Development of a method to estimate the propulsion power of a VLCC Tanker based on operational data

Σέντερης, Αλέξανδρος; Senteris, Alexandros

dc.contributor.author	Σέντερης, Αλέξανδρος	el
dc.contributor.author	Senteris, Alexandros	en
dc.date.accessioned	2019-03-14T09:07:42Z
dc.date.available	2019-03-14T09:07:42Z
dc.date.issued	2019-03-14
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/48435
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.16315
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/gr/	*
dc.subject	Τεχνητά νευρωνικά δίκτυα	el
dc.subject	Μοντελοποίηση	el
dc.subject	Modeling	en
dc.subject	Artificial neural networks	en
dc.subject	Performance	en
dc.subject	Απόδοση	el
dc.subject	Εργαλείο ανάλυσης	el
dc.subject	Analysis tool	en
dc.title	Development of a method to estimate the propulsion power of a VLCC Tanker based on operational data	en
dc.title	Ανάπτυξη μεθόδου για την εκτίμηση ισχύος πρόωσης δεξαμενοπλοίου τύπου VLCC με χρήση πραγματικών δεδομένων λειτουργίας	el
heal.type	bachelorThesis
heal.classification	Ναυπηγική	el
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2018-10-24
heal.abstract	Ανάπτυξη μεθόδου για την εκτίμηση ισχύος πρόωσης δεξαμενοπλοίου τύπου VLCC με χρήση πραγματικών δεδομένων λειτουργίας	el
heal.abstract	The purpose of this thesis is to develop a real-time vessel performance analysis system to evaluate the condition of ships with respect to their clean hull and clean propeller condition. During operation, the vessel will experience an increase of resistance due to several factors, linked to the sailing conditions. Added wave resistance, wind resistance, shallow water effect and trim are examples of parameters, which affect the power (energy) needed to propel the vessel. Any increase in resistance will result to the increase of fuel consumption and thus the increase of harmful emissions to the environment. A robust monitoring and analysis system can be used as a supporting tool to decisions related to actions aiming to improve performance. The performance evaluation is based on a vessel-specific model which takes into account operational and weather condition, trying to assess and estimate power needed to overcome all resistance components, while assuming a clean hull and propeller. The current thesis is based on the analysis of data, logged through the automated data transmission system of sensors’ onboard a 319,000 tdw VLCC managed by Maran Tankers Management Inc. Through mapping of these parameters to the output target (the shaft power measured by a torque meter) the model is generated. The goal of the developed system is to investigate the potential use of Artificial Neural Networks (ANNs) in estimating the power needed to propel the vessel in any given operational, environmental and loading condition, assuming a clean hull and clean propeller condition. Multi-layer perceptron (MLP) networks, were selected to model the vessel’s behaviour. The increasing amount of data transmitted to shore is creating the opportunity to develop systems based on information that until recently was not available. ANNs and in particular, MLPs, are an effective way to process this information. The results indicate that such an approach could be successfully applied, giving the potential to approximate complex non-linear regression problems, based on a reliable set of measured data.	en
heal.advisorName	Ζαραφωνίτης, Γεώργιος	el
heal.committeeMemberName	Τζαμπίρας, Γεώργιος	el
heal.committeeMemberName	Σπύρου, Κωνσταντίνος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ναυπηγών Μηχανολόγων Μηχανικών. Τομέας Μελέτης Πλοίου και Θαλάσσιων Μεταφορών	el
heal.academicPublisherID	ntua
heal.numberOfPages	92 σ.
heal.fullTextAvailability	true