Print Email Facebook Twitter Probabilistic scheduling of offshore operations using copula based environmental time series Title Probabilistic scheduling of offshore operations using copula based environmental time series: An application for cable installation management for offshore wind farms Author Leontaris, G. (TU Delft Integral Design & Management) Morales Napoles, O. (TU Delft Hydraulic Structures and Flood Risk) Wolfert, A.R.M. (TU Delft Integral Design & Management; TU Delft Materials and Environment) Date 2016-10-01 Abstract There are numerous uncertainties that impact offshore operations. However, environmental uncertainties concerning variables such as wave height and wind speed are crucial because these may affect installation and maintenance operations with potential delays and financial consequences. In order to include these uncertainties into the duration estimation, adequate tools should be developed to simulate an installation scenario for a large number of historical environmental data. Data regarding environmental time series are usually scarce and limited, therefore they should be modelled. Since the environmental variables are in reality dependent, we propose a probabilistic method for their construction using copulas. To demonstrate the effectiveness of this method compared to the cases where observed or independently constructed environmental time series are used, a realistic cable installation scenario for an offshore wind farm was simulated. It was found that the proposed method should be followed to acquire more reliable and accurate estimation of the installation's duration. Subject CopulasEnvironmental time seriesOffshore wind farmsProject managementSimulationStochastic model applications To reference this document use: http://resolver.tudelft.nl/uuid:f361f293-66a4-426f-9bf6-7610361fc8d1 DOI https://doi.org/10.1016/j.oceaneng.2016.08.029 Embargo date 2018-10-28 ISSN 0029-8018 Source Ocean Engineering, 125, 328-341 Part of collection Institutional Repository Document type journal article Rights © 2016 G. Leontaris, O. Morales Napoles, A.R.M. Wolfert Files PDF Probabilistic_scheduling_ ... as_AAM.pdf 1.77 MB Close viewer /islandora/object/uuid:f361f293-66a4-426f-9bf6-7610361fc8d1/datastream/OBJ/view