Bivariate copula modelling of successive wave periods in combined sea states
Bivariate copula modelling of successive wave periods in combined sea states
复制标题
组合海况下连续波浪周期的双变量 copula 建模
DOI：
10.1016/j.ecss.2020.106860
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发表时间：
2020-09
期刊：
影响因子：
--
通讯作者：
Dong Sheng
中科院分区：
文献类型：
--
作者：
Huang Weinan;Han Xinyu;Dong Sheng
连续波周期的联合分布在海岸和海洋结构物共振效应研究中起着非常重要的作用。直到最近，对连续周期统计的研究几乎完全集中在单波系统上。本文提出了一种由混合对数正态分布和高斯Copula组合而成的参数模型来描述组合海况下的单个连续波周期。利用实验室采集的二次波数据和六参数Ochi-Hubble模型的模拟数据，比较了新模型和基于条件模型法和Copula函数的两种附加分布。考虑和讨论了九种类型的组合海态。用前一波周期给出的波周期的条件概率来评估所采用的模型在共振研究中的应用。当波纹呈现多峰特性，并且涉及两波系统时，传统的模型是不合适的，它们的谱峰被广泛地分开。与其他两种方法相比，混合模型更准确地描述了双变量分布，并改进了分析海洋结构物共振效应的性能。
The joint distribution of successive wave periods plays a very important role in the study of resonant effects on coastal and marine structures. Until recently, studies on the statistics of consecutive periods have almost exclusively focused on single-wave systems. This paper proposes a parametric model established from a combination of a mixture lognormal distribution and Gaussian copula to describe individual successive wave periods in combined sea states. This new model, together with two additional distributions based on the conditional modelling method and the copula function, respectively, are compared, with reference to secondary wave data collected in laboratory experiments and simulated data obtained by a six-parameter Ochi-Hubble model. Nine types of combined sea states are considered and discussed. The conditional probability of the wave period, given by the previous wave period, is used to assess the application of the adopted models to the resonance study. Conventional models are unsuitable when the patterns exhibit multimodal characteristics and involve two-wave systems whose spectral peaks are widely separated. The mixture model provides a more accurate description of the bivariate distribution and improved performance in the analysis of the resonant effects on marine structures than the other two approaches.
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DOI：
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