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A multi-stage physics-informed neural network for fretting fatigue life prediction of aluminum alloy

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Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Ahead of Print.
As a complex fatigue-wear coupling phenomenon, fretting fatigue is affected by many factors. Proposing an accurate fatigue life prediction model presents a significant challenge. This paper proposes a physics-informed neural network framework (FFLP-PINN) ...