Considering the dependent relationship among wave height,wind speed,and current velocity,we construct novel trivariate joint probability distributions via Archimedean copula functions.Total 30-year data of wave height,wind speed,and current velocity in the Bohai Sea are hindcast and sampled for case study.Four kinds of distributions,namely,Gumbel distribution,lognormal distribution,Weibull distribution,and Pearson Type III distribution,are candidate models for marginal distributions of wave height,wind speed,and current velocity.The Pearson Type III distribution is selected as the optimal model.Bivariate and trivariate probability distributions of these environmental conditions are established based on four bivariate and trivariate Archimedean copulas,namely,Clayton,Frank,Gumbel-Hougaard,and Ali-Mikhail-Haq copulas.These joint probability models can maximize marginal information and the dependence among the three variables.The design return values of these three variables can be obtained by three methods:univariate probability,conditional probability,and joint probability.The joint return periods of different load combinations are estimated by the proposed models.Platform responses(including base shear,overturning moment,and deck displacement) are further calculated.For the same return period,the design values of wave height,wind speed,and current velocity obtained by the conditional and joint probability models are much smaller than those by univariate probability.Considering the dependence among variables,the multivariate probability distributions provide close design parameters to actual sea state for ocean platform design.
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