A study on the effects of compositional variations of biodiesel fuel on its physiochemical properties. Issue 5 (28th May 2021)

• Record Type: Journal Article
• Authors: Bukkarapu, Kiran Raj; Krishnasamy, Anand
• Is Part Of: Biofuels. Volume 12:Issue 5(2021)
• Page Start: 523
• Page End: 535
• Publication Date: 2021-05-28
• Subjects: Biodiesel -- composition -- kinematic viscosity -- heating value -- density -- surface tension; Biomass energy -- Periodicals; 662.8805
• DOI: 10.1080/17597269.2018.1501638
• Languages: English
• ISSNs: 1759-7269

Abstract

Abstract: The objective of the present work is to alter the composition of palm biodiesel and study its effects on fuel properties. As the fatty acid methyl ester composition of biodiesel has an influence on its properties, it can be varied to alter the properties as desired. Palm biodiesel was blended with various neat methyl esters on a 10%, 15% and 20% volume basis. Kinematic viscosity, heating value, density and surface tension of the 34 prepared biodiesel samples were determined and the trends followed were studied to establish the effects. The viscosity of biodiesel decreased with a decrease in methyl oleate concentration and the degree of unsaturation. An 80% palm +20% methyl octanoate blend exhibited the least viscosity. The heating value of the sample was found to be influenced by the changes in the methyl esters' chain length, the average number of single bonds and the average number of double bonds. Apparently, 80% palm +20% methyl stearate has the highest heating value. Not great appreciable change in density was found, but the surface tension of the blends prepared was influenced by changes in the average number of carbon atoms. An 80% palm +20% methyl octanoate mix exhibited the least surface tension of the fuel blends. Based on the measured composition and property data, a multi-linear regression approach was used to develop correlations to predict the properties of biodiesel from its composition, which is validated using samples other than those used as inputs to develop the model. Further, ANN is used to predict the properties of biodiesel fuels based on their composition. The present investigation could further be extended to study the effects of compositional variations of biodiesel on other properties, which would help in arriving at an ideal biodiesel composition for automotive engine applications.