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

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• 作者：Bryan R. Moser ; ^{Bryan.Moser@ars.usda.gov}
• 关键词：APE ; average percent error ; AV ; acid value ; CFME ; chicken fat methyl esters ; CP ; cloud point ; FA ; fatty acid ; FAME ; fatty acid methyl ester ; HDS ; hydrodesulfurization ; KV ; kinematic viscosity ; LSD ; low-sulfur (< ; 500  ; ppm) diesel fuel ; PME ; palm oil
• 刊名：Fuel
• 出版年：2012
• 期刊代码：33_00162361
• 类别：ce
• 出版时间：September, 2012
• 卷：99
• 期：Complete
• 页码：254-261
• 文件大小：351 K

摘要

Prediction of volumetric biodiesel/petrodiesel blend ratio (V_BD) 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 掳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 V_BD. 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 V_BD from SG. The results indicated that accurate prediction of V_BD 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.