Abstract

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.

Graphic Abstract

中文翻译：

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运动粘度预测指南：根据温度和原料审查和评估柴油馏分和生物柴油-柴油混合物的经验模型

摘要

对于少数样品，粘度的实验分析可以是一种直接且廉价的分析。然而，在对特性测量有很高要求的工业过程中，粘度和其他特性的确定涉及采样、分析和结果可用性的耗时。同样在炼油厂，用于实验确定物流粘度的采样程序不足以代表过程中发生的变化，例如蒸馏装置中油罐的移动。此外，除了需要操作人员和实验室分析员的成本外，所有这些步骤可能需要一个班次才能获得结果。因此，作为替代方案，使用运动粘度的预测方法是必不可少的。经验方法已用于工业中关于石油馏分和燃料在不同温度下的运动粘度 (KV) 的流和混合物的模拟和设计计算。然而，在特定条件（温度、原料、体积分数）下使用的最准确方法存在不确定性，这可能会影响未知成分燃料的 KV 预测。因此，我们汇总并评估了几种方法来预测不同柴油系统的 KV。此外，还开发了用于预测多个温度下柴油馏分 KV 的新方法，以提高估计精度。因此，我们制定了一份指南，其中包含最准确模型的建议，这些模型适用于分析中的柴油馏分、混合系统中的柴油馏分 S500 在多个温度下

图形摘要