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Doklady Chemistry

, Volume 486, Issue 1, pp 144–148 | Cite as

Optimizing the Energy Efficiency of a Local Process of Multistage Drying of a Moving Mass of Phosphorite Pellets

  • V. P. Meshalkin
  • V. I. BobkovEmail author
  • M. I. Dli
  • A. Yu. Belozerskii
  • I. I. Men’shova
CHEMICAL TECHNOLOGY
  • 4 Downloads

Abstract

A rapid heuristic computational algorithm for optimizing the energy and resource efficiency of a local process of multistage drying of a moving mass of phosphorite pellets was developed. The algorithm is distinguished by the use of heuristic computational procedures and heuristic rules of the iterative construction of a vector criterion of the efficiency of the chemical and energy engineering system. The criterion takes into account the energy consumption cost and the pellet quality indicators using both special barrier functions for deterministic constraints on control process variables (feed velocity and temperature of the carrier gas), and penalty functions for state variables of a local drying process (temperature gradient, heating rate, moisture content, moisture-transfer rate in pellets, temperature of the carrier gas at the outlet of the vertical multilayer pellet packing). Using the developed algorithm and software package, the scientifically grounded, optimal in energy consumption and dried pellet quality, operating conditions in local zones of drying of a travelling grate machine were determined.

Notes

FUNDING

This work was supported in the framework of the basic part of Government Assignment of the Ministry of Education and Science of the Russian Federation for performing scientific research (project no. 13.9597.2017/BCh).

REFERENCES

  1. 1.
    Meshalkin, V.P., Resursoenergoeffektivnye metody energoobespecheniya i minimizatsii otkhodov neftepererabatyvayushchikh proizvodstv. Osnovy teorii i nailuchshie prakticheskie rezul’taty (Resource-Efficient Methods of Energy Supply and Minimization of Waste from Refining Industries. Fundamentals of Theory and Best Practical Results), Moscow, Genuya: Khimiya, 2010.Google Scholar
  2. 2.
    Meshalkin, V.P., Bobkov, V.I., Dli, M.I., and Khodchenko, S.M., Dokl. Chem., 2017, vol. 475, part 2, pp. 188–191.CrossRefGoogle Scholar
  3. 3.
    Meshalkin, V.P., Bobkov, V.I., Dli, M.I., and Khodchenko, S.M., Dokl. Chem., 2017, vol. 477, part 21, pp. 286–289.CrossRefGoogle Scholar
  4. 4.
    Chodzhoi, M.Kh., Energosberezhenie v promyshlennosti (Energy Saving in Industry), Moscow: Metallurgiya, 1982.Google Scholar
  5. 5.
    Luis, P. and Van der Bruggen, B., J. Chem. Technol. Biotechonol., 2014, vol. 89, no. 9, pp. 1288–1303.CrossRefGoogle Scholar
  6. 6.
    Elgharbi, S., Horchani-Naifer, K., and Ferid, M., J. Therm. Anal. Calorim., 2015, vol. 119, no. 1, pp. 265–271.CrossRefGoogle Scholar
  7. 7.
    Bokovikov, B.A., Bragin, V.V., and Shvydkii, V.S., Stal., 2014, no. 8, pp. 43–48.Google Scholar
  8. 8.
    Rudobashta, S.P., J. Eng. Phys. Thermophys., 2010, vol. 83, no. 4, pp. 753–763.CrossRefGoogle Scholar
  9. 9.
    Bobkov, V.I., Borisov, V.V., Dli, M.I., and Meshalkin, V.P., Theor. Found. Chem. Eng., 2015, vol. 49, no. 6, pp. 842–846.CrossRefGoogle Scholar
  10. 10.
    Himmelblau, D.M., Applied Nonlinear Programming, Mc-Graw-Hill, 1972. Translated under the title Prikladnoe nelineinoe programmirovanie, Moscow: Mir, 1975.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2019

Authors and Affiliations

  • V. P. Meshalkin
    • 1
    • 2
  • V. I. Bobkov
    • 3
    Email author
  • M. I. Dli
    • 3
  • A. Yu. Belozerskii
    • 1
  • I. I. Men’shova
    • 1
  1. 1.Mendeleev Russian University of Chemical TechnologyMoscowRussia
  2. 2.Kurnakov Institute of General and Inorganic Chemistry, Russian Academy of SciencesMoscowRussia
  3. 3.MEI National Research Institute, Smolensk BranchSmolenskRussia

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