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Offloading operation bivariate extreme response statistics for FPSO vessel

The Floating Production Storage and Offloading unit (FPSO) is an offshore unit producing and storing crude oil prior to tanker transport. An important design concern is an accurate prediction of risky dynamic hawser tensions during FPSO offloading operations. Bivariate extreme hawser tension contour...

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Autores principales: Gaidai, Oleg, Cao, Yu, Xu, Xiaosen, Xing, Yihan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033654/
https://www.ncbi.nlm.nih.gov/pubmed/36949113
http://dx.doi.org/10.1038/s41598-023-31533-8
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author Gaidai, Oleg
Cao, Yu
Xu, Xiaosen
Xing, Yihan
author_facet Gaidai, Oleg
Cao, Yu
Xu, Xiaosen
Xing, Yihan
author_sort Gaidai, Oleg
collection PubMed
description The Floating Production Storage and Offloading unit (FPSO) is an offshore unit producing and storing crude oil prior to tanker transport. An important design concern is an accurate prediction of risky dynamic hawser tensions during FPSO offloading operations. Bivariate extreme hawser tension contours are important for selecting proper design values. This paper employed the AQWA hydrodynamic software to analyze vessel hydrodynamic wave loads dynamic response, acting on FPSO vessels under realistic sea state conditions. This paper presents an efficient method for estimating FPSO bivariate response statistics based on numerical simulations validated by various experiments. The bivariate Average Conditional Exceedance Rate (ACER2D) method offers an accurate bivariate extreme value probability distribution and return period contours estimation, utilizing available data efficiently. The two-dimensional probability contours, corresponding to low probability return periods, are easily obtained by the ACER2D method. The performance of the presented method has shown that the ACER2D method provides an efficient and accurate prediction of extreme return period contours. The suggested approach may be used for FPSO vessel design, minimizing potential FPSO hawser damage. Bivariate contours yield bivariate design points, as opposed to a pair of uncoupled univariate design points with the same return period as currently adopted in the industry.
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spelling pubmed-100336542023-03-24 Offloading operation bivariate extreme response statistics for FPSO vessel Gaidai, Oleg Cao, Yu Xu, Xiaosen Xing, Yihan Sci Rep Article The Floating Production Storage and Offloading unit (FPSO) is an offshore unit producing and storing crude oil prior to tanker transport. An important design concern is an accurate prediction of risky dynamic hawser tensions during FPSO offloading operations. Bivariate extreme hawser tension contours are important for selecting proper design values. This paper employed the AQWA hydrodynamic software to analyze vessel hydrodynamic wave loads dynamic response, acting on FPSO vessels under realistic sea state conditions. This paper presents an efficient method for estimating FPSO bivariate response statistics based on numerical simulations validated by various experiments. The bivariate Average Conditional Exceedance Rate (ACER2D) method offers an accurate bivariate extreme value probability distribution and return period contours estimation, utilizing available data efficiently. The two-dimensional probability contours, corresponding to low probability return periods, are easily obtained by the ACER2D method. The performance of the presented method has shown that the ACER2D method provides an efficient and accurate prediction of extreme return period contours. The suggested approach may be used for FPSO vessel design, minimizing potential FPSO hawser damage. Bivariate contours yield bivariate design points, as opposed to a pair of uncoupled univariate design points with the same return period as currently adopted in the industry. Nature Publishing Group UK 2023-03-22 /pmc/articles/PMC10033654/ /pubmed/36949113 http://dx.doi.org/10.1038/s41598-023-31533-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Gaidai, Oleg
Cao, Yu
Xu, Xiaosen
Xing, Yihan
Offloading operation bivariate extreme response statistics for FPSO vessel
title Offloading operation bivariate extreme response statistics for FPSO vessel
title_full Offloading operation bivariate extreme response statistics for FPSO vessel
title_fullStr Offloading operation bivariate extreme response statistics for FPSO vessel
title_full_unstemmed Offloading operation bivariate extreme response statistics for FPSO vessel
title_short Offloading operation bivariate extreme response statistics for FPSO vessel
title_sort offloading operation bivariate extreme response statistics for fpso vessel
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10033654/
https://www.ncbi.nlm.nih.gov/pubmed/36949113
http://dx.doi.org/10.1038/s41598-023-31533-8
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