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Permeability Prediction From Non-Destructive Imaging of Composite Microstructure
Published
Author(s)
Joy Dunkers, Frederick R. Phelan Jr., Kathleen M. Flynn, D P. Sanders, Richard~undefined~undefined~undefined~undefined~undefined Parnas
Abstract
In this work, binary images of the microstructure of a unidirectional E-glass/epoxy composite were generated from the low contrast OCT data through image de-noising, contrast enhancement and feature recognition. The resulting data were input to a lattice Boltzmann model for permeability prediction. Results show that the image processing induced alterations in fiber volume fraction and tow surface area have an influence on the predicted permeability. Level-set methods for image analysis were then used to process the images to binary images. Level-set methods offer image de-noising and feature recognition while preserving fiber volume fraction and tow surface area. The calculated axial and transverse permeabilities from the level-set images shows excellent agreement with experimental values.
Proceedings Title
Society of Plastic Engineers, Annual Technical Conference | 59th | SPE/ANTEC 2001 Proceedings | CRC Press
Volume
59th
Issue
3
Conference Dates
May 1, 2001
Conference Location
Dallas, TX
Conference Title
Technical Papers of the Annual Technical Conference-Society of Plastics Engineers Incorporated
Dunkers, J.
, Phelan Jr., F.
, Flynn, K.
, Sanders, D.
and Parnas, R.
(2001),
Permeability Prediction From Non-Destructive Imaging of Composite Microstructure, Society of Plastic Engineers, Annual Technical Conference | 59th | SPE/ANTEC 2001 Proceedings | CRC Press, Dallas, TX, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=851800
(Accessed October 11, 2025)