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A comprehensive study on measurement and prediction of viscosity of biodiesel-diesel-alcohol ternary blends

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  • Gülüm, Mert
  • Bilgin, Atilla

Abstract

Recently, biodiesel is receiving global attention as an alternative fuel for diesel engines because of its many advantages compared to petroleum-based diesel fuel. Despite many advantages, it has also some drawbacks such as: poor flow characteristics, lower energy content, higher price and viscosity. Higher viscosity leading poor atomization with larger droplet size results in bad mixing quality and incomplete combustion. Blending of biodiesel with diesel or alcohol is one of the most appropriate techniques to overcome high viscosity problem. Although viscosity data of biodiesel-diesel fuel binary blends at different temperatures are abundantly available in the literature, these of ethyl ester-diesel-alcohol ternary blends including especially higher alcohols are still insufficient. Therefore, in this study, waste cooking oil ethyl ester (biodiesel) was produced by means of transesterification, and it was blended with diesel fuel and different alcohols (methanol, ethanol, isopropanol, n-butanol and n-pentanol). Viscosities of the prepared ternary blends were measured at different temperatures accordingly DIN 53015. Finally, a rational model depending on blend temperature or alcohol fraction was proposed for estimating viscosities of them, and it was tested with the well-known other models (Arrhenius, Kendall–Monroe, Andrade and Vogel) for its predictive ability.

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  • Gülüm, Mert & Bilgin, Atilla, 2018. "A comprehensive study on measurement and prediction of viscosity of biodiesel-diesel-alcohol ternary blends," Energy, Elsevier, vol. 148(C), pages 341-361.
    • Handle: RePEc:eee:energy:v:148:y:2018:i:c:p:341-361
    DOI: 10.1016/j.energy.2018.01.123
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    3. Ağbulut, Ümit & Gürel, Ali Etem & Sarıdemir, Suat, 2021. "Experimental investigation and prediction of performance and emission responses of a CI engine fuelled with different metal-oxide based nanoparticles–diesel blends using different machine learning alg," Energy, Elsevier, vol. 215(PA).
    4. Felipe Andrade Torres & Omid Doustdar & Jose Martin Herreros & Runzhao Li & Robert Poku & Athanasios Tsolakis & Jorge Martins & Silvio A. B. Vieira de Melo, 2021. "A Comparative Study of Biofuels and Fischer–Tropsch Diesel Blends on the Engine Combustion Performance for Reducing Exhaust Gaseous and Particulate Emissions," Energies, MDPI, vol. 14(6), pages 1-19, March.
    5. Kumar, A. Naresh & Kishore, P.S. & Raju, K. Brahma & Ashok, B. & Vignesh, R. & Jeevanantham, A.K. & Nanthagopal, K. & Tamilvanan, A., 2020. "Decanol proportional effect prediction model as additive in palm biodiesel using ANN and RSM technique for diesel engine," Energy, Elsevier, vol. 213(C).

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