Mathematical modelling of catalytic cracking riser reactor

Иванчина, Э. Д.; Ivashkina, Elena; Nazarova, Galina

doi:10.1016/j.cej.2017.04.098

Cited by 24 publications

(10 citation statements)

References 39 publications

(40 reference statements)

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“…This approach also included numerical studies and a group of physicochemical methods, such as liquid and gas chromatography, mass spectrometry, structural group analysis, etc. The results of gas chromatography, mass spectrometry, and structural group analysis can be found in [36,40].…”

Section: Methodsmentioning

confidence: 99%

A Model of Catalytic Cracking: Product Distribution and Catalyst Deactivation Depending on Saturates, Aromatics and Resins Content in Feed

et al. 2021

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The problems of catalyst deactivation and optimization of the mixed feedstock become more relevant when the residues are involved as a catalytic cracking feedstock. Through numerical and experimental studies of catalytic cracking, we optimized the composition of the mixed feedstock in order to minimize the catalyst deactivation by coke. A pure vacuum gasoil increases the yields of the wet gas and the gasoline (56.1 and 24.9 wt%). An increase in the ratio of residues up to 50% reduces the gasoline yield due to the catalyst deactivation by 19.9%. However, this provides a rise in the RON of gasoline and the light gasoil yield by 1.9 units and 1.7 wt% Moreover, the ratio of residue may be less than 50%, since the conversion is limited by the regenerator coke burning ability.

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Section: Methodsmentioning

confidence: 99%

A Model of Catalytic Cracking: Product Distribution and Catalyst Deactivation Depending on Saturates, Aromatics and Resins Content in Feed

et al. 2021

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“…The performance of these processes has been shown in many studies to strongly depend on the quality of the feedstock [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. The vacuum gas oil fraction from petroleum is the typical feed for the FCC [2,3,[5][6][7][8][9][10][11][12][13][14][15][16][17] and it has been explored as a feedstock for steam cracking as well [4]. 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].…”

Section: Introductionmentioning

confidence: 99%

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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“…Modeling of catalytic naphtha reforming process is a very complex task because of a number of the features such as catalyst bimetallic nature, feedstock composition complexity, a large number of reactions with different rates and deactivation processes occurring during the catalyst operation. Therefore, a model should consider both the catalyst bimetallic nature and the complexity of the feedstock composition as in a real technological process [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling and optimization of semi-regenerative catalytic reforming of naphtha

Иванчина¹,

Chernyakova²,

Pchelintseva³

et al. 2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Catalytic naphtha reforming is extensively applied in petroleum refineries and petrochemical industries to convert low-octane naphtha into high-octane gasoline. Besides, this process is an important source of hydrogen and aromatics obtained as side products. The bifunctional Pt-catalysts for reforming are deactivated by coke formation during an industrial operation. This results to a reduction in the yield and octane number. In this paper modeling and optimization of a semi-egenerative catalytic reforming of naphtha is carried out considering catalyst deactivation and a complex multicomponent composition of a hydrocarbon mixture. The mathematical model of semi-egenerative catalytic reforming considering coke formation process was proposed. The operating parameters (yield, octane number, activity) for different catalysts were predicted and optimized. It was found that a decrease in the pressure range from 1.5 to 1.2 MPa at the temperature 478–481 °C and feedstock space velocity equal to 1.4–1 h induces an increase in the yield for 1–2 wt.% due to an increase in the aromatization reactions rate and a decrease in the hydrocracking reactions rate depending on the feedstock composition and catalyst type. It is shown that the decrease in pressure is limited by the requirements for the catalyst stability due to the increase in the coke formation rate. The criterion of optimality is the yield, expressed in octanes per tons.

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Mathematical modelling of catalytic cracking riser reactor

Cited by 24 publications

References 39 publications

A Model of Catalytic Cracking: Product Distribution and Catalyst Deactivation Depending on Saturates, Aromatics and Resins Content in Feed

A Model of Catalytic Cracking: Product Distribution and Catalyst Deactivation Depending on Saturates, Aromatics and Resins Content in Feed

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

Mathematical modeling and optimization of semi-regenerative catalytic reforming of naphtha

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