Evaluation of Predictive Models for the Viscosity of Biodiesel
authors Freitas, SVD; Pratas, MJ; Ceriani, R; Lima, AS; Coutinho, JAP
nationality International
journal ENERGY & FUELS
keywords TEMPERATURE-DEPENDENT VISCOSITY; KINEMATIC VISCOSITY; SOYBEAN BIODIESEL; BINARY-MIXTURES; DIESEL FUEL; DENSITIES; BLENDS; ACID; OIL; ESTERS
abstract Viscosity is an important biodiesel parameter, subject to specifications and with an impact on the fuel quality. A model that could predict the value of viscosity of a biodiesel based on the knowledge of its composition would be useful in the optimization of biodiesel production processes and the planning of blending of raw materials and refined products. This work aims at evaluating the predictive capability of several models previously proposed in the literature for the description of the viscosities of biodiesels and their blend with other fuels. The models evaluated here are Ceriani's, Krisnangkura's, and Yuan's models, along with a revised version of Yuan's model proposed here. The results for several biodiesel systems show that revised Yuan's model proposed provides the best description of the experimental data with an average deviation of 4.65%, as compared to 5.34% for Yuan's model, 8.07% for Ceriani's model, and 7.25% for Krisnangkura's model. The same conclusions were obtained when applying these models to predict the viscosity of blends of biodiesel with petrodiesel.
publisher AMER CHEMICAL SOC
issn 0887-0624
year published 2011
volume 25
beginning page 352
ending page 358
digital object identifier (doi) 10.1021/ef101299d
web of science category Energy & Fuels; Engineering, Chemical
subject category Energy & Fuels; Engineering
unique article identifier WOS:000287345900044
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  impact metrics
journal analysis (jcr 2017):
journal impact factor 3.024
5 year journal impact factor 3.622
category normalized journal impact factor percentile 66.683
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