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  • 标题:Statistical analysis on prediction of biodiesel properties from its fatty acid composition
  • 本地全文:下载
  • 作者:Vishal Kumbhar ; Anand Pandey ; Chandrakant R. Sonawane
  • 期刊名称:Case Studies in Thermal Engineering
  • 印刷版ISSN:2214-157X
  • 电子版ISSN:2214-157X
  • 出版年度:2022
  • 卷号:30
  • 页码:101775
  • 语种:English
  • 出版社:Elsevier B.V.
  • 摘要:The present work deals with the statistical analysis to determine the relationship between the vital biodiesel properties (cetane number, density, viscosity, heating value) and fatty acid compositions of nine different types of biodiesels originated from edible oil non-edible oil, waste oil, and animal oil. Multiple linear regression analysis (MLR) was used to develop the mathematical models to predict the properties from the saturated (lauric, myristic, stearic) and unsaturated fatty (oleic, linoleic, linolenic) acids composition. The developed models were then validated with experimental data from the literature to determine their predictive capability. The models developed for cetane number and density were highly statistical and successfully predicted the respective properties of randomly selected biodiesel from the literature. On the other hand, predictive models for kinematic viscosity and heating value were ineffective; however, the error between experimental and predicted values was sufficiently minimal for heating value.
  • 关键词:Biodiesel Fatty acid composition Unsaturated fatty acids Multiple linear regression
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