Stochastic bivariate time series models of waves in the North Sea and their application in simulation-based design
| Autor: | Ole Johan Jørgensen Lønnum, Endre Sandvik, Bjørn Egil Asbjørnslett |
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| Rok vydání: | 2019 |
| Předmět: |
Markov chain
Series (mathematics) Computer science Sampling (statistics) 020101 civil engineering Ocean Engineering 02 engineering and technology Replicate Bivariate analysis Markov model 01 natural sciences 010305 fluids & plasmas 0201 civil engineering 0103 physical sciences Hindcast Significant wave height Algorithm |
| Zdroj: | Applied Ocean Research. 82:283-295 |
| ISSN: | 0141-1187 |
| Popis: | In this paper, we present and evaluate three long-term wave models for application in simulation-based design of ships and marine structures. Designers and researchers often rely on historical weather data as a source for ocean area characteristics based on hindcast datasets or in-situ measurements. The limited access and size of historical datasets reduces repeatability of simulations and analyses, making it difficult to assess the sampling variability of performance and loads on marine vessels and structures. Markov, VAR and VARMA wave models, producing independent long-term time series of significant wave height (Hs) and spectral peak period (Tp), is presented as possible solutions to this problem. The models are tested and compared by addressing how the models affect interpretation of design concepts and the ability to replicate statistical and physical characteristics of the wave process. Our results show that the VAR and VARMA models perform sufficiently in describing design performance, but does not capture the physical process fully. The Markov model is found to perform worst of the tested models in the applied tests, especially for measures covering several consecutive sea states. |
| Databáze: | OpenAIRE |
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