Browse by author
Lookup NU author(s): Professor Longbin Tao
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
The design of fixed and compliant offshore platforms requires the reliable estimation ofextreme values with small probabilities of exceedance based on an appropriate probabilitydistribution. The Weibull distribution is commonly utilised for the statistical analysis ofwave crests, including near-field wave run-ups. The parameters are estimated empiricallyfrom experimental or onsite measurements. In this paper, the data set of wave crests froma Spar model test was statistically analysed by using the method of LH-moments forparameter estimation of the Weibull distribution. The root-mean-square errors (RMSEs)and the error of LH-kurtosis were used to examine the goodness-of-fit. The results for thefirst four LH-moments, the estimated parameters, and the probability distributionsshowed that the level of the LH-moments has a significant influence. At higher levels, theestimation results gave a more focused representation of the upper part of the wave crestdistributions, which indicates consistency with the intention of the method of LHmoments.The low tail RMSE values of less than 2.5% demonstrated that a Weibull distributionmodel estimated by using high-level LH-moments can accurately represent theprobability distribution of large extreme wave crests for incident waves, wave run-ups, andmoon pool waves. Goodness-of-fit test on the basis of comparison of sampling LH-kurtosisand theoretical LH-kurtosis was recommended as a procedure for selecting an optimumlevel.
Author(s): Xiao L, Lu H, Tao L, Yang L
Publication type: Article
Publication status: Published
Journal: Marine Structures
Year: 2017
Volume: 52
Pages: 15-33
Print publication date: 01/03/2017
Online publication date: 23/11/2016
Acceptance date: 15/11/2016
Date deposited: 18/01/2017
ISSN (print): 0951-8339
ISSN (electronic): 1873-4170
Publisher: Elsevier
URL: http://dx.doi.org/10.1016/j.marstruc.2016.11.001
DOI: 10.1016/j.marstruc.2016.11.001
Altmetrics provided by Altmetric
