The Effect of Temperature and Biodiesel Fraction on the Viscosity of Biodiesel-Diesel Fuel Blends


This study aims determination of viscosity of the corn oil biodiesel and its blends with petrodiesel fuel at different temperatures. For this purpose, corn oil biodiesel was produced by using sodium hydroxide (NaOH) as catalyst and methanol (CH3OH) as alcohol. To produce the lowest viscosity corn oil biodiesel, many production parameters such as catalyst concentration, reaction temperature, reaction time and alcohol/oil molar ratio were optimized at the first stage which is not consisted in this study. At the second stage concerned mainly with this study, the biodiesel produced using optimum parameters was blended with petrodiesel fuel at the volume ratios of 5, 10, 15 and 20% and each blend obtained was studied to determine viscosity at different temperatures such as 10, 20, 30 and 40℃. From the experimental data, one and two dimensional curve fit equations were determined by using the least squares regression. In one dimensional curve fits, exponential models (μ=μ_0+ae^(-bϕ)) were found suitable to predict kinematic and dynamic viscosities of the blends with respect to temperature and biodiesel fraction. In this exponential equation, ϕ represents either biodiesel fraction X or blend temperature T while μ_0, a and b are curve fit coefficients. In two dimensional cure fits, 3rd order surface polynomials such as μ=μ(T,X)=a+bT+cX+dT^2+eTX+fX^2+gT^3+hT^2 X+kTX^2 were fitted to the kinematic or dynamic viscosity data. For all the fitted equations, the calculated curve fit coefficients and regression coefficients (R^2) were given as tables. The worst regression coefficient was obtained as 0.9875, while in most situations it has closer to 1.0.

Author Information
Atilla Bi̇lgi̇n, Karadeniz Technical University, Mechanical Engineering Department
Mert Gülüm, Karadeniz Technical University, Mechanical Engineering Department

Paper Information
Conference: ECSEE2014
Stream: Energy: Renewable Energy and Environmental Solutions

This paper is part of the ECSEE2014 Conference Proceedings (View)
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Posted by James Alexander Gordon