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• W3197759934 abstract "To deploy the airframe Digital Twin or to conduct probabilistic evaluations of the remaining life of a structural component, a (near) real-time crack growth simulation method is critical. In this paper, a reduced-order simulation approach is developed to achieve this goal by leveraging two methods. On one hand, the SGBEM super element - FEM coupling method is combined with parametric modeling to generate the database of computed Stress Intensity Factors for cracks with various sizes/shapes in a complex structural component, by which hundreds of samples are automatically simulated within a day. On the other hand, machine learning methods are applied to establish the relation between crack sizes/shapes and crack front SIFs. By combining the reduced-order computational model with load inputs and fatigue growth laws, a real time prediction of probabilistic crack growth in complex structures with minimum computational burden is realized. In an example of a round-robin helicopter component, even though the fatigue crack growth is simulated cycle by cycle, the simulation is faster than real-time (as compared to the physical test). The proposed approach is a key simulation technology towards realizing the Digital Twin of complex structures, which further requires fusion of model predictions with flight/inspection/monitoring data." @default.
• W3197759934 created "2021-09-13" @default.
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• W3197759934 date "2021-05-08" @default.
• W3197759934 modified "2023-09-27" @default.
• W3197759934 title "Real-time prediction of probabilistic crack growth with a reduced-order digital twin of a helicopter component" @default.
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• W3197759934 hasPublicationYear "2021" @default.
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