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

A long-term fatigue assessment method based on EWP concept is proposed. ‘Equivalent wave probability (EWP)’ is the fictitious (H_S, T_m)'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 α_TP, 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.