Metocean Design Parameter Estimation for Fixed Platform Based on Copula Functions

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.

A Preliminary Study on the Intensity of Cold Wave Storm Surges of Laizhou Bay

Abstract Dike failure and marine losses are quite prominent in Laizhou Bay during the period of cold wave storm surges because of its open coastline to the north and fiat topography. In order to evaluate the intensity of c01d wave storm surge, the hindcast of ma- rine elements induced by cold waves in Laizhou Bay from 1985 to 2004 is conducted using a cold wave storm surge-wave coupled model and the joint return period of extreme water level, concomitant wave height, and concomitant wind speed are calculated. A new criterion of cold wave storm surge intensity based on such studies is developed. Considering the frequency of cold wave, this paper introduces a Poisson trivariate compound reconstruction model to calculate the joint return period, which is closer to the reality. By using the newly defined cold wave storm surge intensity, the ＇cold wave grade＇ in meteorology can better describe the severity of cold wave storm surges and the warning level is well corresponding to different intensities of cold wave storm surges. Therefore, it provides a proper guidance to marine hydrological analysis, disaster prevention and marine structure design in Laizhou Bay.

Hazard risk assessment of tropical cyclones based on joint probability theory

The main hazard-causing factors of tropical cyclones are strong wind,heavy rainfall,and storm surge.Evaluation of the hazard-causing degree of a tropical cyclone requires a joint intensity analysis of these hazard-causing factors.According to the maximum hourly mean wind speed,total rainfall,and maximum tide level at various observation stations in Hong Kong during these tropical cyclones,three hazard-causing indices for tropical cyclones are introduced:the strong-wind index(VI),total-rainfall index(RI),and tide-level index(LI).Through a joint probability analysis of VI,RI,and LI for a tropical cyclone affecting Hong Kong,the joint return period is calculated to evaluate its joint hazard-causing intensity.A limit state function of Hong Kong’s resistance to tropical cyclones is developed and used to evaluate the regional risk of tropical cyclones affecting Hong Kong.The results indicate that the joint return period of VI,RI,and LI can reflect the joint hazard-causing intensity of strong wind,heavy rain,and storm surge caused by tropical cyclones;if the overall design return periods of the regional structures decrease,the regional ability to defend against tropical cyclone disasters is degraded.

Stochastic ordering of medians in exchangeable trivariate normal vectors

In this paper, we establish the stochastic ordering of median from an exchangeable trivaxiate normal vector based on the strength of the correlation coefficient. Specifically, by considering two exchangeable trivariate normal vectors with different correlation coefficients, we show that the absolute value of the median in the vector with smaller correlation coefficient is stochastically smaller than the absolute value of the median in the vector with larger correlation coefficient. We prove this result by utilizing skew-normal distributions.

On Trivariate Copulas with Bivariate Linear Spearman Marginal Copulas

Based on the trivariate reduction technique two different trivariate Bernoulli mixtures of univariate uniform distributions and their associated trivariate copulas with bivariate linear Spearman marginal copulas are considered. Mathematical characterizations of these Bernoulli mixture models are obtained. Since Bernoulli mixture trivariate reduction copulas are not compatible with all valid grade correlation coefficients, and there exist linear Spearman compatible non-Bernoulli mixture trivariate copulas, one can ask when there exists at all a trivariate copula with given linear Spearman marginal copulas. Based on a known concordance ordering compatibility criterion, a set of grade correlation inequalities, which must necessarily be satisfied for compatibility, is derived. The existence question for trivariate copulas with compatible linear Spearman marginal copulas is settled in the main result, which states that this set of inequalities is also sufficient for compatibility. The constructive proof makes use of two new classes of trivariate copulas that are obtained from the Bernoulli mixture trivariate copulas through a natural parametric extension. Finally, the obtained classes of trivariate copulas are compared with another class that contains as special case some trivariate copulas with linear Spearman marginal copulas. Since the latter class is incompatible with some type of linear Spearman copulas, the new classes of trivariate copulas build a richer class in this respect. Moreover, in contrast to the mentioned class, which requires in general 11 different elementary copulas in the defining convex linear combination, the new classes require at most five of them, which results in a more parsimonious parametric modelling.