moe; Sun, Xin; Garmestani, Hamid.

In: Computational Materials Science, Vol. 48, No. 1, 01.03.2010, p. 133-139.

Research output: Contribution to journalArticle

Li, Dongsheng ; Khaleel, Moe ; Sun, Xin ; Garmestani, Hamid. / Representation of correlation statistics functions in heterogeneous materials using layered fast spherical harmonics expansion. In: Computational Materials Science. 2010 ; Vol. 48, No. 1. pp. 133-139.
@article{105bf18c900d447996370b78fd510f83,
title = "Representation of correlation statistics functions in heterogeneous materials using layered fast spherical harmonics expansion",
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.",
keywords = "Microstructure representation, Probability functions, Spherical harmonics, Statistical continuum mechanics, Statistics correlation",
author = "Dongsheng Li and Moe Khaleel and Xin Sun and Hamid Garmestani",
year = "2010",
month = "3",
day = "1",
doi = "10.1016/j.commatsci.2009.12.019",
language = "English",
volume = "48",
pages = "133--139",
journal = "Computational Materials Science",
issn = "0927-0256",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - Representation of correlation statistics functions in heterogeneous materials using layered fast spherical harmonics expansion

AU - Li, Dongsheng

AU - Khaleel, Moe

AU - Sun, Xin

AU - Garmestani, Hamid

PY - 2010/3/1

Y1 - 2010/3/1

N2 - 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.

AB - 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.

KW - Microstructure representation

KW - Probability functions

KW - Spherical harmonics

KW - Statistical continuum mechanics

KW - Statistics correlation

UR - http://www.scopus.com/inward/record.url?scp=76449092808&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=76449092808&partnerID=8YFLogxK

U2 - 10.1016/j.commatsci.2009.12.019

DO - 10.1016/j.commatsci.2009.12.019

M3 - Article

VL - 48

SP - 133

EP - 139

JO - Computational Materials Science

JF - Computational Materials Science

SN - 0927-0256

IS - 1

ER -