Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

The Prediction of Permeability for an Epoxy/E-Glass Composite Using Optical Coherence Tomographic Images

Published

Author(s)

Joy Dunkers, Frederick R. Phelan Jr., C G. Zimba, Kathleen M. Flynn, D P. Sanders, R C. Peterson, Richard~undefined~undefined~undefined~undefined~undefined Parnas

Abstract

Knowledge of the permeability tensor in liquid composite molding is important for process optimization. Unfortunately, experimental determination of permeability is difficult and time consuming. A rapid, non-destructive technique called optical coherence tomography (OCT) can image the microstructure of a composite in minutes. In this work, binary images were generated from the low contrast OCT data through image de-noising, contrast enhancement and feature recognition. The images were then subjected to an additional pattern recognition routine that smoothed the images without sacrificing fiber volume fraction. The resulting data were input to a lattice Boltzmann model for permeability prediction. The influence of the fiber volume fraction, tow surface area, average mean free channel path, and variable microstructure are discussed in terms of their individual and synergistic effects on permeability. The calculated axial and transverse permeabilities from the post-processed images show excellent agreement with the experimental values.
Citation
Polymer Composites
Volume
22
Issue
No. 6

Keywords

composites, imaging, optical coherence tomography, permeability

Citation

Dunkers, J. , Phelan Jr., F. , Zimba, C. , Flynn, K. , Sanders, D. , Peterson, R. and Parnas, R. (2001), The Prediction of Permeability for an Epoxy/E-Glass Composite Using Optical Coherence Tomographic Images, Polymer Composites, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=851606 (Accessed April 23, 2024)
Created November 30, 2001, Updated October 12, 2021