Automated System for Identification of Conditions for Homogeneous and Heterogeneous Reactions in Multiobjective Optimization Problems

Коледина, К. Ф.; Koledin, S. N.; Gubaydullin, I. M.

doi:10.1134/s1995423919020022

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…The optimal temperature for the process is 25-30 °С. The adequacy of the calculated values is supported by the experimental data [47].…”

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...supporting

confidence: 58%

“…Prolongation of the reaction duration allows one to decrease the initial amount of catalyst from 1 mmol to 0.2 mmol. The optimal temperature for the process is 25-30 • C. The adequacy of the calculated values is supported by the experimental data [47].…”

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...supporting

confidence: 57%

“…Figures 2 and 3 demonstrate the results of the solution to the problem of multiobjective optimization of the olefin (octen-1) HA reaction conditions with DIBAC. and heterogeneous reaction conditions in the problems of the multiobject optimization elaborated earlier [47]. The algorithm's exit condition was the minimum change of the value of the optimality criterion (less than 10 −6 ) in accordance with experimental values.…”

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...mentioning

confidence: 82%

“…1.4.) in MATLAB with the help of parallelizing [45,46] in the automated system of identification of homogeneous and heterogeneous reaction conditions in the problems of the multiobject optimization elaborated earlier [47]. The algorithm's exit condition was the minimum change of the value of the optimality criterion (less than 10 −6 ) in accordance with experimental values.…”

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...mentioning

confidence: 99%

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Multiobjective Optimization of a Metal Complex Catalytic Reaction Based on a Detailed Kinetic Model with Parallelization of Calculations

2023

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The solution of the multiobjective optimization problem was performed with the help of the Pareto approximation algorithm. The problem of multiobjective optimization of the reaction process conditions for the olefin hydroalumination catalytic reaction, with the presence of organoaluminum compounds diisobutylaluminiumchloride, diisobutylaluminiumhydrate, and triisobutylaluminum, was solved. The optimality criteria are the yield of the reaction resultants. The largest yield of the high-order organoaluminum compound Bu2AlR was observed for the reactions with diisobutylaluminiumhydrate and triisobutylaluminum. Such results were obtained due to the fact that in the case of diisobutylaluminiumchloride, Bu2AlR was used for the formation of ClBuAlR. The yield of the Schwartz reagent Cp2ZrHCl was higher by a third in the reaction in the presence of diisobutylaluminiumchloride. Unlike the experimental isothermal conditions, the temperature optimal control showed the sufficiency of the gradual growth temperature for achieving the same or higher values of optimality criteria. For computational experiments, the algorithm for solving the multi-criteria optimization problem was parallelized using an island model.

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“…The optimal temperature for the process is 25-30 °С. The adequacy of the calculated values is supported by the experimental data [47].…”

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...supporting

confidence: 58%

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...supporting

confidence: 57%

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...mentioning

confidence: 82%

Section: Multiobjective Optimization Of the Metal Complex Catalytic R...mentioning

confidence: 99%

See 2 more Smart Citations

Multiobjective Optimization of a Metal Complex Catalytic Reaction Based on a Detailed Kinetic Model with Parallelization of Calculations

2023

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“…Table 1 shows the scheme of chemical transformations of the catalytic reaction of DMC with alcohols in the presence of W(CO)6, obtained in [1][2][3].…”

mentioning

confidence: 99%

Genetic Algorithm for Solving the Inverse Problem of Chemical Kinetics

Shaimardanova¹,

Коледина²

2022

CMIT

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Modeling allows to get a description of the object being modeled, in particular complications, which improves and clarifies its understanding and presents an organization of information that makes it easier to get the necessary information. Modeling of chemical kinetics problems is the solution of systems of ordinary nonlinear differential equations with determination of kinetic parameters. The inverse problem refers to incorrectly set tasks and does not have a single solution. The development of modern methods of evolutionary optimization, including the genetic algorithm, makes it possible to obtain a solution to such a high-dimensional problem in an acceptable time. Materials and methods. The object of research is the catalytic reaction of dimethyl carbonate (DMC) with alcohols in the presence of hexacarbonyl tungsten. The solution of the direct problem is the solution of a system of ordinary nonlinear differential equations with initial data and given kinetic parameters. The solution of the inverse problem consists in determining the kinetic parameters corresponding to the minimum deviation of the calculated values of substance concentrations from the experimental data. Results. The inverse problem of chemical kinetics is solved, which consists in calculating kinetic parameters with minimizing the functional deviation of the calculated values of component concentrations from experimental data. In the language of Python, program has been developed that implements the genetic algorithm. Numerical experiments with different numbers of iterations are performed and their impact on the accuracy of the solution, as well as the corresponding time costs, is estimated. Discussion and conclusions. The calculated values of the component concentrations based on the kinetic parameters found correspond to the values of the experimental data. Numerical experiments with different numbers of iterations are performed. Based on experiments, it was concluded that with an increase in the number of iterations, the accuracy of the solution increases. An increase in the number of iterations, in turn, leads to an increase in the time required for performing calculations. The time dependence on the number of iterations is analyzed.

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Pareto Frontier in Multicriteria Optimization of Chemical Processes Based on a Kinetic Model

Коледина

Koledin

Gubaydullin

2021

Communications in Computer and Information Science

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Automated System for Identification of Conditions for Homogeneous and Heterogeneous Reactions in Multiobjective Optimization Problems

Cited by 9 publications

References 14 publications

Multiobjective Optimization of a Metal Complex Catalytic Reaction Based on a Detailed Kinetic Model with Parallelization of Calculations

Multiobjective Optimization of a Metal Complex Catalytic Reaction Based on a Detailed Kinetic Model with Parallelization of Calculations

Genetic Algorithm for Solving the Inverse Problem of Chemical Kinetics

Pareto Frontier in Multicriteria Optimization of Chemical Processes Based on a Kinetic Model

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