Bivariate copula modelling of successive wave periods in combined sea states. (5th September 2020)

• Record Type: Journal Article
• Authors: Huang, Weinan; Han, Xinyu; Dong, Sheng
• Is Part Of: Estuarine, coastal and shelf science. Volume 242(2020)
• Publication Date: 2020-09-05
• Subjects: Successive wave periods -- Bivariate distribution -- Parametric model -- Mixture model -- Gaussian copula -- Combined sea states; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2020.106860
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: 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. Highlights: Successive wave period distribution patterns in combined sea states are investigated. Laboratory experiments are conducted to generate secondary waves. A novel model to describe bivariate distribution of consecutive wave period is proposed. Comparative study of continuous wave period distributions is carried out. Conditional probability is used for the evaluation of the parametric models.