Fuel consumption assessment on actual operation of an LPG carrier

Μερκούρη, Ολυμπία; Merkouri, Olympia

dc.contributor.author	Μερκούρη, Ολυμπία	el
dc.contributor.author	Merkouri, Olympia	en
dc.date.accessioned	2026-05-15T10:01:58Z
dc.date.available	2026-05-15T10:01:58Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/64673
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.32367
dc.rights	Default License
dc.subject	Fuel consumption	en
dc.subject	Operating modes	en
dc.subject	Lpg carrier	en
dc.subject	Data analysis	en
dc.subject	Ανάλυση δεδομένων	el
dc.subject	Επιχειρησιακό προφίλ	el
dc.subject	Διορθωτικοί συντελεστές	el
dc.subject	Κατανάλωση καυσίμου	el
dc.title	Fuel consumption assessment on actual operation of an LPG carrier	en
heal.type	bachelorThesis
heal.classification	Ναυτική Μηχανολογία	el
heal.language	en
heal.access	campus
heal.recordProvider	ntua	el
heal.publicationDate	2026-02-05
heal.abstract	Fuel consumption measurement, estimation, and prediction are increasingly prioritized in the shipping industry, in line with international guidelines. Accurate data from one vessel are essential for performance monitoring and optimized route planning for a broader fleet. Conversely, newbuildings often rely on generic yard logbook estimates, offering limited insight into actual operating conditions. This thesis develops a tool that leverages preliminary information from technical guides, shop tests, and sea trials to predict vessel performance under real operational conditions using statistical analysis. Engine room data, combined with a large dataset from an existing vessel, provide a detailed representation of the vessel’s operational profile. However, measurement errors remain and must be addressed through statistical corrections or other methods to build a robust model. Additional inputs, including detailed engine parameters, as well as advanced machine learning and regression techniques, could further enhance the model’s predictive accuracy. The proposed tool integrates all available technical documentation and operational information, considering the operation of the vessel’s main prime movers, including the main and auxiliary engines. A holistic approach based on this model could improve fuel consumption predictions for specific vessel types, accounting for different machinery configurations and chartering itineraries, while enhancing the model’s generalization and predictive capabilities through additional data and analytical tools.	en
heal.advisorName	Δημόπουλος, Γεώργιος	el
heal.committeeMemberName	Παπαδόπουλος, Χρήστος	el
heal.committeeMemberName	Μπαρδής, Κωνσταντίνος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ναυπηγών Μηχανολόγων Μηχανικών. Τομέας Ναυτικής Μηχανολογίας	el
heal.academicPublisherID	ntua
heal.numberOfPages	138 σ.	el
heal.fullTextAvailability	false