A machine learning framework for damage mechanism identification from acoustic emissions in unidirectional SiC/SiC composites

Abstract In this work, we demonstrate that damage mechanism identification from acoustic emission (AE) signals generated in minicomposites with elastically similar constituents is possible. AE waveforms were generated by SiC/SiC ceramic matrix minicomposites (CMCs) loaded under uniaxial tension and...

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Auteurs principaux: C. Muir, B. Swaminathan, K. Fields, A. S. Almansour, K. Sevener, C. Smith, M. Presby, J. D. Kiser, T. M. Pollock, S. Daly
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/a32a34e63afa41ae95684f6380fb93fe
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