Abstract
AbstractThe cold filtration plugging point (CFPP) is the method most commonly applied to characterize the low‐temperature behavior of diesel and its components. However, this method is time‐consuming and does not have good repeatability, especially for samples with very low CFPP values like kerosene, light cycle oil, etc. Three new models for CFPP prediction were developed and compared: a combined density and distillation curve, differential scanning calorimetry, and near‐infrared. A set of 133 samples of diesel components were used to create the models, containing streams from different sources and levels of treatment. A further 28 diesel samples were used to validate and compare the models. All three models not only were faster than the standard method but also were found to be in good agreement with CFPP values. Each model has its own particular advantages suiting it to a particular type of diesel sample and stage of the diesel production process.
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