Research And Applications On The Prediction Method Of Extreme Value Of Marine Environment

Watercraft and marine structures are often subjected by random loads and extreme loads such as wind and wave flow when they are serving in terrible ocean environment.The extreme loads will cause irreversible structural damage and safety accident.Therefore,determining the extreme weather conditions in the waters where the ships and marine structures are located,predicting the extreme value of wind speed,wave height and other Marine environments within return periods,has a significance meaning for designing and safety of the ships and Marine structures.This paper based on the fundamental principles of Average Conditional Exceedance Rate(ACER),studies the capacity of extreme value prediction of the Naess-Gaidai method(N-G method)which based on the ACER principle.The paper proposed two methods for predicting the extreme value of Marine environmental features which aim at the limitations of N-G method in the process of prediction,the validity and reliability of the two methods are compared and verified.In addition,two methods were adopted to predict the extreme value of the measured wind speed and wave height in the surrounding waters of two buoys are marked as sea area No.? and sea area No.??,the buoys are located close to the Hawaiian islands.Specific works are mainly included as follows:(1)Researching the N-G method's capacity of predicting extreme value with the multi-groups stochastic load samples obtained by Monte Carlo method and the data obtained from real sea areas;(2)The calculation process is complicated and the calculation results are more conservative in the process of predicting the extreme value of Marine environment for N-G method.The present paper proposed the optimized N-G method based on the Levenberg—Marquardt method.In addition,two parameters or three parameter exceedance rate functions are given without reducing the accuracy of extreme prediction and simplifying the fitting process;writing relevant programs through Matlab,the optimized N-G method is applied to the prediction of the stochastic wind speed samples obtained by Monte Carlo method and real measured wind speed;the feasibility of this method is verified by comparing with the prediction results of N-G method;(3)To aim at the limitation of predicting the extreme value of Marine environment based on the ACER conception,which is strict to the distribution of the data,the paper presents the Interpolation ACER method which base on the Cubic spline interpolation.Writing relevant programs through Matlab,the Interpolation ACER method is applied to the prediction of the stochastic wind speed samples obtained by Monte Carlo method and real measured wind speed,the validity of this method is verified by comparing with the prediction results of N-G method;the method can effectively replace the complicated nonlinear least square method in N-G method and simplify the process of extreme prediction.(4)Using N-G method,the optimized N-G method and the Interpolation ACER method proposed in this paper predict the stochastic wind speed samples obtained by Monte Carlo method with return periods are 25,50 and 100 years.By comparing with the theoretical results,the prediction accuracy of the two methods established in this paper is verified.And those three methods are applied to the prediction of the the historical data with return periods is 50 years.By comparing with the real historical extreme value,the prediction effect of methods in the prediction of the actual Marine environmental characteristics are further verified.(5)Based on the measured data of Marine meteorological in the waters around sea area No.? and sea area No.?? near the Hawaiian islands,the Interpolation ACER method and optimized N-G method are used respectively,predicted the extreme values of wind speed and wave height in the two sea areas.The present paper compared and researched the prediction process and prediction results of two methods by predicting the extreme value of Marine environment in actual sea areas.The applicability of the two prediction methods,their advantages and disadvantages are analyzed,which lays a foundation for further research.