UNCERTAINTY AND BAYESIAN UPDATING CONSIDERING INSPECTION FOR SHIP STRUCTURE SUBJECTED TO CORROSION DETERIORATION

摘要

The classical probability theory cannot effectively quantify the parameter uncertainty in probability of detection. Furthermore, the conventional data analytic method and expert judgment method fail to handle the problem of model uncertainty updating with the information from nondestructive inspection. To overcome these disadvantages, a Bayesian approach was proposed to quantify the parameter uncertainty in probability of detection. Furthermore, the formulae of the multiplication factors to measure the statistical uncertainties in the probability of detection following the Weibull distribution were derived. A Bayesian updating method was applied to compute the posterior probabilities of model weights and the posterior probability density functions of distribution parameters of probability of detection. A total probability model method was proposed to analyze the problem of multi-layered model uncertainty updating. This method was then applied to the problem of multi-layered corrosion model uncertainty updating for ship structures. The results indicate that the proposed method is very effectively in analyzing the problem of multi-layered model uncertainty updating.