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    Study of FAME model systems: Database and evaluation of predicting models for biodiesel physical properties

    Year: 2020

    Journal: Renew. Energy, Volume 151, MAY, page 837–845

    Authors: Florido, Priscila M.; Visioli, Paola C. F.; Pinto, Camila N.; Goncalves, Cintia B.

    Organizations: FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2014/09757-0, 2014/21252-0, 2015/23372-6, 2018/21558-3]; CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) [308615/2016-6]; CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) [001]

    Keywords: Viscosities; Densities; Surface tension; Biodiesel; Prediction

    The present paper reports a viscosity and density unpublished database of systems formed for fatty acid methyl esters (FAMEs), leading to 426 experimental data points of each property. Kay's mixing rule and Grunberg-Nissan equation were used to estimate data and the group contribution models GC-VOL and GC-UNIMOD were used to predict density and viscosity, respectively. For surface tension, parameters of a Wilson modified equation were adjusted and tested in systems with composition similar to biodiesel. Density estimations resulted in global average relative deviations (ARD) of 0.02%, 0.07% and 0.15% for Kay's mixing rule weighted in mass and molar fractions, and GC-VOL model, respectively. For viscosities, GC-UNIMOD was the most accurate model with global ARD of 5.17%. The surface tension prediction resulted in global ARD minor than 7.00%. These results are an important tool to improve the biodiesel production, its modeling and simulation. (C) 2019 Elsevier Ltd. All rights reserved.
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