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    Measurement and correlation of thermophysical properties of waste lubricant oil

    Year: 2018

    Journal: J. Chem. Thermodyn., Volume 116, JAN, page 137–146

    Authors: Pinheiro, C. T.; Pais, R. F.; Ferreira, A. G. M.; Quina, M. J.; Gando-Ferreira, L. M.

    Organizations: SOGILUB - Sociedade de Gestao Integrada de Oleos Lubrificantes Usados, Lda

    Keywords: Waste lubrication oil; Viscosity; Density; Surface tension; Glass transition; Dynamic crossover

    Measurements of viscosity, density and surface tension of waste lubricant oil (WLO) were conducted at different temperatures. The dataset was constituted by nine WLO samples from different producers. The main objective of the work is the investigation of the temperature dependence of viscosity, including the glass transition, T-g, and dynamic crossover, T-x, temperatures. In addition, different correlations were evaluated to predict viscosity and surface tension starting from a property easily obtained such as density. WLO show rapid decrease of viscosity with shear rate, followed by an extensive and well defined Newtonian plateau. The temperature dependence of viscosity at the Newtonian plateau of WLO deviated from the Arrhenius behavior, and was accurately described by four different models: Williams-Landel-Ferry (WLF), MYEGA, power law and Ghatee. The minimum and maximum absolute average relative deviation (AARD) were 0.08% and 0.9%, respectively. T-g predicted by WLF equation varied between T = 170.5 K and T = 198.7 K, while MYEGA tends to predict lower T-g (about T = 20 K). The power law and Ghatee models estimate T-x nearly with the same accuracy. A ratio T-x/T-g of about 1.28 +/- 0.03 was obtained for WLO, which agrees with the literature. Waste oil is a moderately fragile glass forming fluid with a fragility parameter, m, ranging from 47.8 and 64.5. New correlations were developed for the prediction of viscosity and surface tension from density at different temperatures. AARD of 7% was observed for viscosity and 2% for surface tension. (C) 2017 Elsevier Ltd.
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