Artificial neural networks and phenomenological degradation models for fatigue damage tracking and life prediction in laser-induced graphene interlayered fiberglass composites
Abstract:Fiber-reinforced polymer matrix composites deteriorate mechanically due to fatigue degradation during cyclic stress. The progressive decrease in elastic stiffness over fatigue life is well-established and investigated, yet many dynamic engineering systems that use composite materials are subjected to random and unexpected loading circumstances, making it impossible to continually monitor such structural changes. LIG can detect strain and damage in fiberglass composites under quasi-static and dynamic loads. ANN… Show more
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