Diffuse manifold learning of the geometry of woven reinforcements in composites

Anna Madra, Piotr Breitkopf, Balaji Raghavan, François Trochu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

When attempting to build mesoscale geometric models of woven reinforcements in composites based on X-ray microtomography data, we frequently run into ambiguous situations due to noise, particularly in contact zones between fiber tows, resulting in inadmissible cross-sectional shapes. We propose here a custom-built shape-manifold approach based on kernel PCA, k-means classification and Diffuse Approximation to identify, “repair” such badly segmented shapes in the feature space, and finally recover admissible shapes in the original space.

Original languageEnglish (US)
Pages (from-to)532-538
Number of pages7
JournalComptes Rendus - Mecanique
Volume346
Issue number7
DOIs
StatePublished - Jul 2018

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Mechanics of Materials

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