Validation of reliability computational models using Bayes networks |
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Authors: | Sankaran Mahadevan Ramesh Rebba |
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Affiliation: | Department of Civil and Environmental Engineering, Vanderbilt University, Box 1831-B, Nashville, TN 37235, USA |
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Abstract: | This paper proposes a methodology based on Bayesian statistics to assess the validity of reliability computational models when full-scale testing is not possible. Sub-module validation results are used to derive a validation measure for the overall reliability estimate. Bayes networks are used for the propagation and updating of validation information from the sub-modules to the overall model prediction. The methodology includes uncertainty in the experimental measurement, and the posterior and prior distributions of the model output are used to compute a validation metric based on Bayesian hypothesis testing. Validation of a reliability prediction model for an engine blade under high-cycle fatigue is illustrated using the proposed methodology. |
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Keywords: | Bayes network Bayesian statistics Model validation Reliability prediction |
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