Optimization of parameters of mechanical mixing devices of vertical capacitive reactors

Authors

DOI:

https://doi.org/10.17308/sait/1995-5499/2022/3/33-44

Keywords:

optimization algorithms, computational fluid dynamics, mechanical mixing devices, mixing intensity

Abstract

The article presents the results of solving the problem of optimizing the operating and design parameters of mechanical mixing devices of vertical capacitive apparatuses using an algorithm, that guarantees an optimal solution to the problem with minimal time. The algorithm is developed on the basis of the brute force method implemented using the Python programming language and the SciPy library, which is designed to perform scientific and engineering calculations. A block diagram and a step-by-step implementation of the developed algorithm are presented. The evaluation of the performance was carried out by the example of solving the problem of determining the design and operating parameters of an open turbine agitator installed in a vertical capacitive apparatus with an elliptical bottom, which provide maximum mixing intensity.

Author Biographies

  • Evgeny I. Martyanov, Tambov State Technical University

    PhD student of the department “Computer-integrated systems in mechanical engineering” of Tambov State Technical University

  • Sergey V. Karpushkin, Tambov State Technical University

    Doctor of Technical Sciences, Professor, Professor of the department “Computer-integrated systems in mechanical engineering” of Tambov State Technical University

  • Vladimir V. Alexeev, Tambov State Technical University

    Doctor of Technical Sciences, Professor, Head of Information Systems and Information Protection Department, Tambov State Technical University

References

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Published

2022-11-09

Issue

Section

Mathematical Methods of System Analysis, Management and Modelling

How to Cite

Optimization of parameters of mechanical mixing devices of vertical capacitive reactors. (2022). Proceedings of Voronezh State University. Series: Systems Analysis and Information Technologies, 3, 33-44. https://doi.org/10.17308/sait/1995-5499/2022/3/33-44