Modeling Three-Dimensional Liquid Flows in Computer-Controlled Vibrojet Mixer Using FlowVision

  • Yu. S. Sergeev
  • S. V. SergeevEmail author
  • G. E. Karpov
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


The chapter shows that to study the three-dimensional flows arising from the complex effect of vibration on Newtonian fluids, it is best to use a topological method of computer modeling. For reliability and clarity of the numerical modeling results obtained, FlowVision software and SUSU supercomputer resources were used. The calculation results showed the superiority of the new controlled vibrojet method over the traditional process of mixing liquid media. The calculations of flows rates were performed. The conditions for the formation of internal submerged toroidal flows and counter-swirling jets inside these flows are revealed. The simulation results made it possible to determine the control parameters of the process, to describe the functionality and technological capabilities of the computer-controlled vibrojet mixer. Its design is based on a fundamentally new method of controlled vibration mixing of multicomponent mixtures and solutions used in the chemical, pharmaceutical, food, engineering, and mining industries. As a result, practical technology has received a tool for digital processing of the mixing process.


Modeling FlowVision Mixing automation Liquid multicomponent systems Digital twin mixing 



South Ural State University is grateful for financial support of the Ministry of Education and Science of the Russian Federation (grant No 9.7960.2017/BP).


  1. 1.
    Hessel V, Noël T (2012) Micro process technology, 2. Processing. Ullmann’s Encyclopedia of Industrial Chemistry.
  2. 2.
    Xia B, Sun D-W (2002) Applications of computational fluid dynamics (cfd) in the food industry: a review. Comput Electron Agric 34(1):5–24. Scholar
  3. 3.
    Latyshev VN (1975) Improving the efficiency of cutting fluid. Mechanical Engineering, MoscowGoogle Scholar
  4. 4.
    Khudobin LV, Babichev AP, Bulyzhev EM (2006) Lubricating and cooling technological tools and their use in machining. Mechanical Engineering, MoscowGoogle Scholar
  5. 5.
    Hoelscher KP, De Stefano G, Riley M, Young S (2012) Application of nanotechnology in drilling fluids. In: Paper presented at the SPE International Oilfield Nanotechnology Conference and Exhibition, Noordwijk, The NetherlandsGoogle Scholar
  6. 6.
    Matsunaga D, Imai Y, Yamaguchi T, Ishikawa T (2016) Rheology of a dense suspension of spherical capsules under simple shear flow. J Fluid Mech 786:110–127. Scholar
  7. 7.
    Dodd MS, Ferrante A (2016) On the interaction of Taylor length scale size droplets and isotropic turbulence. J Fluid Mech 806:356–412. Scholar
  8. 8.
    Schlichting G (1974) Theory of the boundary layer. Publishing House “Science”, Moscow, p 712Google Scholar
  9. 9.
    Yatsun SF, Mishchenko VY, Mishchenko EV (2009) The impact of vibration effects on the extraction process in the food industry. News of universities. Food Technol 4:70–72Google Scholar
  10. 10.
    Blekhman II (1994) Vibration mechanics. Science, MoscowGoogle Scholar
  11. 11.
    Sergeev YS, Sergeev SV, Zakirov RG, Nekrutov VG, Gordeev EN, Irshin AV et al (2013) Method of mixing liquid. Russian Federation Patent 2543204, 27 Feb 2015Google Scholar
  12. 12.
    Kulkarni PM, Morris JF (2008) Suspension properties at finite Reynolds number from simulated shear flow. Phys Fluids 20(4):040602. Scholar
  13. 13.
    Sergeev YS, Sergeev SV, Maltsev PS (2015) Intensification of hydrodynamic processes in the preparation and regeneration of technological multicomponent mixtures Science SUSU: Materials of the 67th scientific conference. Publishing Center SUSU, Chelyabinsk, pp 1762–1766Google Scholar
  14. 14.
    Sandalov VM, Sergeev YS (2012) Dynamic model of switched reluctance vibratory drive. Russian Electrical Engineering 83(8):432–435. Scholar
  15. 15.
    Sergeev YS, Sandalov VM, Karpov GE (2017) Modeling switched reluctance vibratory drive. Bulletin of SUSU. Series: Energy 17(4):90–98.
  16. 16.
    Sergeev YS, Sandalov VM, Karpov GE (2018) ‘Modeling of switched reluctance electric vibration drive with adaptive control’ 2018 international russian automation conference (RusAutoCon), 9–16 Sept 2018, pp 1–4Google Scholar
  17. 17.
    Lakirev SG, Khilkevich YM, Sergeev SV (1988) The method of excitation of circular oscillations and device for its implementation. USSR Patent 1664412, 1991Google Scholar
  18. 18.
    Sergeev YS, Sergeev SV, D’yakonov AA, Kononistov AV, Karpov GE, Mikryukov AA (2018) Automated monitoring system for self-synchronizing vibrational drives. Russian Engineering Research 38(2):86–90.
  19. 19.
    Rudman M (1998) Volume-tracking methods for interfacial flow calculations. Int J Numer Meth Fluids 24(7):671–691.;2-9MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Stickel JJ, Powell RL (2005) Fluid mechanics and Rheology of dense suspensions. Annu Rev Fluid Mech 37(1):129–149. Scholar
  21. 21.
    Rosti ME, De Vita F, Brandt L (2018) Numerical simulations of emulsions in shear flows. Acta Mechanica.
  22. 22.
    Izbassarov D, Rosti ME, Ardekani MN, Sarabian M, Hormozi S, Brandt L et al (2018) Computational modeling of multiphase viscoelastic and elastoviscoplastic flows. Int J Numer Meth Fluids 88(12):521–543. Scholar
  23. 23.
    Kim J, Moin P (1985) Application of a fractional-step method to incompressible Navier-Stokes equations. J Comput Phys 59(2):308–323. Scholar
  24. 24.
    Pastrana D, Cajas JC, Lehmkuhl O, Rodríguez I, Houzeaux G (2018) Large-eddy simulations of the vortex-induced vibration of a low mass ratio two-degree-of-freedom circular cylinder at subcritical Reynolds numbers. Comput Fluids 173:118–132. Scholar
  25. 25.
    Alizad Banaei A, Loiseau J-C, Lashgari I, Brandt L (2017) Numerical simulations of elastic capsules with nucleus in shear flow. Eur J Comput Mech 26(1–2):131–153. Scholar
  26. 26.
    Kostenetskiy P (2016) SUSU supercomputer resourcesGoogle Scholar
  27. 27.
    Rekachinsky AI, Chulkevich RA, Kostenetskiy PS (2018) Modeling parallel processing of databases on the central processor Intel Xeon Phi KNL’ 2018. In: 41st international convention on information and communication technology, Electronics and Microelectronics (MIPRO), 21–25 May 2018, pp 1605–1610Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yu. S. Sergeev
    • 1
  • S. V. Sergeev
    • 1
    Email author
  • G. E. Karpov
    • 1
  1. 1.South Ural State UniversityZlatoustRussia

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