To develop reliable models for the densities and viscosities of biodiesel fuel, reliable data for the pure fatty acid esters are required. Densities and viscosities were measured for seven ethyl esters and eight methyl esters, at atmospheric pressure and temperatures from (273.15 to 363.15) K. A critical assessment of the measured data against the data previously available in the literature was carried out. It is shown that the data here reported presents deviations of less than 0.15 % for densities and less than 5 % for viscosities. Correlations for the densities and viscosities with temperature are proposed. The densities and viscosities of the pure ethyl and methyl esters here reported were used to evaluate three predictive models. The GCVOL group contribution method is shown to be able to predict densities for these compounds within 1 %. The methods of Ceriani and Meirelles (CM) and of Marreiro and Gani (MG) were applied to the viscosity data. It is shown that only the first of these methods is able to provide a fair description of the viscosities of fatty acid esters.
Density is an important biodiesel parameter, with impact on fuel quality. Predicting density is of high relevance for a correct formulation of an adequate blend of raw materials that optimize the cost of biodiesel fuel production while allowing the produced fuel to meet the required quality standards. The aim of this work is to present new density data for different biodiesels and use the reported data to evaluate the predictive capability of models previously proposed to predict biodiesel or fatty acid methyl ester densities. Densities were measured here for 10 biodiesel samples, for which detailed composition is reported, at atmospheric pressure and temperatures from 278.15 to 373.15 K. Density dependence with temperature correlations was proposed for the biodiesels, and isobaric expansivities are presented. The new experimental data presented here were used along with other literature data to evaluate predictive density models, such as those based on Kay’s mixing rules and the GCVOL group contribution method. It is shown that Kay’s mixing rules and a revised form of the GCVOL model are able to predict biodiesel densities with average deviations of only 0.3%. A comparison between biodiesel densities produced from similar vegetable oils, by different authors, highlights the importance of knowing the detailed composition of the samples. An extension of GCVOL for high pressures is also proposed here. It is shown that it can predict the densities of biodiesel fuels with average deviations less than 0.4%.
Biodiesels have several known components in their composition. The majority of components is well described in the literature, but a minority of components are poorly characterized. These are however required to develop reliable models to predict the biodiesel behavior. This work considers minor components of biodiesel: the polyunsaturated compounds (in C18), the monounsaturated (in C16, C20, and C22), and the long-chain saturated esters. In this work, densities and viscosities of pure fatty acid ester minor components of biodiesel fuel were measured (three ethyl esters and seven methyl esters), at atmospheric pressure and temperatures from (273.15 to 373.15) K. Correlations for the densities and viscosities with temperature are proposed. Three predictive models were evaluated in the prediction of densities and viscosities of the pure ethyl and methyl esters here reported. The GCVOL group contribution method is shown to be able to predict densities for these compounds within 1.5 %. The methods of Ceriani et al. (CM) and of Marrero et al. (MG) were applied to the viscosity data. The first show a better predictive capacity to provide a fair description of the viscosities of the minority esters here studied.
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.
Biofuels are an important alternative to environmental sustainability, and biodiesel has a detached contribution to this scenario. The increasing use of biodiesel requires the knowledge of several thermophysical properties of this biofuel. This work addresses the measurements of the speed of sound and density at atmospheric pressure of five fatty acid methyl esters (methyl caprylate, methyl caprate, methyl palmitate, methyl stearate, and methyl linoleate). These data are used to test Wada's group contribution method recently proposed by us and its ability to predict the speed of sound of biodiesel fuels and to expand the application of this model to the prediction of the speed of sound of biodiesel fuels. The overall average relative deviations (OARD) obtained were 0.12% for the methyl esters and 0.29% for biodiesels. An extension of this model to high pressures is also proposed and tested with success, presenting an OARD of 1.0% for six biodiesel fuels.
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