The data of annual extreme wave height and corresponding wind speed at a platform in Bohai Bay is hindcasted by a numerical model from 1970 to 1993. Common-used design probability distributions, such as Gumbel distribution, Weibull distribution, and lognormal distribution are applied to fit the data of extreme wave height and concomitant wind speed, respectively. Then the best-fitted marginal distributions of annual extreme wave height and wind speed can be selected. Bivariate normal copula and Frank copula are utilized to construct joint distribution of these two random variables. Based on empirical base shear equation of the on-site fixed jacket platform, the maximum base shear can be calculated under the same joint return period of the wave height and wind speed. The results show that the proposed joint probability models constructed by bivariate copulas result in lower the design environmental parameters because of the consideration of correlation between random variables. Eventually the investment cost of marginal oil fields could be relatively reduced.
Design Parameter Estimation of Wave Height and Wind Speed With Bivariate Copulas
Tao, S, Dong, S, & Xu, Y. "Design Parameter Estimation of Wave Height and Wind Speed With Bivariate Copulas." Proceedings of the ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. Volume 2A: Structures, Safety and Reliability. Nantes, France. June 9–14, 2013. V02AT02A041. ASME. https://doi.org/10.1115/OMAE2013-10519
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