Skip to main content

Numerical Modelling of the Fluid Flow at the Outlet from Narrowed Space for a Better Water Management

  • Chapter
  • First Online:
  • 600 Accesses

Part of the book series: Springer Water ((SPWA))

Abstract

In the water management, events of significant changes of the running fluid flow space occur very frequently. Such change influences significantly the characteristics of the flow field and thus its effects on the environment. These might be the effects on adjacent objects in the close proximity such as walls of the designated space, or effects on objects bypassed with the running fluid. Such a situation frequently influences the surrounding area. The flow run may affect the terrain of the land or even the ambient climate in some cases. This chapter is dedicated to problems of numerical modelling of Newtonian fluid flows in changing flow space. Showing a particular task, which is solved numerically using computational fluid dynamics (CFD) codes in ANSYS Fluent software, the reader becomes familiar with both problems of the mathematical specification of fluid movements and principles of the correct choice of the numerical model. To resolve this task, four numerical models are selected. Basic turbulent characteristics of the flow field are monitored. Outputs of individual models are evaluated and compared with each other. Selected results are also verified by experimental measuring.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Abbreviations

A :

Turbulent viscosity function (SST k-ω) (-)

\(C_{ij}\) :

Convection member (RSM) (kg m−1s−3)

\(C_{\mu }\) :

Constant (-)

\(C_{\mu }\) :

Model function for \(\mu_{t}\) calculation (Realisable k-ε) (-)

\(C_{1\varepsilon }\) :

Empiric constant (-)

\(C_{2\varepsilon }\) :

Empiric constant (-)

\(D_{L,ij}\) :

Molecular diffusion member (RSM) (kg m−1s−3)

\(D_{T,ij}^{*}\) :

Turbulent diffusion member (RSM) (kg m−1s−3)

\(D_{\omega }\) :

Mixing member (SST k-ω) (kg m−3s−2)

\(f_{i} ,F_{i}\) :

Force components (N)

\(G_{k}\) :

Generation member of turbulent kinetic energy (kg m−1s−3)

\(G_{\omega }\) :

Generation member of dissipation (SST k-ω) (kg m−3s−2)

k :

Turbulent kinetic energy (m2s−2)

I :

Linear scale factor of turbulence (m)

p :

Compression (Pa)

\(P_{ij}\) :

Compression production member (RSM) (kg m−1s−3)

t :

Time (s)

u :

Momentary velocity (m s−1)

\(u_{i}\) :

I-fold component of momentary velocity (m s−1)

\(u_{i}\) :

Wind velocity at fall in the i-fold building point (m s−1)

\(\overline{u}\) :

Mean velocity (time averaged) (ms−1)

\(\overline{u_{i}}\) :

Mean wind velocity at fall in the i-fold building point (m s−1)

\(\overline{{u_{i,j,k} }}\) :

i, j, k-fold component of mean velocity (m s−1)

\(u_{i,jk}^{\prime }\) :

i, j, k-fold component of fluctuation velocity (m s−1)

\(x_{i}\) :

Cartesian coordinate system [x1, x2, x3] or [x, y, z] (m)

S :

Tensor module of the mean deformation velocity (k-ε) (s−1)

\(S_{i,j}\) :

Deformation velocity tensor (k-ε) (s−1)

\(Y_{k}\) :

Dissipation member for k (SST k-ω) (kg m−1s−3)

\(Y_{\omega }\) :

Dissipation member for ω (SST k-ω) (kg m−3s−2)

\(\delta_{ij}\) :

Kronecker delta symbol (-)

\(\varepsilon\) :

Velocity of kinetic energy dissipation (m2s−3)

\(\varepsilon_{ij}^{*} ,\varepsilon_{ij}\) :

Dissipation member (RSM) (kg m−1s−3)

\(\varPhi_{ij}^{*} ,\varPhi_{ij}\) :

Compressive stress member (RSM) (kg m−1s−3)

\(\kappa\) :

Von Karman constant (-)

\(\mu\) :

Dynamic viscosity (Pa s), (kg m−1s−1)

\(\mu_{t}\) :

Dynamic turbulent viscosity (Pa s), (kg m−1s−1)

\(\nu\) :

Kinematic viscosity (m2s−1)

\(\nu_{t}\) :

Kinematic turbulent viscosity (m2s−1)

\(\rho\) :

Density (kg m−3)

\(\sigma_{k}\) :

Turbulent Prandtl number for k (-)

\(\sigma_{\varepsilon }\) :

Turbulent Prandtl number for ε (-)

\(\sigma_{{v_{i} }}\) :

Turbulent Prandtl number for \(\nu_{t}\) (-)

\(\tau\) :

Viscous stress (Pa)

\(\omega\) :

Dissipation per turbulent kinetic energy (s−1)

\(i\) :

Velocity component index, iteration index, point index (-)

\(i\) :

Summary index (-)

\(j,k,l\) :

Summary Einstein index (-)

References

  1. Sargison JE, Walker GJ, Rosi R (2004) Design and calibration of a wind tunnel with a two dimensional contraction. In: Proceeding of the 15th Australian fluid mechanic conference, Sydney, Australia, pp 143–146. ISBN 1-864-87695-6

    Google Scholar 

  2. Fang FM, Chen JC, Hong YT (2001) Experimental and analytical evaluation of flow in a square-to square wind tunnel contraction. J Wind Eng Ind Aerodyn 89(1):247–262. ISSN: 0167-6105

    Google Scholar 

  3. Fang FM (1997) A design method for contractions with square end sections. J Fluids Eng 119(2):454–458. ISSN: 1555-1415

    Google Scholar 

  4. Wolf T (1995) Design of a variable contraction for a full-scale automotive wind tunnel. J Wind Eng Ind Aerodyn 56(1):1–21. ISSN: 0167-6105

    Google Scholar 

  5. Michalcová V, Kuznětsov S, Pospíšil S, Brožovský J (2014) Numerical and experimental investigations of air flow turbulence characteristics in the wind tunnel. Appl Mech Mater 617:275–279

    Article  Google Scholar 

  6. Vijiapurapu S, Cui J (2010) Performance of turbulence models for flows through rough pipes. Appl Math Model 34(6):1458–1466. ISSN: 0307-904X

    Article  Google Scholar 

  7. Michalcová V, Kuznětsov S, Pospíšil S (2013) Models of load on buildings from the effects of the flow field. Trans VŠB Tech Univ Ostrava Constr Ser 13(2):91–97. ISSN: 1804-4824 (Online); ISSN: 1213-1962 (Print)

    Google Scholar 

  8. Rodríguez M, Lastra J, Oro MF, Galdo M, Vega E, Marigorta B, Morros CS (2013) Novel design and experimental validation of a contraction nozzle for aerodynamic measurements in a subsonic wind tunnel. J Wind Eng Ind Aerodyn 118:35–43. ISSN: 0167-6105

    Google Scholar 

  9. Liu P, Duan H, Zhao W (2009) Numerical investigation of hot air recirculation of air-cooled condensers at a large power plant. Appl Therm Eng 29(10):1927–1934. ISSN: 1359-4311

    Article  CAS  Google Scholar 

  10. Tropea C, Yarin AL, Foss JF (eds) (2007) Measurement of turbulent flows. Springer (Chapter 10)

    Google Scholar 

  11. Toda HB, Cabrit O, Truffin K, Bruneaux G, Nicoud F (2014) Assessment of subgrid-scale models with an LES-dedicated experimental database: the pulsatile impinging jet in turbulent cross flow. Phys Fluids Am Inst Phys 26:075108

    Article  Google Scholar 

  12. Kotrasová K, Grajciar I (2014) Dynamic analysis of liquid storage cylindrical tanks due to earthquake. Adv Mater Res 969:119–124

    Article  Google Scholar 

  13. Kotrasová K (2014) Sloshing of liquid in rectangular tank. Adv Mater Res 969:320–323

    Article  Google Scholar 

  14. Kotrasová K (2017) Study of hydrodynamic pressure on wall of tank. Procedia Eng 190:2–6. ISSN: 1877-7058

    Article  Google Scholar 

  15. Michalcová V, Kotrasová K (2012) Influence of numerical diffusion on exactness of calculation in software FLUENT. Bull Transilvania Univ’Brasov 5(54):99–106

    Google Scholar 

  16. Eymard R, Gallouët T, Herbin R (2000) Finite volume methods. In: Handbook of numerical analysis, vol 7. Elsevier, pp 713-1018. ISSN: 1570-8659

    Google Scholar 

  17. Santis DD, Geraci G, Guardone A (2012) Finite volume and finite element schemes for the euler equation in cylindrical and spherical coordinates. J Comput Appl Math ISSN: 0377-0427

    Google Scholar 

  18. Mehta DR, Bell JH (1989) Boundary-layer predictions for small low-speed contractions. AIAA J 27(3):372–374

    Article  Google Scholar 

  19. Michalcová V, Kuznětsov S, Pospíšil S (2014) Numerical and experimental study of the load of an object due to the effects of a flow field in the atmospheric boundary layer. Int J Math Comput Simul 8:135–140. ISSN: 0378-4754

    Google Scholar 

  20. Irrenfried C, Steiner H (2017) DNS based analytical P-function model for RANS with heat transfer at high Prandtl numbers. Int J Heat Fluid Flow 66:217–225. ISSN: 0142-727X

    Google Scholar 

  21. Taraba B, Michalec Z, Michalcová V, Blejchař T, Bojko, Kozubková M (2014) CFD simulations of the effect of wind on the spontaneous heating of coal stockpiles. Fuel 118:107–112. ISSN: 0016-2361

    Google Scholar 

  22. Michalcová V, Kuznětsov S, Pospíšil S (2014) Numerical modelling of air flow attributes in a contractions chamber. Trans VŠB Tech Univ Ostrava Civil Eng Ser 14(2):11–16. ISSN: 1804-4824 (Online); ISSN: 1213-1962 (Print)

    Article  Google Scholar 

  23. Michalcová V, Kuznětsov S, Pospíšil S, Brožovský J (2014) Numerical and experimental investigations of air flow turbulence characteristics in the wind tunnel contraction. Appl Mech Mater 617:275–279

    Article  Google Scholar 

  24. Kocich R, Bojko M, Macháčková A, Klečková Z (2012) Numerical analysis of the tubular heat exchanger designed for co-generating units on the basis of microturbines. J Heat Mass Transfer 55(19/20):5336–5342. ISSN: 00179310

    Article  Google Scholar 

  25. Bojko M, Kozdera M, Kozubkova M (2014) Investigation of viscous fluid flow in an eccentrically deposited annulus using CFD methods. In: Proceeding of the 8th international conference on experimental fluid mechanics, Kutna Hora, Czech Republic. ISSN: 21016275, ISBN: 978-802605375-0

    Google Scholar 

  26. Balbus S (2017) When is high Reynolds number shear flow not turbulent? J Fluid Mech 824:1–4

    Article  CAS  Google Scholar 

  27. ANSYS® Fluent Release 18.2, Fluent documentation, Theory Guide

    Google Scholar 

  28. Khadra K, Angot P, Parneix S, Caltagirone JP (2000) Fictitious domain approach for numerical modelling of Navier-Stokes equations. Int J Numer Meth Fluids 34:651–684

    Article  Google Scholar 

  29. Coleman G, Sandberg R (2010) A primer on direct numerical simulation of turbulence—methods, procedures and guidelines. Aerodynamics and Flight Mechanics Research Group

    Google Scholar 

  30. Spalart PR, Coleman GN, Johnstone R (2008) Direct numerical simulation of the Ekman layer: a step in Reynolds number, and cautious support for a log law with a shifted origin. Phys Fluids 20:101507

    Article  Google Scholar 

  31. Zhiyin Y (2015) Large-eddy simulation: past, present and the future. Chin J Aeronaut 28(1):11–24. ISSN: 1000-9361

    Google Scholar 

  32. Xie ZT, Castro IP (2008) Efficient generation of inflow conditions for large-eddy simulation of street-scale flows. Flow Turbul Combust 81:449–470. ISSN: 1386-6184

    Google Scholar 

  33. Hertwig D, Efthimiou GC, Bartzis JG, Leitl B (2012) CFD-RANS model validation of turbulent flow in a semi-idealized urban canopy. J Wind Eng Ind Aerodyn 111:61–72. ISSN: 0167-6105

    Google Scholar 

  34. Schmitt FG (2007) About Boussinesq’s turbulent viscosity hypothesis: historical remarks and a direct evaluation of its validity. Comptes Rendus Mécanique, Elsevier Masson 335(9–10):617–627

    Article  CAS  Google Scholar 

  35. Sedláček D (2017) Modelový výzkum proudění na vtoku do propustku. Thesis, ČVUT, Praha

    Google Scholar 

Download references

Acknowledgements

Financial support from VŠB-Technical University of Ostrava by means of the Czech Ministry of Education, Youth and Sports through the Institutional support for conceptual development of science, research, and innovations for the year 2018 and by the Scientific Grant Agency of the Ministry of Education of Slovak Republic and the Slovak Academy of Sciences the project VEGA 1/0477/15 and VEGA 1/0374/19 is gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. Michalcová .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Michalcová, V., Kotrasová, K. (2020). Numerical Modelling of the Fluid Flow at the Outlet from Narrowed Space for a Better Water Management. In: Zelenakova, M., Hlavínek, P., Negm, A. (eds) Management of Water Quality and Quantity. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-030-18359-2_11

Download citation

Publish with us

Policies and ethics