Mathematical modeling of multicomponent catalytic processes of petroleum refining and petrochemistry

Abstract This review summarizes Russian developments on the most important industrial processes of hydrocarbon feedstock refining according to the data of the last 15–20 years on the kinetics of deactivation of heterogeneous and liquid-phase catalysts under non-stationary conditions. The methodological aspects of the creation and application of kinetic models for the deactivation of heterogeneous and liquid-phase catalysts under non-stationary conditions are considered. It is shown that high efficiency of catalytic technologies is ensured by regulation of hydrodynamic and thermal conditions of industrial processes of gasoline reforming, alkane dehydrogenation, alkylation of benzene with higher alkenes and catalytic dewaxing using kinetic models, which take into account catalyst deactivation.

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Hydrothermal conversions of waste biomass: Assessment of kinetic models using liquid-phase electrical conductivity measurements

Waste Management ◽

10.1016/j.wasman.2018.05.033 ◽

2018 ◽

Vol 77 ◽

pp. 586-592 ◽

Cited By ~ 7

Author(s):

Alberto Gallifuoco ◽

Luca Taglieri ◽

Francesca Scimia ◽

Alessandro Antonio Papa ◽

Gabriele Di Giacomo

Keyword(s):

Electrical Conductivity ◽

Liquid Phase ◽

Kinetic Models ◽

Waste Biomass ◽

Conductivity Measurements ◽

Biomass Assessment

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Analysis and classification of tem¬perature measurements during melting and casting of alloys using neural networks

Izvestiya Ferrous Metallurgy ◽

10.17073/0368-0797-2020-10-856-861 ◽

2020 ◽

Vol 63 (10) ◽

pp. 856-861

Author(s):

A. V. Fedosov ◽

G. V. Chumachenko

Keyword(s):

Neural Network ◽

Neural Networks ◽

Human Factor ◽

High Efficiency ◽

Thermal Conditions ◽

Second Stage ◽

Three Stages ◽

Fully Automatic ◽

Artificial Neural

The article considers the issues of monitoring the thermal conditions of alloys melting and casting at foundries. It is noted that the least reliable method is when the measurement and fixing the temperature is assigned to the worker. On the other hand, a fully automatic approach is not always available for small foundries. In this regard, the expediency of using an automated approach is shown, in which the measurement is assigned to the worker, and the values are recorded automatically. This method assumes implementation of an algorithm for automatic classification of temperature measurements based on an end-to-end array of data obtained in the production stream. The solving of this task is divided into three stages. Preparing of raw data for classification process is provided on the first stage. On the second stage, the task of measurement classification is solved by using neural network principles. Analysis of the results of the artificial neural network has shown its high efficiency and degree of their correspondence with the actual situation on the work site. It was also noted that the application of artificial neural networks principles makes the classification process flexible, due to the ability to easily supplement the process with new parameters and neurons. The final stage is analysis of the obtained results. Correctly performed data classification provides an opportunity not only to assess compliance with technological discipline at the site, but also to improve the process of identifying the causes of casting defects. Application of the proposed approach allows us to reduce the influence of human factor in the analysis of thermal conditions of alloys melting and casting with minimal costs for melting monitoring.

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Mechanistic Investigations of Liquid-phase Direct Alkylation of Benzene with n-Heptane Using Proton-exchanged Montmorillonite Catalysts

Journal of the Japan Petroleum Institute ◽

10.1627/jpi.63.289 ◽

2020 ◽

Vol 63 (5) ◽

pp. 289-296

Author(s):

Moe TAKABATAKE ◽

Masayuki NAMBO ◽

Yuichi MANAKA ◽

Ken MOTOKURA

Keyword(s):

Liquid Phase ◽

Alkylation Of Benzene ◽

Mechanistic Investigations

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Development of Kinetic Models for the Liquid Phase Methanol (LPMEOH tm) Process

10.2172/922636 ◽

2002 ◽

Author(s):

Xiang-Dong Peng

Keyword(s):

Liquid Phase ◽

Kinetic Models

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Liquid phase crystalline Silicon on Glass: A pathway to high efficiency thin film solarcells

10.7567/ssdm.2019.c-6-01 ◽

2019 ◽

Author(s):

C.T. Trinh ◽

S. Garud ◽

M. Trahms ◽

D. Amkreutz

Keyword(s):

Thin Film ◽

Liquid Phase ◽

High Efficiency ◽

Crystalline Silicon

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Catalysis in Alkylation of Benzene With Ethene and Propene to Produce Ethylbenzene and Isopropylbenzene

Advanced Catalysis Processes in Petrochemicals and Petroleum Refining - Advances in Chemical and Materials Engineering ◽

10.4018/978-1-5225-8033-1.ch001 ◽

2020 ◽

pp. 1-47

Author(s):

Mohammed C. Al-Kinany ◽

Saeed M. Alshihri ◽

Saud A. Aldrees ◽

Eyad A. Alghilan ◽

Sami D. Aldrees ◽

...

Keyword(s):

Liquid Phase ◽

Gas Phase ◽

Bronsted Acids ◽

Solid Catalysts ◽

Alkylation Of Benzene ◽

History Of

The alkylation of benzene with ethylene or propylene to form ethylbenzene (EB) or cumene is an industrially significant transformation. EB is used as an intermediate in the manufacture of styrene, which in turn is an important in the manufacture of many kinds of polymers. The primary use of cumene is in the co-production of phenol and acetone, which in turn are important in the manufacture of many kinds of chemicals and polymers. In industry, EB and cumene are mainly manufactured by the alkylation of benzene with ethene or propene via two methods, the gas and the liquid phase in the presence of Lewis and Brønsted acids. The development of efficient solid catalysts has gained much attention over the last decades. The objective of this chapter is to provide an overview of the history of the alkylation of benzene with ethene and propene, the development of homogeneous and heterogeneous Lewis and Brønsted acids and zeiolite catalysts, the liquid and gas phase alkylation processes, and the industrial technologies for EB and cumene production.

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