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Development of Techniques for Composite Parts Failure Analysis in Static and Fatigue Mode - Application on Thermoset and Thermoplastic Materials for Rotorcraft Main Rotor Hub Analysis

Mélanie Herman, Jean-Marc Besson, Jean-Paul Charles, Nassira Boulebbad-Gomez, Airbus Helicopters
Christian Hochard, Noël Lahellec, CNRS

May 14, 2018

https://doi.org/10.4050/F-0074-2018-12887

Abstract:
A model defined at the ply scale to predict the failure of laminated composites for static or fatigue loading is proposed. The model describes the loss of strength in the fiber direction for a significant level of transverse damage. This meso-scale model has been characterized on woven ply laminates used for rotorcraft dynamic components, such as glass/epoxy of Starflex®, carbon fiber/epoxy, and carbon fiber/PEEK of H160 main rotor hub. Failure behavior prediction at coupon level has been validated regarding static and fatigue failure mode in tension for epoxy resin woven ply laminates. Characterizations have been also provided for PEEK resin in balanced woven ply laminate, regarding static or fatigue failure mode. Those activities are crucial to increase the level of confidence in failure model, to rely on virtual testing at coupons level, and to better predict damage and failure at component level. This work intends to support the building block approach during development and certification of such critical applications for rotorcraft.


Development of Techniques for Composite Parts Failure Analysis in Static and Fatigue Mode - Application on Thermoset and Thermoplastic Materials for Rotorcraft Main Rotor Hub Analysis

  • Presented at Forum 74
  • 16 pages
  • SKU # : F-0074-2018-12887
  • Structures and Materials

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Development of Techniques for Composite Parts Failure Analysis in Static and Fatigue Mode - Application on Thermoset and Thermoplastic Materials for Rotorcraft Main Rotor Hub Analysis

Authors / Details:
Mélanie Herman, Jean-Marc Besson, Jean-Paul Charles, Nassira Boulebbad-Gomez, Airbus Helicopters
Christian Hochard, Noël Lahellec, CNRS