Preview

Scientific and Technical Journal of Information Technologies, Mechanics and Optics

Advanced search

Numerical algorithm for finding the optimal composition of the reacting mixture on the basis of the reaction kinetic model

https://doi.org/10.17586/2226-1494-2023-23-6-1128-1135

Abstract

The results of developing an algorithm for searching for optimal initial concentrations of substances in a chemical reaction are presented. The algorithm combines a combination of optimization methods with the theoretical foundations of modeling chemical reactions in terms of constructing their kinetic models. A mathematical description of the dynamics of the concentrations of reactants over time is presented in the form of a system of ordinary differential equations the initial conditions of which are specified by the values of the initial concentrations of the reactants. The problem of determining the optimal composition of the reacting mixture is formulated in general terms. The problem contains restrictions imposed on the values of the initial concentrations of substances and on their initial total concentration. To solve the problem, the penalty method and the Hooke–Jeeves method were used. A penalty function is described that allows one to reduce the original problem to a problem without restrictions. A step-by-step algorithm for searching for optimal initial concentrations of a chemical reaction is formulated. A computational experiment was carried out for the catalytic reaction of aminomethylation of thiols using tetramethylmethanediamine. A kinetic model of the reaction is presented on the basis of which an optimization problem is formulated to find the values of the initial concentrations of reagents to obtain the highest yield of the target product at the end of the reaction. The optimal initial concentrations of the starting substances were calculated for different reaction durations and at different temperatures. The developed numerical algorithm for determining the optimal initial concentrations of reagents takes into account the physicochemical features of the problem and can be used in the study of complex chemical reactions containing a large number of initial and intermediate substances. Its use makes it possible to determine the patterns of a chemical reaction at the stage of a computer experiment, without resorting to laboratory experiments, which significantly saves the material and time costs of the researcher.

About the Authors

E V. Antipina
Ufa University of Science and Technology
Russian Federation

Evgenia V. Antipina — PhD (Physics & Mathematics), Senior Researcher

Ufa, 450076

sc 57214879770



S. A. Mustafina
Ufa University of Science and Technology
Russian Federation

Svetlana A. Mustafina — D.Sc. (Physics & Mathematics), Vice Rector

Ufa, 450076

sc 6603592002



A. F. Antipin
Sterlitamak branch of Ufa University of Science and Technology
Russian Federation

Andrey F. Antipin — PhD, Associate Professor

Sterlitamak, 453103

sc 55904921400



References

1. Ziyatdinov N.N., Emel’yanov I.I., Lapteva T.V., Ryzhova A.A., Ignat’ev A.N. Method of automated synthesis of optimal heat exchange network (HEN) based on the principle of fixation of variables. Theoretical Foundations of Chemical Engineering, 2020, vol. 54, no. 2, pp. 258–276. https://doi.org/10.1134/S0040579520020189

2. Lindborg H., Eide V., Unger S., Henriksen S.T., Jakobsen H.A. Parallelization and performance optimization of a dynamic PDE fixed bed reactor model for practical applications. Computers & Chemical Engineering, 2004, vol. 28, no. 9, pp. 1585–1597. https://doi.org/10.1016/j.compchemeng.2003.12.009

3. Sahinidis N.V., Grossmann I.E. Reformulation of the multiperiod MILP model for capacity expansion of chemical processes. Operations Research, 1992, vol. 40, no. 1-supplement-1, pp. 127– 144. https://doi.org/10.1287/opre.40.1.S127

4. Royce N.J. Linear programming applied to production planning and operation of a chemical process. Operational Research Quarterly (1970–1977), 1970, vol. 21, no. 1, pp. 61–80. https://doi.org/10.2307/3007719

5. Biegler L.T. Integrated optimization strategies for dynamic process operations. Theoretical Foundations of Chemical Engineering, 2017, vol. 51, no. 6, pp. 910–927. https://doi.org/10.1134/S004057951706001X

6. Dadebo S.A., Mcauley K.B. Dynamic optimization of constrained chemical engineering problems using dynamic programming. Computers & Chemical Engineering, 1995, vol. 19, no. 5, pp. 513– 525. https://doi.org/10.1016/0098-1354(94)00086-4

7. Pan Y., Fei Z.-S., Zhao L., Liang J. Dynamic optimization for chemical process based on improved iterative dynamic programming algorithm. Journal of East China University of Science and Technology, 2013, vol. 39, no. 1, pp. 61–65.

8. Antipina E.V., Mustafina S.A., Antipin A.F. Algorithm of solving a multiobjective optimization problem on the basis of a kinetic chemical reaction model. Optoelectronics, Instrumentation and Data Processing, 2021, vol. 57, no. 6, pp. 668–674. https://doi.org/10.3103/S8756699021060029

9. Santos L.-R., Villas-Bôas F., Oliveira A.R.L., Perin C. Optimized choice of parameters in interior-point methods for linear programming. Computational Optimization and Applications, 2019, vol. 73, no. 2, pp. 535–574. https://doi.org/10.1007/s10589-019-00079-9

10. Antipina E.V., Antipin A.F. Algorithm for calculating the optimal initial concentrations of chemical reactions substances. Bulletin of the Technological University, 2017, vol. 20, no. 13, pp. 84–87. (in Russian)

11. Smith S., Mayne D.Q. Exact penalty algorithm for optimal control problems with control and terminal constraints. International Journal of Control, 1988, vol. 48, no. 1, pp. 257–271. https://doi.org/10.1080/00207178808906173

12. Gugat M., Zuazua E. Exact penalization of terminal constraints for optimal control problems. Optimal Control Applications and Methods, 2016, vol. 37, no. 6, pp. 1329–1354. https://doi.org/10.1002/oca.2238

13. Gao X., Zhang X., Wang Y. A simple exact penalty function method for optimal control problem with continuous inequality constraints. Abstract and Applied Analysis, 2014, vol. 2014, pp. 752854. https://doi.org/10.1155/2014/752854

14. Malisani P., Chaplais F., Petit N. An interior penalty method for optimal control problems with state and input constraints of nonlinear systems. Optimal Control Applications and Methods, 2016, vol. 37, no. 1, pp. 3–33. https://doi.org/10.1002/oca.2134

15. Pan L.P., Teo K.L. Linear-nonquadratic optimal control problems with terminal inequality constraints. Journal of Mathematical Analysis and Applications, 1997, vol. 212, no. 1, pp. 176–189. https://doi.org/10.1006/jmaa.1997.5489

16. Bushuev A.Yu., Ryauzov S.S. Optimization of solid fuel model gas generator design. Mathematical Modeling and Computational Methods, 2019, no. 4(24), pp. 3–14. (in Russian). https://doi.org/10.18698/2309-3684-2019-4-314

17. Panteleev A.V., Letova T.A. Optimization Methods in the Examples and Problems. Moscow, Vysshaja shkola Publ., 2005, 544 p. (in Russian)

18. Fitsov V. Software methodology for estimating the efficiency of the hardware composition of deep packet inspection system using the modernized Hooke–Jeeves method. Proceedings of Telecommunication Universities, 2021, vol. 7, no. 1, pp. 132–140. (in Russian). https://doi.org/10.31854/1813-324X-2021-7-1-132-140

19. Sergeev A.I., Krylova S.E., Shamaev S.Yu., Mamukov T.R. Parametric synthesis algorithms in the design of flexible manufacturing systems based on computer modeling. Izvestia of Samara Scientific Center of the Russian Academy of Sciences, 2021, vol. 23, no. 2, pp. 106–114. (in Russian). https://doi.org/10.37313/1990-5378-2021-23-2-106-114

20. Kozhevnikova P.V., Kuntsev V.E., Chuvashov A.A. Mathematical model for calculation of data sources in building membership function in problems of estimating reliable hydrocarbon reserves. Vestnik of Astrakhan state technical university. Series: Management, computer science and informatics, 2023, no. 1, pp. 98–104. (in Russian).

21. Novichkova A.V. Numerical analysis of olefins and organoaluminum compounds reactivity based on kinetic models of specific and general reactions. Dissertation for the degree of candidate of physical and mathematical sciences. Ufa, BashSU, 2015, 110 p. (in Russian)


Review

For citations:


Antipina E.V., Mustafina S.A., Antipin A.F. Numerical algorithm for finding the optimal composition of the reacting mixture on the basis of the reaction kinetic model. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2023;23(6):1128-1135. (In Russ.) https://doi.org/10.17586/2226-1494-2023-23-6-1128-1135

Views: 7


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2226-1494 (Print)
ISSN 2500-0373 (Online)