Incorporation of structural health monitoring data on load effects in the reliability and redundancy assessment of ship cross-sections using Bayesian updating

Abstract

This article presents an approach for improving the accuracy in the reliability and redundancy assessment of ship cross-sections by using the Bayesian updating method. The vertical bending moments associated with ultimate failure and first failure for a given ship cross-section are evaluated using an optimization-based method and the progressive collapse method, respectively. The prior information on the wave-induced load effects is calculated based on the linear theory. Having extracted the hogging and sagging peaks from the low-frequency structural health monitoring signals, the Bayesian method is used to update the Rayleigh-distributed prior load effects. The original and updated reliability and redundancy indexes of the ship cross-sections are evaluated, and the results are displayed in polar plots.