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A Methodology for Incorporating the Effect of Grain Size on the Energy Efficiency Coefficient for Fatigue Crack Initiation Estimation in Polycrystalline Metal
Open AccessArticle

Uncertainty Quantification in Small-Timescale Model-Based Fatigue Crack Growth Analysis Using a Stochastic Collocation Method

1
Department of Disaster Mitigation for Structures, Tongji University, Shanghai 200092, China
2
State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
*
Author to whom correspondence should be addressed.
Metals 2020, 10(5), 646; https://doi.org/10.3390/met10050646
Received: 16 April 2020 / Revised: 12 May 2020 / Accepted: 14 May 2020 / Published: 16 May 2020
(This article belongs to the Special Issue Fatigue Life Prediction of Metallic Materials)
Due to the uncertainties originating from the underlying physical model, material properties and the measurement data in fatigue crack growth (FCG) processing, the prediction of fatigue crack growth lifetime is still challenging. The objective of this paper was to investigate a methodology for uncertainty quantification in FCG analysis and probabilistic remaining useful life prediction. A small-timescale growth model for the fracture mechanics-based analysis and predicting crack-growth lifetime is studied. A stochastic collocation method is used to alleviate the computational difficulties in the uncertainty quantification in the small-timescale model-based FCG analysis, which is derived from tensor products based on the solution of deterministic FCG problems on sparse grids of collocation point sets in random space. The proposed method is applied to the prediction of fatigue crack growth lifetime of Al7075-T6 alloy plates and verified by fatigue crack-growth experiments. The results show that the proposed method has the advantage of computational efficiency in uncertainty quantification of remaining life prediction of FCG. View Full-Text
Keywords: fatigue crack growth lifetime; uncertainty quantification; small-timescale; stochastic collocation method; remaining life prediction fatigue crack growth lifetime; uncertainty quantification; small-timescale; stochastic collocation method; remaining life prediction
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Tang, H.; Guo, X.; Xue, S. Uncertainty Quantification in Small-Timescale Model-Based Fatigue Crack Growth Analysis Using a Stochastic Collocation Method. Metals 2020, 10, 646.

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