期刊
ENGINEERING FRACTURE MECHANICS
卷 78, 期 7, 页码 1487-1504出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engfracmech.2011.02.017
关键词
Uncertainty quantification; Model validation; Bayes factor; Crack growth; Model uncertainty
类别
资金
- Federal Aviation Administration William J. Hughes Technical Center [DTFACT-06-R-BAAVAN1]
- NASA ARMD/AvSP IVHM [NNX09AY54A]
This paper presents a methodology for uncertainty quantification and model validation in fatigue crack growth analysis. Several models - finite element model, crack growth model, surrogate model, etc. - are connected through a Bayes network that aids in model calibration, uncertainty quantification, and model validation. Three types of uncertainty are included in both uncertainty quantification and model validation: (1) natural variability in loading and material properties; (2) data uncertainty due to measurement errors, sparse data, and different inspection results (crack not detected, crack detected but size not measured, and crack detected with size measurement); and (3) modeling uncertainty and errors during crack growth analysis, numerical approximations, and finite element discretization. Global sensitivity analysis is used to quantify the contribution of each source of uncertainty to the overall prediction uncertainty and to identify the important parameters that need to be calibrated. Bayesian hypothesis testing is used for model validation and the Bayes factor metric is used to quantify the confidence in the model prediction. The proposed methodology is illustrated using a numerical example of surface cracking in a cylindrical component. (C) 2011 Elsevier Ltd. All rights reserved.
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