Experimental analysis of viscosity can be a straightforward and inexpensive analysis for few samples. However, in industrial processes that have high demands of properties measurements, the determination of viscosity and other properties involves time-consuming with sampling, analysis, and availability of results. Also in refineries, the sampling routines for experimental determination of the viscosity of streams are not enough to represent variations that occur in the process, such as the shift of an oil tank in distillation units. In addition, besides requiring cost of operating personnel and laboratory analyst, all of these steps can take up to one shift until the result is available. Therefore, as an alternative, the use of predictive methods of kinematic viscosity are essential. Empirical methods have been used in simulations and design calculations of streams and mixture at industries regarding kinematic viscosity (KV) of petroleum fractions and fuels at different temperatures. However, there are uncertainties about the most accurate method to use at specific condition (temperature, feedstock, volume fraction) which might affect the KV prediction of fuels with unknown composition. Therefore, we assembled and evaluated several methods to predict KV of different diesel systems. In addition, new methods for predicting KV of diesel fractions at several temperatures were also developed for improving the estimation accuracy. As a result, we developed a guide with suggestions of the most accurate models to be applied for diesel fraction from assays, diesel fractions S500 from blend system at several temperatures, and biodiesel–diesel blends at different temperatures, volume fractions, and feedstock.
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