Fatigue assessment of ship structures based on equivalent wave probability (EWP) concept (1st report): Proposal of EWP concept and its verification by 8600TEU container ship's onboard hull monitoring

Abstract

A long-term fatigue assessment method based on EWP concept is proposed. ‘Equivalent wave probability (EWP)’ is the fictitious (HS, Tm)'s joint probability distribution function (JPDF), for which the frequency distribution of the stress variance R2, f(R2), calculated by spectral fatigue assessment agrees with the observed one. By choosing probability function p(R2) to fit f(R2), the R2's statistical model (R2SM) which represents the relation between the EWP parameters and R2's population parameters is developed, and the Bayesian inference, which can estimate the EWP parameters from the measured R2 data is developed. The EWP at the reference position (RP) can be determined by Bayesian inference from the measured R2 through the R2SM at RP. To accurately estimate the measured f(R2) at the target position (TP) from the EWP at RP, an R2SM correction factor at TP, denoted by αTP, is introduced in the process of assimilating R2SM. The resulting R2SM, which has been assimilated by Bayesian inference using measured data, is referred to as data-assimilated R2SM (DAR2SM). The fatigue assessment using EWP at RP as the input of DAR2SM at TP is called Bayes-EWP-DAR2SM analysis. The validity of Bayes-EWP-DAR2SM analysis is verified by using the long-term (about four years) multi(12)-position hull monitoring (HM) data of an 8,600TEU container ship. The fatigue damages estimated by Bayes-EWP-DAR2SM based solely on the stress history of a single sensor are in agreement with measurements with sufficient accuracy, independent of the chosen data assimilation period. This demonstrates that the multi-position fatigue assessment solely through HM at one RP based on EWP concept is realized.