Browsing by Author "Zlatanov K."

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    Comparison of empirical models to predict viscosity of secondary vacuum gas oils
    (2021-08-01) Stratiev D.S.; Nenov S.; Shishkova I.K.; Dinkov R.K.; Zlatanov K.; Yordanov D.; Sotirov S.; Sotirova E.; Atanassova V.; Atanassov K.; Stratiev D.D.; Todorova‐yankova L.
    This work presents characterization data and viscosity of 34 secondary vacuum gas oils (H‐Oil gas oils, visbreaker gas oils, and fluid catalytic cracking slurry oils) with aromatic content reaching up to 100 wt.%. Inter‐criteria analysis was employed to define the secondary VGO charac-teristic parameters which have an effect on viscosity. Seven published empirical models to predict viscosity of the secondary vacuum gas oils were examined for their prediction ability. The empirical model of Aboul‐Seud and Moharam was found to have the lowest error of prediction. A modifica-tion of Aboul‐Seoud and Moharam model by separating the power terms accounting for the effects of specific gravity and average boiling point improves the accuracy of viscosity prediction. It was discovered that the relation of slope of viscosity decrease with temperature enhancement for the secondary vacuum gas oil is not a constant. This slope increases with the average boiling point and the specific gravity augmentation, a fact that has not been discussed before.
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    Empirical models to characterize the structural and physiochemical properties of vacuum gas oils with different saturate contents
    (2021-07-01) Stratiev D.S.; Shishkova I.K.; Dinkov R.K.; Petrov I.P.; Kolev I.V.; Yordanov D.; Sotirov S.; Sotirova E.; Atanassova V.; Ribagin S.; Atanassov K.; Stratiev D.D.; Nenov S.; Todorova‐yankova L.; Zlatanov K.
    Inter‐criteria analysis was employed in VGO samples having a saturate content between 0.8 and 93.1 wt.% to define the statistically significant relations between physicochemical properties, empirical structural models and vacuum gas oil compositional information. The use of a logistic function and employment of a non‐linear least squares method along with the aromatic ring index allowed for our newly developed correlation to accurately predict the saturate content of VGOs. The empirical models developed in this study can be used not only for obtaining the valuable structural information necessary to predict the behavior of VGOs in the conversion processes but can also be utilized to detect incorrectly performed SARA analyses. This work confirms the possibility of predicting the contents of VGO compounds from physicochemical properties and empirical models.