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Quantitative Comparison of Information-Rich Data Fields from Characterization/Simulation of Microstructural Damage in Ceramic Matrix Composites

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Technical Report,01 Sep 2017,30 Nov 2018

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The University of Liverpool Liverpool United Kingdom

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The research has been conducted in collaboration with Dr Craig Przybyla from the Air Force Research Laboratory AFRL, under the supervision of Professor Eann Patterson and Miss Ksenija Dvurecenska, and has been carried out by Dr William Christian and Dr Khurram Amjad. The aim of the work was to apply the novel techniques for quantitative comparison of information-rich data fields, developed by Professor Patterson and his research group at the University of Liverpool, to the data obtained from the work by Dr Przybyla and his team on microstructure-sensitive damage characterization in continuous fiber reinforced ceramic matrix composites CMCs. Five objectives were identified for this project by Dr Przybyla and Professor Patterson, as reported in the Introduction Chapter, to address the research questions from the AFRLs program on damage characterizationsimulation in CMCs. A novel method for the characterization of voids observed in the stack of mosaics of a CMC sample has been proposed in Chapter 2 which was developed by Christian to meet the first objective of this project. Chapter 3 describes a strain-based damage monitoring algorithm which has been developed by Christian to fulfil the second research objective. This algorithm can be used to identify the time and location of damage initiation within composite specimens during loading. The work on characterization and quantitative comparison of the fiber orientation fields, reported in Chapter 4, has been performed by Amjad to achieve the third research objective. Two methods, one based on digital image correlation and the other on two-dimensional cross correlation, have been proposed for the determination of fiber orientation fields from the stack of mosaics of a CMC sample. The proposed methods are estimated to be at least 17 times faster than the previously published rule-based method developed for the characterization of fiber orientation.

Subject Categories:

  • Laminates and Composite Materials
  • Cybernetics
  • Crystallography

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