Determination of Correlation for Extreme Metocean Variables
Metocean environmental load includes wind, wave and currents. Offshore structures are designed for two environmental load design conditions i.e. extreme and operational load conditions of environmental loads are evaluated. The ccorrelation between load variables using Joint probability distribution,...
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Main Authors: | , , , |
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Format: | Article |
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EDP Sciences
2017
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Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018579814&doi=10.1051%2fmatecconf%2f201710304013&partnerID=40&md5=c7d7da9f5cab75127922394fadfd9f05 http://eprints.utp.edu.my/20107/ |
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Institution: | Universiti Teknologi Petronas |
Summary: | Metocean environmental load includes wind, wave and currents. Offshore structures are designed for two environmental load design conditions i.e. extreme and operational load conditions of environmental loads are evaluated. The ccorrelation between load variables using Joint probability distribution, Pearson correlation coefficient and Spearman's rank correlation coefficients methods in Peninsular Malaysia (PM), Sabah and Sarawak are computed. Joint probability distribution method is considered as a reliable method among three different methods to determine the relationship between load variables. The PM has good correlation between the wind-wave and wave-current; Sabah has both strong relationships of wind-wave and wind-current with 50 year return period; Sarawak has good correlation between wind and current in both 50 years and 100 years return period. Since Sabah has good correlation between the associated load variables, no matter in 50 years or 100 years of return period of load combination. Thus, method 1 of ISO 19901-1, specimen provides guideline for metocean loading conditions, can be adopted for design for offshore structure in Sabah. However, due to weak correlations in PM and Sarawak, this method cannot be applied and method 2, which is current practice in offshore industry, should continueto be used. © The Authors, published by EDP Sciences, 2017. |
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