Effective conductivity of a class of multicomponent heterogeneous materials by digital image analysis

Author(s)Alnaghmoush, Abdulaziz M.
Date Accessioned2022-11-10T12:58:02Z
Date Available2022-11-10T12:58:02Z
Publication Date2022
SWORD Update2022-08-10T19:10:16Z
AbstractWe develop computer vision techniques to calculate the effective (electrical or thermal) conductivity of multicomponent heterogeneous materials based on information collected from digital images of their microstructure. Image processing techniques are used in order to obtain the geometric and material properties of circular or near- circular inclusions embedded in a matrix. More specifically, a border-following algorithm is used to extract digital contour data pertaining to the interphase boundaries from grayscale images. The effective conductivities are then determined using an integral boundary equation formulation using the contour data extracted from images. Tests conducted on various images of multicomponent microstructures produce accurate results throughout a wide range of image resolution, demonstrating the efficacy and robustness of the developed approach. ☐ Keywords: digital image processing, border-following algorithm, effective conductivities, heterogeneous materials, composite materials.en_US
AdvisorRoy, R. Valéry
DegreeM.S.M.E.
DepartmentUniversity of Delaware, Department of Mechanical Engineering
DOIhttps://doi.org/10.58088/6tnf-xv64
Unique Identifier1350600770
URLhttps://udspace.udel.edu/handle/19716/31571
Languageen
PublisherUniversity of Delawareen_US
URIhttps://login.udel.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/effective-conductivity-class-multicomponent/docview/2700794093/se-2?accountid=10457
KeywordsBorder-following algorithm
KeywordsComposite materials
KeywordsDigital image processing
KeywordsEffective conductivities
KeywordsHeterogeneous materials
TitleEffective conductivity of a class of multicomponent heterogeneous materials by digital image analysisen_US
TypeThesisen_US
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