Stochastic characterization of textile reinforcements in composites based on X-ray microtomographic scans

Anna Madra, Philippe Causse, François Trochu, Jérôme Adrien, Eric Maire, Piotr Breitkopf

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A stochastic method is introduced to characterize the dual-scale geometry of textile reinforcements in composites. The fiber tows are identified automatically from X-ray microtomographic scans with a machine learning algorithm, quantifying the error of the procedure. The tow geometry is then used to construct a stochastic model as a Gaussian Random Process which permits quantification of the uncertainty in the measurements of microscale fiber volume fraction. The hyperparameters of the model are calibrated with a custom-built multi-objective evolutionary algorithm. The approach is illustrated by the analysis of a vinyl-ester composite reinforced with a glass fiber non-crimp fabric.

Original languageEnglish (US)
Article number111031
JournalComposite Structures
Volume224
DOIs
StatePublished - Sep 15 2019

All Science Journal Classification (ASJC) codes

  • Ceramics and Composites
  • Civil and Structural Engineering

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