Mert Gülüm

Development of Two-Dimensional Models for Estimating Densities of Biodiesel-Diesel-Alcohol Ternary Blends

Recently, biodiesel has become one of the most significant clean alternative biofuels because of many advantages. However, it has also some shortcomings such as: higher density and viscosity. The high density of biodiesel can cause an increase in the fuel consumption and NOX emissions. In order to overcome this problem, the blending of biodiesel with diesel fuel or alcohols is generally recommended in the existing literature. Although many one-dimensional models are proposed by different authors for predicting fuel properties of biodiesel-diesel binary blends, two-dimensional models are still inadequate for estimating densities of biodiesel-diesel fuel-alcohol ternary blends. Therefore, in this study, (1) densities of waste cooking oil biodiesel-diesel fuel-ethanol ternary blends were measured at different temperatures (278.15 K–343.15 K) according to ISO test method, and (2) some two-dimensional models, previously suggested by the authors, were fitted to the density data of ternary blends obtained from the authors and specialized literature to determine the best correlation for prediction of density. The quadratic surface model is found to be best predictor to estimate densities of ternary blends.

Temperature Dependence of Densities of Different Biodiesel-Diesel-Alcohol Ternary Blends

In this study, waste cooking oil ethyl ester (biodiesel) was produced via basic transesterification reaction, ethyl ester-diesel-methanol ternary blends including different volume ratios of alcohol (2% and 4%) were prepared, densities of the ternary blends were measured at different temperatures (278.15 K, 283.15 K, 288.15 K, 293.15 K, 298.15 K, 303.15 K, 308.15 K, 313.15 K, 318.15 K, 323.15 K, 328.15 K, and 333.15 K) according to ISO 4787 standard, and the exponential model as a function of temperature was derived using the least squares method to predict density values. Moreover, the exponential model was compared to the well-known linear model, and the reliability of these models was investigated using the density data of rapeseed oil methyl ester-diesel-bioethanol ternary blends measured by Barabas. According to result, the exponential model, suggested by the authors, qualitatively and quantitatively better reflects the variations in densities of different biodiesel-diesel-alcohol ternary blends measured by the authors and Barabas.

Effects of Temperature and Biodiesel Fraction on Dynamic Viscosities of Commercially Available Diesel Fuels and Its Blends with the Highest Methyl Ester Yield Corn Oil Biodisel Produced by Using KOH

The objective of this chapter is to determine the effects of biodiesel fraction in blend (X) and temperature (T) on dynamic viscosities of the highest methyl ester content corn oil biodiesel and its blends with commercially available diesel fuel. For this objective, first, the highest methyl ester content corn oil biodiesel was produced by using potassium hydroxide (KOH) as catalyst and methanol (CH3OH) as alcohol, and the biodiesel was blended with commercially available diesel fuel at the volume ratios of 5, 10, 15, and 20%. Then, dynamic viscosities of pure biodiesel and diesel fuel, their blends were measured at different temperatures of 10, 20, 30, and 40 °C by following DIN 53015 test methods. From the obtained experimental data, one- and two-dimensional models as a function of X or T were derived using the least square regression for estimating dynamic viscosity values of pure fuels or fuel blends. Also, these models were compared to previously published models and measurements to show their validities. According to regression analysis results, among the proposed one-dimensional models, rational ones such as μ = μ(X) = (aX + 1)/(b + cX) with minimum correlation coefficient (R) value of 0.9942 and maximum error value of 4.5976%, μ = μ(X) = (a ∙ X + 1)/(b + c ∙ X) and power ones such as μ = μ(T) = aTb + c with minimum R value of 0.9914 and maximum error value of 3.9733% better represent the dynamic viscosity–biodiesel fraction and dynamic viscosity–temperature relationship, respectively, and these models give higher accuracies for predicting viscosity values. Also, two-dimensional combination surface model including exponential and linear terms such as μ = μ(T, X) = a ∙ ebT + c ∙ edX + eX with the higher R value of 0.9952 and lower maximum error value of 3.2319% was recommended for demonstrating the variations in dynamic viscosity values with respect to biodiesel fraction and temperature simultaneously. Furthermore, the quality of the corn oil biodiesel and its blends were evaluated by determining the other important fuel properties, such as kinematic viscosity, flash point temperature, and higher heating value.

Regression Models for Predicting Some Important Fuel Properties of Corn and Hazelnut Oil Biodiesel–Diesel Fuel Blends

Abstract This chapter deals with the derivation of one-dimensional models to estimate some important fuel features of different biodiesel–diesel fuel (DF) blends. For the derivation of the models, biodiesels were synthesized through a transesterification reaction using hazelnut and corn oils, and the produced biodiesels were mixed with DF at 5%, 10%, 15%, 20%, 50%, and 75% on a volume basis. The kinematic viscosity, higher heating value, and flash point of the prepared Corn oil biodiesel–DF and Hazelnut oil biodiesel–DF blends were determined according to the related international standards. One-dimensional models were derived through the least squares regression method to estimate these fuel features. For all models that were tried, calculated regression constants and correlation coefficients are given as tables.

Mechanical and corrosion properties of brass exposed to waste sunflower oil biodiesel-diesel fuel blends

Abstract Biodiesel has recently received increasing attention because of many advantages such as higher cetane number and flash point compared to diesel fuel. However, corrosion of engine parts exposed to biodiesel or biodiesel-diesel fuel blends is still a critical challenge in the biodiesel industry. In the existing literature, there is still a lack of systematic studies including corrosion process in light alloy and changes in mechanical and fuel properties of engine parts (such as brass) after exposure to biodiesel. Therefore, in this study, (1) waste sunflower oil biodiesel (WSOB, B100) was supplied and blended with diesel fuel (B0) at the volume ratios of 10%, 20%, and 40, which are called as B10, B20, and B40, as usual. The important fuel properties of the biodiesel-diesel fuel blends were also analyzed using ASTM test methods. (2) Corrosion characteristics of brass exposed to the biodiesel-diesel fuel blends were determined by means of a static immersion method at room temperature. (3) Mechanical properties of brass were investigated before and after the corrosion test. Finally, (4) variations in surface morphologies of the brass coupons were researched. According to the experimental results, the corrosion rate (0.3810 mpy) of brass exposed to B100 was found to be higher than that of brass exposed to B0 (0.1330 mpy) for the exposure duration of 960 hours. The Brinell hardness numbers (BHN) were determined as 406.265, 477.713, 541.983, 579.448, and 636.602 N/mm2 while the tensile strengths (TS) were 1381.30, 1624.22, 1842.743, 1970.13, and 2164.45 MPa for B0, B10, B20, B40, and B100, respectively. BHN and TS values of B10 were closer to that of B0. Therefore, B10 was found to be a more suitable alternative to diesel fuel in terms of fuel property and corrosion characteristic. The results of this study can promote thermo-physical property collection for biofuels and guide for corrosion studies related to the industrial applications of diesel-biodiesel blends and pure biodiesel.