Characterizing damage evolution in fiber reinforced composites using in-situ X-ray computed tomography, deep machine learning and digital volume correlation (DVC)

This publication has 52 references indexed in Scilit:

• Experimental investigation on interlaminar and in-plane shear damage evolution of 2D C/SiC composites using acoustic emission and X-ray computed microtomography
  Ceramics International, 2022
• Damage evolution characterization of glass fabric composites at cryogenic temperatures via in-situ tensile X-ray computed tomography tests
  Composites Communications, 2022
• In-situ X-ray computed tomography characterization of compaction-creep-recovery response and statistical void analysis of carbon/epoxy prepregs
  Composites Communications, 2022
• Fibre-direction strain measurement in a composite ply under quasi-static tensile loading using Digital Volume Correlation and in situ Synchrotron Radiation Computed Tomography
  Composites Part A: Applied Science and Manufacturing, 2020
• Interlaboratory Study of Digital Volume Correlation Error Due to X-Ray Computed Tomography Equipment and Scan Parameters: an Update from the DVC Challenge
  Experimental Mechanics, 2020
• Automated segmentation of computed tomography images of fiber-reinforced composites by deep learning
  Journal of Materials Science, 2020
• Internal three-dimensional strain evolution of the failure process for short carbon fiber composite through in situ synchrotron radiation X-ray computed tomography
  Carbon, 2020
• Design of an uncontaminated textile CFRP specimen optimised for both mechanical testing and X-ray microtomography
  Composites Part A: Applied Science and Manufacturing, 2019
• Damage investigation and modeling of 3D woven ceramic matrix composites from X-ray tomography in-situ tensile tests
  Acta Materialia, 2017
• Failure Mechanisms of Plasterboard in Nail Pull Test Determined by X-ray Microtomography and Digital Volume Correlation
  Experimental Mechanics, 2016