Statistical Modeling and Applications of Joint Distributions for Significant Wave Height, Spectral Peak Period, and Peak Direction of Propagation: A Case Study in the Norwegian Sea
The estimation of long-term extreme response is a crucial task in the design of marine structures. The target extreme responses are typically defined by annual exceedance probabilities of 10 −2 and 10 −4 . Various approaches can be employed for this purpose, with preference given to statistical long...
| Published in: | Journal of Marine Science and Engineering |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
MDPI AG
2023
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| Subjects: | |
| Online Access: | https://doi.org/10.3390/jmse11122372 https://doaj.org/article/9be8a4d7a933404a9637420f45f0fb6a |
| Summary: | The estimation of long-term extreme response is a crucial task in the design of marine structures. The target extreme responses are typically defined by annual exceedance probabilities of 10 −2 and 10 −4 . Various approaches can be employed for this purpose, with preference given to statistical long-term analysis, which involves aggregating the exceedance probabilities of all potential sea states contributing to the exceedance of the target extremes. A joint model encompassing important metocean parameters such as wind, waves, and current is often necessary. This study specifically focuses on waves and wave-induced responses. In characterizing short-term sea state conditions, significant wave height ( <semantics> H s </semantics> ), spectral peak period ( <semantics> T p </semantics> ) and peak direction of propagation ( <semantics> Φ p </semantics> ) are identified as the most important sea state characteristics. The objective of this work is to present the results of the joint model for the three sea state parameters, i.e., <semantics> H s </semantics> , <semantics> T p </semantics> and <semantics> Φ p </semantics> , at an offshore site in the Norwegian Sea. The conditional modeling approach is applied using long-term hindcast data, and different statistical models are discussed for fitting the marginal and conditional distributions. The fitted parameters for all directional sectors are provided, offering a comprehensive representation of the joint model for direct use in long-term response analysis. Two case studies are included to illustrate the application of the fitted joint model in long-term response analyses. The case studies identify the governing wave directions and the most important combinations of short-term sea state characteristics regarding the estimation of long-term extreme responses. |
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