Optimization of the pyrolysis of ethane using fuzzy programming

Riverol, C.; Pilipovik, M.V.

doi:10.1016/j.cej.2007.02.009

Cited by 14 publications

(3 citation statements)

References 20 publications

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“…Experimental measurement [19] and numerical simulation data [20] concentrated mainly on the route of formation of intermediates [21][22][23][24][25][26], and the distribution of final products [27]. Interaction of hydrocarbons with catalysts has also been studied [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Autocatalytic gas-phase dehydrogenation of ethane

et al. 2011

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Homogeneous gas-phase pyrolysis of ethane by continuous CO 2 laser irradiation was used in our experiments for bulk heating of the reaction mixture. Laser energy was absorbed by ethylene, the main product of ethane dehydrogenation, and transferred to the reaction medium via collisional relaxation. A mechanism of ethane dehydrogenation is suggested to describe the pyrolysis process. The mechanism is autocatalytic in respect of ethylene and includes ethane-ethylene interaction with the formation of methyl and propyl radicals. Rate constants of elementary reactions, selectivity, and yields of pyrolysis products were determined. The composition of ethane dehydrogenation products determined in the experiments was substantially different from the calculated thermodynamic equilibrium composition.

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Section: Introductionmentioning

confidence: 99%

Autocatalytic gas-phase dehydrogenation of ethane

et al. 2011

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“…The decision variables were selected based on a sensitivity analysis. Riverol and Pilipovik applied a fuzzy/possibilistic optimization approach to an ethane cracker. The idea was based on the fact that the optimal values of the design parameters are target values not fixed real numbers.…”

Section: Optimal Designmentioning

confidence: 99%

Thermal Cracking of Hydrocarbons for the Production of Light Olefins; A Review on Optimal Process Design, Operation, and Control

Fakhroleslam

Sadrameli

2020

Ind. Eng. Chem. Res.

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Olefins production plants are large-scale plants, in most of which gaseous and liquid hydrocarbons are cracked to produce light olefins. The complex and large-scale nature of these plants makes it an utmost necessity to design and operate them with the use of computer-aided optimization and control methods. This review paper provides an overview of the reported research works on the optimization and control of different parts of olefin plants. The main research studies are discussed in two main sections: Optimal Design and Process Operation and Control. In the Optimal Design section, the state of the optimal design of cracking furnace systems, cold-end separation systems, and separation columns have been studied. Then in the Process Operation and Control section, the control of cracking furnaces, the control of cold-end separation systems, real-time optimization of olefin plants, cyclic scheduling of cracking furnace systems, production planning of olefin plants, and finally, start-up and shutdown operations in these plants have been extensively reviewed. This paper is a continuation of the three review articles published previously entitled Thermal and Catalytic Cracking of Hydrocarbons for the Production of Light Olefins, the last of which focused on process modeling and simulation.

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“…As for the operation optimization of a furnace system, much work is being done for steady state optimization without considering the change of coke deposition. Riverol and Pilipovik carried out the operation optimization on the ethane pyrolysis process using fuzzy programming, in which they claimed that a good result could be obtained using fuzzy programming and the furnace was economically attractive. Nian et al proposed a differential evolution group search optimization (DEGSO) algorithm to optimize the operation conditions of a naphtha cracking furnace by maximizing the sum mass yield of ethylene and propylene under three different kinds of naphtha feedstock.…”

Section: Introductionmentioning

confidence: 99%

Integrated Operation and Cyclic Scheduling Optimization for an Ethylene Cracking Furnaces System

Jin

et al. 2015

Ind. Eng. Chem. Res.

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Multiple cracking furnaces in an ethylene plant run in parallel to produce ethylene, propylene, and other products from different hydrocarbon feedstocks. Because both coke formation in radiant coils and change of operation conditions with time have significant effects on the performance of cracking furnaces, it is better for the cyclic scheduling to be simultaneously optimized with the operation conditions. To match this real requirement, a mixed-integer dynamic optimization (MIDO) problem is presented for the optimization of both operation conditions and cyclic scheduling simultaneously, through which the optimal assignment, the processing time, the subcycle number, and the optimal operation conditions of different feeds in different cracking furnaces are determined at the same time. To solve the MIDO problem, it is discretized and converted into a large scale mixed-integer nonlinear programming (MINLP) problem. The two scheduling cases of a cracking furnaces system are illustrated showing a remarkable increase in the economic performance as compared with that of the traditional method.

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Optimization of the pyrolysis of ethane using fuzzy programming

Cited by 14 publications

References 20 publications

Autocatalytic gas-phase dehydrogenation of ethane

Autocatalytic gas-phase dehydrogenation of ethane

Thermal Cracking of Hydrocarbons for the Production of Light Olefins; A Review on Optimal Process Design, Operation, and Control

Integrated Operation and Cyclic Scheduling Optimization for an Ethylene Cracking Furnaces System

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