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UNSUPERVISED LEARNING METHODS FOR IDENTIFICATION OF DEFECTS IN HETEROGENEOUS MATERIALS
(Proceedings of the American Society for Composites—Thirty-fifth Technical Conference, 2020-09-17)
**Please note that the full text is embargoed** ABSTRACT: The complexity of composite materials due to the nature of their numerous laminated layers, stacking sequences, type of fibers, resin, and other external factors ...
Performance Enhancement and Prediction of Composite Materials with Embedded Electrospun Piezoelectric Sensors
(Society of the Advancement of Material and Process Engineering (SAMPE), 2020)
**Please note that the full text is embargoed** ABSTRACT: In today’s world, continuous fiber reinforced composite materials are extensively used in the aerospace, automotive and other structural industries. Since the ...
ASSESSMENT OF MATERIAL STATE FOR PREDICTING THE DURABILITY OF COMPOSITES
(Proceedings of the American Society for Composites—Thirty-fifth Technical Conference, 2020-09-17)
**Please note that the full text is embargoed** ABSTRACT: The long term behavior of composites have been extensively studied for the last four decades. Given the heterogeneity of these materials, the damage accumulation ...