Data-driven algorithm for real-time fatigue life prediction of structures with stochastic parameters

Volume: 372, Pages: 113373 - 113373
Published: Dec 1, 2020
Abstract
Fatigue crack growth analysis using extended finite element method (XFEM) is an efficient way to predict the residual life of structures; however, when the structure parameters vary stochastically, it will be very hard to make accurate predictions. To bridge this research gap, this work proposed a data-driven learning algorithm to improve the prediction capacity of fatigue life by considering stochastic parameters of structures. In this new...
Paper Details
Title
Data-driven algorithm for real-time fatigue life prediction of structures with stochastic parameters
Published Date
Dec 1, 2020
Volume
372
Pages
113373 - 113373
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