Numerical evaluation method of lightning rod protection probability北大核心CSCD

［Objectives］Aiming at the current situation in which it is difficult to efficiently evaluate protection probability through traditional lightning rod evaluation methods, an efficient numerical evaluation algorithm is developed on the basis of an electrogeometric model (EGM) and attractive volume to realize the efficient calculation of lightning protection probability at any point in space.［Methods］This method first determines the attractive volume boundary of the lightning rod and protection object according to the interception process of the upward and downward leaders. The collection surface and exposure arc of the lightning stroke distance are then calculated, enabling the attractive risk and interception effect of the lightning rod to be quantified. Finally, the attraction and interception characteristics of the lightning rod are integrated to establish a numerical evaluation model of protection probability. To verify the accuracy of this method, the general rule of lightning rod protection probability is analyzed and the results compared with the existing analysis method.［Result］The evaluation results of this method show good agreement with those of classical leader progression model (LPM) theory.［Conclusions］ The method proposed herein has a high degree of quantification and can realize the efficient calculation of lightning protection probability at any point in space, which can provide useful references for lightning protection design work. © 2023 Authors. All rights reserved.     

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.