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dc.contributor.authorCostas Gómez, Raquel
dc.contributor.authorCarro Fidalgo, Humberto
dc.contributor.authorFiguero, A.
dc.contributor.authorPeña González, Enrique
dc.contributor.authorSande, José
dc.date.accessioned2023-04-26T16:01:39Z
dc.date.available2023-04-26T16:01:39Z
dc.date.issued2023
dc.identifier.citationCostas, R.; Carro, H.; Figuero, A.; Peña, E.; Sande, J. A Decision-Making Tool for Port Operations Based on Downtime Risk and Met-Ocean Conditions including Infragravity Wave Forecast. J. Mar. Sci. Eng. 2023, 11, 536. https://doi.org/10.3390/jmse11030536es_ES
dc.identifier.urihttp://hdl.handle.net/2183/32947
dc.description.abstract[Abstract:] Port downtime leads to economic losses and reductions in safety levels. This problem is generally assessed in terms of uni-variable thresholds, despite its multidimensional nature. The aim of the present study is to develop a downtime probability forecasting tool, based on real problems at the Outer Port of Punta Langosteira (Spain), and including infragravity wave prediction. The combination of measurements from three pressure sensors and a tide gauge, together with machine-learning techniques, made it possible to generate long wave prognostication at different frequencies. A fitting correlation of 0.95 and 0.9 and a root mean squared error (RMSE) of 0.022 m and 0.012 m were achieved for gravity and infragravity waves, respectively. A wave hindcast in the berthing areas, met-ocean forecast data, and information on 15 real operational problems between 2017 and 2022, were all used to build a classification model for downtime probability estimation. The proposed use of this tool addresses the problems that arise when two consecutive sea states have thresholds above 3.97%. This is the limit for guaranteeing the safety of port operations and has a cost of just 0.6 unnecessary interruptions of operations per year. The methodology is easily exportable to other facilities for an adequate assessment of downtime risks.es_ES
dc.description.sponsorshipThis research was carried out with the grant PID2020-112794RB-I00 funded by MCIN/AEI/10.13039/501100011033 and the FPI predoctoral grants from the Spanish Ministry of Science, Innovation, and Universities (PRE2018-083777 and PRE2021-100141).
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112794RB-I00es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PRE2018-083777es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PRE2021-100141es_ES
dc.relation.urihttps://doi.org/10.3390/jmse11030536es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectLong waves predictiones_ES
dc.subjectPort operabilityes_ES
dc.subjectMultidimensional operational thresholdes_ES
dc.subjectMachine learninges_ES
dc.subjectPort managementes_ES
dc.titleA decision-making tool for port operations based on downtime risk and met-ocean conditions including infragravity wave forecastes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleJournal of Marine Science and Engineeringes_ES
UDC.volume11es_ES
UDC.issue3es_ES
UDC.startPage536es_ES
dc.identifier.doi10.3390/jmse11030536


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