Joint Modelling of Wave Energy Flux and Wave Direction

In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wa...

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Published in:Processes
Main Authors: Takvor H. Soukissian, Flora E. Karathanasi
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
Online Access:https://doi.org/10.3390/pr9030460
https://doaj.org/article/76e9143361724dd28c0382e219fb6407
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spelling ftdoajarticles:oai:doaj.org/article:76e9143361724dd28c0382e219fb6407 2024-01-07T09:45:11+01:00 Joint Modelling of Wave Energy Flux and Wave Direction Takvor H. Soukissian Flora E. Karathanasi 2021-03-01T00:00:00Z https://doi.org/10.3390/pr9030460 https://doaj.org/article/76e9143361724dd28c0382e219fb6407 EN eng MDPI AG https://www.mdpi.com/2227-9717/9/3/460 https://doaj.org/toc/2227-9717 doi:10.3390/pr9030460 2227-9717 https://doaj.org/article/76e9143361724dd28c0382e219fb6407 Processes, Vol 9, Iss 3, p 460 (2021) wave energy flux wave direction mixture distribution bivariate distribution wave energy converters European seas Chemical technology TP1-1185 Chemistry QD1-999 article 2021 ftdoajarticles https://doi.org/10.3390/pr9030460 2023-12-10T01:47:54Z In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wave energy converters. In this work, the joint probabilistic description of wave energy flux and wave direction is performed and evaluated. Parametric univariate models are implemented for the description of wave energy flux and wave direction. For wave energy flux, conventional, and mixture distributions are examined while for wave direction proven and efficient finite mixtures of von Mises distributions are used. The bivariate modelling is based on the implementation of the Johnson–Wehrly model. The examined models are applied on long-term measured wave data at three offshore locations in Greece and hindcast numerical wave model data at three locations in the western Mediterranean, the North Sea, and the North Atlantic Ocean. A global criterion that combines five individual goodness-of-fit criteria into a single expression is used to evaluate the performance of bivariate models. From the optimum bivariate model, the expected wave energy flux as function of wave direction and the distribution of wave energy flux for the mean and most probable wave directions are also obtained. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Processes 9 3 460
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic wave energy flux
wave direction
mixture distribution
bivariate distribution
wave energy converters
European seas
Chemical technology
TP1-1185
Chemistry
QD1-999
spellingShingle wave energy flux
wave direction
mixture distribution
bivariate distribution
wave energy converters
European seas
Chemical technology
TP1-1185
Chemistry
QD1-999
Takvor H. Soukissian
Flora E. Karathanasi
Joint Modelling of Wave Energy Flux and Wave Direction
topic_facet wave energy flux
wave direction
mixture distribution
bivariate distribution
wave energy converters
European seas
Chemical technology
TP1-1185
Chemistry
QD1-999
description In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wave energy converters. In this work, the joint probabilistic description of wave energy flux and wave direction is performed and evaluated. Parametric univariate models are implemented for the description of wave energy flux and wave direction. For wave energy flux, conventional, and mixture distributions are examined while for wave direction proven and efficient finite mixtures of von Mises distributions are used. The bivariate modelling is based on the implementation of the Johnson–Wehrly model. The examined models are applied on long-term measured wave data at three offshore locations in Greece and hindcast numerical wave model data at three locations in the western Mediterranean, the North Sea, and the North Atlantic Ocean. A global criterion that combines five individual goodness-of-fit criteria into a single expression is used to evaluate the performance of bivariate models. From the optimum bivariate model, the expected wave energy flux as function of wave direction and the distribution of wave energy flux for the mean and most probable wave directions are also obtained.
format Article in Journal/Newspaper
author Takvor H. Soukissian
Flora E. Karathanasi
author_facet Takvor H. Soukissian
Flora E. Karathanasi
author_sort Takvor H. Soukissian
title Joint Modelling of Wave Energy Flux and Wave Direction
title_short Joint Modelling of Wave Energy Flux and Wave Direction
title_full Joint Modelling of Wave Energy Flux and Wave Direction
title_fullStr Joint Modelling of Wave Energy Flux and Wave Direction
title_full_unstemmed Joint Modelling of Wave Energy Flux and Wave Direction
title_sort joint modelling of wave energy flux and wave direction
publisher MDPI AG
publishDate 2021
url https://doi.org/10.3390/pr9030460
https://doaj.org/article/76e9143361724dd28c0382e219fb6407
genre North Atlantic
genre_facet North Atlantic
op_source Processes, Vol 9, Iss 3, p 460 (2021)
op_relation https://www.mdpi.com/2227-9717/9/3/460
https://doaj.org/toc/2227-9717
doi:10.3390/pr9030460
2227-9717
https://doaj.org/article/76e9143361724dd28c0382e219fb6407
op_doi https://doi.org/10.3390/pr9030460
container_title Processes
container_volume 9
container_issue 3
container_start_page 460
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