{"title":"Long-Term Analysis Applied to Mooring Systems Design","authors":"Pedro Seabra, L. Sagrilo, P. Esperança","doi":"10.1115/omae2020-18211","DOIUrl":null,"url":null,"abstract":"\n Nowadays, the most used methodology to predict line tensions is the short-term coupled analysis, where the mooring system responses are obtained by a time-domain analysis for only some specific design combinations of extreme environmental conditions. This mooring analysis demands certain considerations and it is not the best way to obtain the offshore structure responses. The advances in both quantity and quality of collected environmental data and the increase of the computers processing power has enabled to consider the approach of more accurate long-term methodologies for mooring systems design. This paper proposes a numerical/computational procedure to obtain the extreme loads (ULS) acting on offshore platforms’ mooring lines. The work is based on the methodology of long-term analysis, employing a 10-yr long short-term environmental dataset of 3-h sea-states, where each short-term environmental condition is composed of the simultaneously observed environmental parameters of wave (sea and swell), wind and current. The methodology is applied to the analysis of three different mooring systems: a) spread-moored FPSO, b) Semi-Submersible platform and c) turret-moored FPSO. The Bootstrap approach is employed in order to take into account the statistical uncertainty associated to the estimated long-term most probable extreme response due to the limited number of short-term environmental conditions. The work was carried out using Dynasim software [1] to generate the time domain tension time series, which were later post-processed by using computational codes developed with Python software. Longer short-term numerical simulations lengths than the short-term period (3-h) have been investigated in order to understand the influence of this parameter on the final extreme long-term top tensions.","PeriodicalId":297013,"journal":{"name":"Volume 2A: Structures, Safety, and Reliability","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2A: Structures, Safety, and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/omae2020-18211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Nowadays, the most used methodology to predict line tensions is the short-term coupled analysis, where the mooring system responses are obtained by a time-domain analysis for only some specific design combinations of extreme environmental conditions. This mooring analysis demands certain considerations and it is not the best way to obtain the offshore structure responses. The advances in both quantity and quality of collected environmental data and the increase of the computers processing power has enabled to consider the approach of more accurate long-term methodologies for mooring systems design. This paper proposes a numerical/computational procedure to obtain the extreme loads (ULS) acting on offshore platforms’ mooring lines. The work is based on the methodology of long-term analysis, employing a 10-yr long short-term environmental dataset of 3-h sea-states, where each short-term environmental condition is composed of the simultaneously observed environmental parameters of wave (sea and swell), wind and current. The methodology is applied to the analysis of three different mooring systems: a) spread-moored FPSO, b) Semi-Submersible platform and c) turret-moored FPSO. The Bootstrap approach is employed in order to take into account the statistical uncertainty associated to the estimated long-term most probable extreme response due to the limited number of short-term environmental conditions. The work was carried out using Dynasim software [1] to generate the time domain tension time series, which were later post-processed by using computational codes developed with Python software. Longer short-term numerical simulations lengths than the short-term period (3-h) have been investigated in order to understand the influence of this parameter on the final extreme long-term top tensions.