Computational and experimental research of the gas dynamic factors’ impact on the stochastic-statistical dispersion of particles in a two-phasr high-velocity flow


Аuthors

Abramov M. A.1*, Arefiev K. Y.1, Voronetsky A. V.2, Sarkisov A. V.2, Grishin I. M.1, Kruchkov S. V.1

1. Moscow Institute of Physics and Technology (National Research University), 9, Institutskiy per., Dolgoprudny, Moscow region, 141701, Russia
2. Bauman Moscow State Technical University, MSTU, 5, bldg. 1, 2-nd Baumanskaya str., Moscow, 105005, Russia

*e-mail: abramov.ma@mipt.ru

Abstract

The present study explores the gas-dynamic factors impact, specifically directed injection, on the empirical coefficients used to convert discrete particle trajectories into a locally continuous field of the dispersed phase flow intensity in supersonic turbulent two-phase flows. Statistical modeling is employed to develop a technique for the particle localization distribution evaluating, with account for the probabilistic nature of the trajectory deviations.

A discrete-continuous transformation method is applied by constructing a probability density function to evaluate the particle localization distribution. This technique assumes that the cluster velocity vector deviation from the section normal is negligible. By utilizing this probability density function, an equation is derived to convert discrete particle trajectories into a continuous field, approximating a two-dimensional normal distribution. The flow rate intensity, defined as the ratio of the particles mass flow to the unit area, is used to create a continuous field of particle flow intensity distribution. The basic trajectories of cluster motion are computed with the Lagrange-Euler method. A supersonic experimental setup for gas-dynamic spraying of coatings is employed to determine the the normal distribution value and examine the particles spatial localization.

The experimental data reveles that the acquired volumetric layer of sprayed condensed phase indicates the particle distribution structure in the cross-section of a high-speed two-phase flow.

The main findings of the study demonstrate that random factors significantly affect the particle distribution in the flow. The standard deviation of particle spatial localization ranges from 4.8 to 5.4 mm for a dispersed phase size of 15 to 40 μm in a supersonic flow, regardless of the presence or absence of a drifting flow.

Keywords:

two-phase flow, Lagrange-Euler method, probability density function, mean-square deviation, dispersed phase flow rate.

References

  1. Basharina T.A., Shmatov D.P., Glebov S.E., Akol'zin I.V. Trudy MAI, 2023, no. 132. URL: https://trudymai.ru/published.php?ID=176844

  2. Savin E.I., Min'kov L.L. Trudy MAI, 2023, no. 130. URL: https://trudymai.ru/published.php?ID=174603. DOI: 10.34759/trd-2023-130-07

  3. Dikshaev A.I., Kostyanoi E.M. Trudy MAI, 2014, no. 74. URL: https://trudymai.ru/published.php?ID=49300

  4. Varaksin A.Yu. Teplofizika vysokikh temperature, 2013, vol. 51, no. 3, pp. 421–455.

  5. Kozul M. A scanning particle tracking velocimetry technique for high‑Reynolds number turbulent flows, Experiments in Fluids, 2019, vol. 60, no. 137, pp. 255-266. DOI: 10.1007/s00348-019-2777-3

  6. Barnkob R., Kahler C.J., Rossi M. General defocusing particle tracking, Lab on a Chip, 2015, no. 5, pp. 562-568. DOI: 10.1007/s00348-020-2937-5

  7. Buist K.A., Jayaprakash P., Kuipers J.A.M. Magnetic Particle Tracking for Nonspherical Particles in a Cylindrical Fluidized Bed, AIChE Journal, 2017, vol. 63, no. 12, pp. 86-98. DOI: 10.1002/aic.15854

  8. Ge W., Sankaran R. An Adaptive Particle Tracking Algorithm for Lagrangian-Eulerian Simulations of Dispersed Multiphase Flows, Conference: AIAA Scitech 2019 Forum, 2019, no. 0728, pp. 582-691. DOI: 10.2514/6.2019-0728

  9. Khare P., Wang S., Yang V. Modeling of finite-size droplets and particles in multiphase flows, Chinese Journal of Aeronautics, 2015, vol. 28, no. 4, pp. 974 – 982. DOI: 10.1016/j.cja.2015.05.004

  10. Nigmatulin R.I., Gubaidullin D.A. Vliyanie fazovykh prevrashchenii v akustike polidispersnykh tumanov, Doklady RAN, 1996, vol. 347, no. 3, pp. 330.

  11. NakoryakovV.E., KashinskyO.N., BurdukovA.P. et al. Local characteristics of upward gas-liquids flows, International Journal of Multiphase flow, 1981, vol. 7, pp. 63-81. DOI: 10.1016/0301-9322(81)90015-X

  12. Yagodnikov D.A. Vosplamenenie i gorenie poroshkoobraznykh metallov (Ignition and Combustion of Metal Powders), Moscow, Izd-vo MGTU im. N.E. Baumana, 2009, 432 p.

  13. Pen'kov S.N., Sukhov A.V. Izvestiya vuzov. Seriya: Mashinostroenie, 1980, no. 1, pp. 56-66.

  14. Yagodnikov D.A., Voronetskii A.V., Sarab'ev V.I. Fizika goreniya i vzryva, 2016, vol. 52, no. 3, pp. 51-58.

  15. Yanenko N.N., Soloukhin R.I., Papyrin A.N. et. al. Sverkhzvukovye dvukhfaznye techeniya v usloviyakh skorostnoi neravnovesnosti chastits (Supersonic two-phase flows under the conditions of particle velocity nonequilibrium), Novosibirsk, Nauka, 1980, 160 p.

  16. Rychkov A.D. Matematicheskoe modelirovanie gazodinamicheskikh protsessov v kanalakh i soplakh (Mathematical modeling of gasdynamic processes in channels and nozzles), Novosibirsk, Nauka, 1988, 222 p.

  17. Garg R., Narayanan C., Subramaniam S. A Numerically Convergent Lagrangian-Eulerian Simulation Method for Dispersed Two-Phase Flows, International Journal of Multiphase Flow, 2009, vol. 35, no. 4, pp. 376–388. DOI: 10.1016/j.ijmultiphaseflow.2008.12.004

  18. Doisneau F., Arienti M., Oefelein J.C. A Semi-Lagrangian Transport Method for Kinetic Problems with Application to Dense-to-Dilute Polydisperse Reacting Spray Flows, Journal of Computational Physics, 2017, vol. 329, pp. 48–72. DOI: 10.1016/j.jcp.2016.10.042

  19. Edwards H.C. et al. Manycore performance-portability: Kokkos multidimensional array library, Scientific Programming, 2012, vol. 20, no. 2, pp. 89–114. DOI: 10.1155/2012/917630.

  20. Voronetskii A.V., Aref'ev K.Yu., Abramov M.A. Teplofizika i aeromekhanika, 2020, vol. 27, no. 6, pp. 833-851.

  21. Voronetskii A.V., Aref'ev K.Yu., Abramov M.A. Inzhenernyi zhurnal: nauka i innovatsii, 2021, no. 8, pp. 1-18. DOI: 10.18698/2308-6033-2021-8-2107

  22. Voronetskii A.V., Aref'ev K.Yu., Abramov M.A. et a.l. Teplofizika vysokikh temperature, 2022, vol. 60, no. 1, pp. 94-102.

  23. Abramov M.A., Aref'ev K.Yu. Vserossiiskaya nauchno-tekhnicheskaya konferentsiya «Raketno-kosmicheskie dvigatel'nye ustanovki»: sbornik trudov. Moscow, MGTU im. N.E. Baumana, 2023, pp. 91.

  24. Wielage B., Wank A., Pokhmurska H., et al. Development and Trends in HVOF Spraying Technology, Surface and Coatings Technology, 2006, vol. 201, no. 5, pp. 2032-2037. DOI: 10.1016/j.surfcoat.2006.04.049

  25. Hawryluk M., Ziemba J., Dworzak L. Development of a Method for Tool Wear Analysis Using 3D Scanning, Metrology and Measurement Systems, 2017, vol. 24, no.4, pp. 739-757. DOI: 10.1515/mms-2017-0054

  26. Alharbi N., Stokes J. Optimizing HVOF spray process parameteers and post-heat treatment for Micro/Nano WC-12%Co, mixed with Inconel-625 Powders: A Critical Review, 32 International Manufacturing Conference, 2015, 13 p.

  27. Beketaeva A.O., Naimanova A.Zh. Prikladnaya mekhanika i tekhnicheskaya fizika, 2011, vol. 52, no. 6, pp. 58-68.

  28. Langtry R.B., Menter F.R. Correlation-Based Transition Modeling for Unstructured Parallelized Computational Fluid Dynamics Codes, AIAA Journal, 2009, vol. 47, no. 12, pp. 2894–2906. DOI: 10.2514/1.42362


Download

mai.ru — informational site MAI

Copyright © 2000-2024 by MAI

Вход