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  4. Mathematical Model of Energy Transformation Processes in Barrel System for Determining Shooting Performance

Mathematical Model of Energy Transformation Processes in Barrel System for Determining Shooting Performance

JEECS.
2022;
Volume 8, Number 1
: pp. 28 – 39
https://doi.org/10.23939/jeecs2022.01.028
Received: February 07, 2022
Revised: May 05, 2022
Accepted: May 12, 2022

O. Brunetkin, V. Kuzmenko, O. Soloviova. Mathematical model of energy transformation processes in barrel system for determining shooting performance. Energy Engineering and Control Systems, 2022, Vol. 8, No. 1, pp. 28 – 39. https://doi.org/10.23939/jeecs2022.01.028

Authors:
  1. Oleksandr Brunetkin
  2. Vitalii Kuzmenko
  3. Olha Soloviova
1
Odesа Polytechnic State University
2
National University "Odesa Maritime Academy"
3
Odesа Polytechnic State University

A phenomenon has been singled out that is present during almost every shot. It manifests itself in a muzzle blast in the form of soot of a certain amount. The Bell-Boudoir thermochemical reaction has been defined, which explains the formation of soot in powder gases during the shot. The conditions making it possible to manifest have been mentioned. A method for solving the problem of internal ballistics has been developed, enabling to determine the temperature of powder gases along the length of the gun barrel at different times and at different positions of the projectile in the barrel. The modelling of the powder gases temperature distribution in the barrel space between the charging chamber and the moving projectile has been carried out in the model system. The possibility of changing the length of the zone of the Bell-Boudoir reaction (the zone of soot formation) depending on the initial data has been shown. The use of a fresh powder charge and a degraded one has been modelled.

gun
powder gases
temperature distribution
disproportionation reaction
soot
  1. Dobrynin E., Maksymov M., Boltenkov V. (2020). Development of a Method for Determining the Wear of Artillery Barrels by Acoustic Fields of Shots. Eastern–European Journal of Enterprise Technologies. Vol 3, No 5 (105), 2020, p.6–18. https://doi.org/10.15587/1729-4061.2020.206114
  2. Dobrynin Y., Volkov V., Maksymov M., Boltenkov V. (2020). The Development of Physical Models for Acoustic Wave Formation at the Artillery Shot and Study of Possibilities for Separate Registration of Various Types Waves. Eastern–European Journal of Enterprise Technologies. Vol 4, No 5 (106), 2020, p.6–15 https://doi.org/10.15587/1729-4061.2020.209847
  3. Serebryakov M. E. (1962). Internal ballistics of barrel systems and powder rockets. Moscow, 702. (in Russian)
  4. Carlucci D.E., Jacobson S.S. (2008). Ballistics : theory and design of guns and ammunition. Taylor & Francis Group, 2008, pp. 502. ISBN-13: 978-1-4200-6618-0; ISBN-10: 1-4200-6618-8; http://www.taylorandfrancis.com
  5. Rashad M.M., Zhang X.B., Elsadek H. (2013). Numerical simulation of interior ballistics for large caliber guided projectile naval gun. Journal of Engineering and Applied Science Vol. 60, No. 2, 2013, pp.163-176. https://www.researchgate.net/publication/264786882
  6. Jang J., Oh S., Roh T. (2016). Development of three-dimensional numerical model for combustion-flow in interior ballistics. Journal of Mechanical Science and Technology. Vol 30, 2016, pp. 1631-1637. https://doi.org/10.1007/s12206-016-0319-y
  7. Cheng C., Zhang X. (2013). Modeling of Interior Ballistic Gas-Solid Flow Using a Coupled Computational Fluid Dynamics-Discrete Element Method. ASME.J. Appl. Mech. 2013; 80(3): 031403. https://doi.org/10.1115/1.4023313
  8. Li P., Zhang X. (2020). Numerical research on adverse effect of muzzle flow formed by muzzle brake considering secondary combustion. Defence Technology. 2020, ISSN 2214-9147, https://doi.org/10.1016/j.dt.2020.06.019.
  9. Steward B.J., Perram G.P., Gross K.C. (2011). Visible and Near-Infrared Spectra of the Secondary Combustion of a 152 mm Howitzer. Applied Spectroscopy. 2011; 65(12):1363-1371. https://doi.org/10.1366/11-06445
  10. Steward B.J., Bauer K.W., Perram G.P. (2012). Remote discrimination of large-caliber gun firing signatures. J. Appl. Rem. Sens. 6(1) 063607, 2012 https://doi.org/10.1117/1.JRS.6.063607
  11. Steward B.J., Gross K.C., Perram G.P. (2011). Reduction of optically observed artillery blast wave trajectories using low dimensionality models. Proc. SPIE 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII, 80200D, 2011; https://doi.org/10.1117/12.883524
  12. Zakharenkov V.F. (2010). Interior ballistics and automation of artillery gun design. Tutorial. Balt. state tech. un-t. - SPb., 2010, 276 p. ISBN 978-5-85546-580-8, https://ua1lib.org/book/3064917/757a40?id=3064917&secret=757a40
  13. Li X., Mu L., Zang Y., Qin Q. (2020). Study on performance degradation and failure analysis of machine gun barrel, Defence Technology, Volume 16, Issue 2, 2020, Pages 362-373, ISSN 2214-9147, https://doi.org/10.1016/j.dt.2019.05.008.
  14. Kriukov O., Melnikov R., Bilenko О., Zozulia A., Herasimov S., Borysenko M., Pavlii V., Khmelevskiy S., Abramov D., & Sivak V. (2019). Modeling of the process of the shot based on the numerical solution of the equations of internal ballistics. Eastern-European Journal of Enterprise Technologies, 1/5 (97), 40–46. https://doi.org/10.15587/1729-4061.2019.155357
  15. Rout K.R., Gil M.V., Chen D. (2019). Highly selective CO removal by sorption enhanced Boudouard reaction for hydrogen production. Catalysis Science & Technology, 2019, Vol. 9, Issue 15, p. 4100–4107. https://doi.org/10.1039/C9CY00851A
  16. Krylova A.Y. (2014). Products of the Fischer-Tropsch synthesis. Solid Fuel Chem. 48, 22–35 (2014). https://doi.org/10.3103/S0361521914010030
  17.  Kogler M., Köock E.-M., Klöotzer B., Schachinger T., Wallisch W., Henn R., Huck C.H., Hejny C., Penner C. (2016). High-temperature carbon deposition on oxide surfaces by CO disproportionation. J. Phys. Chem. C 3(120), 1795–1807 (2016). https://doi.org/10.1021/acs.jpcc.5b12210
  18. Mianowski A., Robak Z., Tomaszewicz M. et al. (2012). The Boudouard–Bell reaction analysis under high pressure conditions. J Therm Anal Calorim 110, 93–102 (2012). https://doi.org/10.1007/s10973-012-2334-2
  19.  Brunetkin O., Maksymov M. V., Maksymenko A., Maksymov M. M. (2019). Development of the unified model for identification of composition of products from incineration, gasification, and slow pyrolysis. Eastern-European Journal of Enterprise Technologies. – 2019. – 4/6 (100). – P. 25–31 DOI: https://doi.org/10.15587/1729-4061.2019.176422
  20. Burnham A.K., Fried L.E. (2006). Kinetics of PBX9404 aging. UCRL-CONF-224391. 7th aging, compatibility and stockpile stewardship conference. Los Alamos, NM, USA. September 26, 2006 – September 28, 2006. – 6 p. https://www.osti.gov/biblio/894349-kinetics-pbx9404-aging
  21.  Anipko O.B., Khaykov V.L. (2012). Methods analysis for assessment of propellant charges as a part of the artillery ammunition monitoring system Integrated Technologies and Energy Conservation, NTU “KhPI”, 3, 2012. pp. 60–71. http://repository.kpi.kharkov.ua/handle/KhPI-Press/2199
  22. Alemasov V.E., Glushko V. (1974). Thermodynamic and thermophysical properties of combustion products = Termodinamicheskie i teplofizicheskie svoistva produktov sgoraniya : translated from Russian [by R. Kondor, and Ch. Nisenbaum], Jerusalem : Israel Program for Scientific Translations, 1974-1976. https://searchworks.stanford.edu/view/892711
  23.  Rusyaka I.G., Tenenevb V.А. (2020). Modeling of ballistics of an artillery shot taking into account the spatial distribution of parameters and backpressure. Computer research and modeling, 2020, Vol. 12, № 5 p. 1123-1147 https://doi.org/10.20537/2076-7633-2020-12-5-1123-1147
  24. Pelykh S.N., Maksimov M.V., Baskakov V.E. (2008). Model of cladding failure estimation under multiple cyclic reactor power changes, The 2-nd International Conference ’Current Problems in Nuclear Physics and Atomic Energy’. Book of abstracts 2008, p. 638-641, https://inis.iaea.org/search/search.aspx?orig_q=RN:40062726.
  25. Brunetkin O., Davydov V., Butenko O., Lysiuk G., Bondarenko A. (2019). Determining the composition of burned gas using the method of constraints as a problem of model interpretation. Eastern-European Journal of Enterprise Technologies. – 2019. – 3/6 (99). – P. 22–30. https://doi.org/10.15587/1729-4061.2019.169219