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Efficacy of specific gravity as a tool for prediction of biodiesel-petroleum diesel blend ratio

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Prediction of volumetric biodiesel/petrodiesel blend ratio (VBD) from specific gravity (SG) data was the subject of the current investigation. Fatty acid methyl esters obtained from soybean, palm and rapeseed oils along with chicken fat (SME-1, SME-2, PME, RME and CFME) were blended (0–20 vol%) with three ultra-low sulfur (<15 ppm S) diesel (ULSD) fuels and SG at 15.6 °C was measured. Least-squares statistical regression on SG data from each of the biodiesel/ULSD blend sets revealed highly linear relationships (R2 > 0.991) between SG and VBD. Blends with the highest R2 values from each of the ULSD fuels were used as model systems to develop predictive equations useful for calculation of VBD from SG. The results indicated that accurate prediction of VBD from SG was most effective when applied to blends prepared from the same fuel-types as the model systems used to develop the predictive equations.
Moser, Bryan R.
animal fats and oils , biodiesel , diesel fuel , equations , fatty acid esters , mixing , palm oils , prediction , rapeseed oil , regression analysis , soybean oil , specific gravity , sulfur
Includes references
Fuel 2012 Sept., v. 99
Journal Articles, USDA Authors, Peer-Reviewed
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