%0 Journal Article
%A soleymani, alireza
%A sharifi, mohammad hossein
%A edalat, pedram
%A sharifi, mohammad mahdi
%A karim zadeh, samad
%T Linear Modelling of Marine Vessels Fuel Consumption for Ration of Subsidized Fuel
%J International Journal of Maritime Technology
%V 10
%N 0
%U http://ijmt.ir/article-1-637-en.html
%R
%D 2018
%K Marine vessels, Fuel consumption, Linear Modelling, Regression analysis, Cross sectional data,
%X An approach to deal with the phenomenon of maritime fuel smuggling is to control the quantity of fuel that is supplied to vessels. For the same reason, fuel is delivered to marine vessels in Iran in accordance with the ration defined by the National Iranian Oil Products Distribution Company (NIOPDC). The ration is determined by a fuel consumption formula defined by the Food and Agriculture Organization of the United Nations (FAO) which is used to estimate the fuel cost of agricultural and road construction equipment and machinery. The use of this formula for maritime usage renders fuel allocation to vessels inappropriate. This paper makes a database containing the specifications of 452 vessels, including length, width, summer draft, economical speed, engine power and hourly fuel consumption values. Then, a linear model is estimated over the available database. Ordinary least square method is used for regression analysis. Then, the estimated linear model is compared with FAO formula and linear model is selected as the optimum model to estimate vessel fuel consumption as close to the actual value of fuel consumption as possible. This linear model contains three parameters: engines power, economical speed, and immersed volume as defined by multiplying three parameters of length, width, and summer draft. In general, the amount of fuel consumption estimated by FAO formula is about 50% greater than that estimated by the linear model.
%> http://ijmt.ir/article-1-637-en.pdf
%P 7-13
%& 7
%!
%9 Research Paper
%L A-10-724-2
%+ Faculty Member of Marine Engineering Department, Petroleum University of Technology
%G eng
%@ 2345-6000
%[ 2018