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Deep learning has achieved great success in multiaxial fatigue life prediction. However, when data‐driven models are used to describe data from physical processes, the relationship between inputs and outputs is agnostic. This paper proposes a deep learning framework combining generative adversarial networks and physical models to predict multiaxial fatigue life. This framework incorporates three life...
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