Abstract
The objectives of this chapter are to measure densities of the highest methyl ester yield corn oil biodiesel and its blends with commercially available diesel fuel at different temperatures and also to develop new one- and two-dimensional models for predicting density values by using the measurements. For these objectives, first, corn oil biodiesel having the highest methyl ester content was blended with commercially available diesel fuel at the volume ratios of 5%, 10%, 15%, and 20%, and densities of each blend were measured at different temperatures of 10, 20, 30, and 40 °C by following the ISO test method. Then, some one- and two-dimensional models were fitted to the experimental data, and these models were compared with each other. According to results, among one-dimensional models, linear ρ = ρ(X) = a + bX and power ρ = ρ(T) = aT b + c ones were found to be more suitable for representing the density–biodiesel fraction in the blend and density–temperature relationship, respectively. Also, when compared with the two-dimensional model, linear with respect to X and power with respect to T, ρ = ρ(T, X) = aT b + cX, the linear surface ρ = ρ(T, X) = a + bT + cX gave a higher degree of accuracy to represent the variations of densities of the blends with respect to temperature and biodiesel fraction at the same time. Moreover, the qualities of the corn oil biodiesel and its blends was evaluated by determining other important fuel properties such as kinematic viscosity, flash point temperature, and higher heating value.
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The authors express their gratitude to Karadeniz Technical University Scientific Research Projects Fund for financial support received (Project No: 9745).
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Bilgin, A., Gülüm, M. (2018). Effects of Temperature and Biodiesel Fraction on Densities of Commercially Available Diesel Fuel and Its Blends with the Highest Methyl Ester Yield Corn Oil Biodiesel Produced by Using NaOH. In: Aloui, F., Dincer, I. (eds) Exergy for A Better Environment and Improved Sustainability 2. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-62575-1_5
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