International Research Journal of Pure and Applied Physics (IRJPAP)

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Arrhenius-Type Relationship of Viscosity as a Function of Temperature for Mustard and Cotton Seed Oils


The knowledge and evaluation of transport behaviors of fluids are very important in heat and mass flow. In this study, we adopted a statistical technique for regression analysis and statistical correlation tests. An equation modeling the relationship between the two parameters of viscosity Arrhenius-type equation, such as the Arrhenius energy (Ea) or the pre-exponential factor (A) was used. In addition, we introduce two other parameters; the Arrhenius temperature (T) and Arrhenius activation temperature (T*) to enrich the discussion. The viscosity data from two vegetable oils at different temperature ranges gives excellent statistical results. In addition, the model in this case is very useful for engineering data and permits the estimation of one non-available parameter when the other is available. The Activation energy Ea, Entropic (pre-exponential) factor A, Arrhenius temperature TA and the Arrhenius activation temperature for the mustard oil were observed to be 374.37381 J/mole, 12.39260595 cP, -17.89797783 oC, 45.051 oC respectively while Activation energy Ea, Entropic (pre-exponential) factor A, Arrhenius temperature TA and the Arrhenius activation temperature for the cotton seed oil are respectively 451.90611 J/mole, 8.210386507 cP, -25.8292961 oC, 54.381 oC . The coefficients of regressions (R2) for the graph of the natural log of viscosity versus reciprocal of temperature (Figures 2 and 4) for the mustard oil and cotton seed oil are 0.9996 and 0.9996 respectively. Since the correlation coefficient is the measure of how well a collection of data points can be modeled by a line, we can hence conclude that the natural log of the viscosity of both seed oil samples versus the inverse of their respective temperatures have a very good fit.

Keywords: Correlation, Model, Temperature, arrhenius parameters, statistics, vegetable oil, viscosity

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