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Computational Analysis of Air Lubrication System for Commercial Shipping and Impacts on Fuel Consumption

Authors: Andreas G. Fotopoulos; Dionissios P. Margaris;

Computational Analysis of Air Lubrication System for Commercial Shipping and Impacts on Fuel Consumption

Abstract

Our study presents the computational implementation of an air lubrication system on a commercial ship with 154,800 m3 Liquified Natural Gas capacity. The air lubrication reduces the skin friction between the ship’s wetted area and sea water. We analyze the real operating conditions as well as the assumptions, that will approach the problem as accurately as possible. The computational analysis is performed with the ANSYS FLUENT software. Two separate geometries (two different models) are drawn for a ship’s hull: with and without an air lubrication system. Our aim is to extract two different skin friction coefficients, which affect the fuel consumption and the CO2 emissions of the ship. A ship’s hull has never been designed before in real scale with air lubrication injectors adjusted in a computational environment, in order to simulate the function of air lubrication system. The system’s impact on the minimization of LNG transfer cost and on the reduction in fuel consumption and CO2 emissions is also examined. The study demonstrates the way to install the entire system in a new building. Fuel consumption can be reduced by up to 8%, and daily savings could reach up to EUR 8000 per travelling day.

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Keywords

skin friction coefficient, Electronic computers. Computer science, air lubrication system, decrease of fuel consumption and emissions, QA75.5-76.95, ANSYS FLUENT CFD analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
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