Prediction of the Hydrogen Content of Petroleum Fractions

Goossens, Adriaan G.

doi:10.1021/ie960772x

Cited by 16 publications

(16 citation statements)

References 4 publications

(4 reference statements)

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“…• Goosens highlighted the importance of accurate hydrogen content prediction of petroleum fractions, which is used as input in the kinetic models that simulate and optimize the performance of conversion processes like steam cracking and catalytic cracking [22]. He reported that while Dhulesia's method exhibited a 1% average deviation in hydrogen prediction of FCC feeds, Goosens' method achieved a standard deviation of only 0.3% in predicted wt.% hydrogen for the full practical range of oil fractions for olefin manufacture.…”

Section: Determination Of Refractive Index Aromatic Carbon and Hydrogen Content By The Total Methodsmentioning

confidence: 99%

“…He reported that while Dhulesia's method exhibited a 1% average deviation in hydrogen prediction of FCC feeds, Goosens' method achieved a standard deviation of only 0.3% in predicted wt.% hydrogen for the full practical range of oil fractions for olefin manufacture. [22]. Goosens' method requires data on the refractive index, density and distillation characteristics of VGOs to predict hydrogen content [22].…”

Section: Determination Of Refractive Index Aromatic Carbon and Hydrogen Content By The Total Methodsmentioning

confidence: 99%

“…[22]. Goosens' method requires data on the refractive index, density and distillation characteristics of VGOs to predict hydrogen content [22]. It is inferred from the concept of the molar additivity of the structural contributions of the carbon types in the average hydrocarbon molecule.…”

Section: Determination Of Refractive Index Aromatic Carbon and Hydrogen Content By The Total Methodsmentioning

confidence: 99%

“…Considering that in Resources 2021, 10, 71 2 of 20 both FCC and thermal cracking the reactivity of the vacuum gas oils increases with the saturate content enhancement and aromatic carbon content reduction, the information about these vacuum gas oil characteristics is of paramount importance for optimizing their performance [17]. Different empirical models for predicting important vacuum gas oil characteristics have been developed and published in the open literature [18][19][20][21][22][23][24][25][26][27][28]. To the best of our knowledge, these empirical models have not been evaluated to predict the content of saturates of vacuum gas oils in the whole range of possible variation (between 0 and 100%).…”

Section: Introductionmentioning

confidence: 99%

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Empirical Models to Characterize the Structural and Physiochemical Properties of Vacuum Gas Oils with Different Saturate Contents

et al. 2021

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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.

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Section: Determination Of Refractive Index Aromatic Carbon and Hydrogen Content By The Total Methodsmentioning

confidence: 99%

Section: Determination Of Refractive Index Aromatic Carbon and Hydrogen Content By The Total Methodsmentioning

confidence: 99%

Section: Determination Of Refractive Index Aromatic Carbon and Hydrogen Content By The Total Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Empirical Models to Characterize the Structural and Physiochemical Properties of Vacuum Gas Oils with Different Saturate Contents

et al. 2021

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“…The molecular weight and hydrogen 312 content were determined with the density, refractive index, and 50% distillation temperature in simulated distillation with the correlations reported in [3,4].…”

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confidence: 99%

Yield of products from catalytic cracking of vacuum gasoils

Stratiev

Галкин

Shishkova

et al. 2007

Chem Technol Fuels Oils

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In catalytic cracking of vacuum gasoils, the yields of products are correlated with their hydrogen content. A correlation that allows predicting the yields of products of this process was elaborated based on the results of cracking of 11 gasoils of different origin and data on their density, refractive index, and 50% distillation temperature. However, it is not possible to predict the octane number of the naphtha obtained in cracking with the group hydrocarbon composition of the feedstock.Feedstock consumption is one of the most important factors that determine an oil company's profitability.For this reason, feedstock of the optimum composition and quality must be selected for each oil refinery (OR). The cost of the feedstock for each given process is also determined by these parameters, particularly the content of light cuts.The quality of the feedstock cuts going to conversion units -catalytic cracking, hydrocracking, visbreaking, coking, etc., is due to the degree of their conversion into products of higher cost. The efficiency of catalytic cracking is inarguably one of the most important processes in oil refining and is basically a function of the chemical nature of the feedstock. According to the mass spectroscopic data in [1] obtained in conversion of nine vacuum gasoils, the yield of naphtha cut is maximum, and the yields of other products are correlated with the alkane, cycloalkane, and monocyclic arene content in the feedstock. It was later shown in [2] that the quality of catalytic feedstock can be evaluated by empirical methods based on the data from regularly performed analyses. We quantitatively evaluated the quality of vacuum gasoils from different crudes as catalytic feedstock.The physicochemical characteristics of these gasoils are reported in Table 1. The molecular weight and hydrogen 312 content were determined with the density, refractive index, and 50% distillation temperature in simulated distillation with the correlations reported in [3,4].The experiments were conducted on a MAT (Micro Activity Test) laboratory unit with the method in ASTM D 3907-92. The conversion was varied by varying the catalyst:feedstock mass ratio from 2 to 6. The methodology of the experiments is described in detail in [2]. The feedstock was cracked in an equilibrium industrial catalyzer with the following physicochemical properties: Chemical composition, wt. % Al 2 O 3 47.2 Na 2 O 0.17 Re 2 O 3 1.34 Metal content vanadium, ppm 1074 nickel, ppm 328 iron, wt. % 0.68 Microactivity: conversion, wt. % 71 Average particle size, mm 71 Bulk density, kg/m 3 920Pore volume, cm 3 /g 0.3 Total specific surface area, m 2 /g 66The necessity of comparing different feedstock at the maximum yield of naphtha cut was demonstrated in [1]. A comparison at constant conversion or constant yield of coke cannot be conclusive, since each feedstock has its own optimum degree of conversion.The feedstock was cracked at different catalyst:feedstock ratios and constant (30 sec) contact time of the catalyst with the feedstock. The possibility of us...

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