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Modulation of turbulence in forced convection by temperature-dependent viscosity

  • Francesco Zonta (a1), Cristian Marchioli (a1) and Alfredo Soldati (a1)

Abstract

In this work, we run a numerical experiment to study the behaviour of incompressible Newtonian fluids with anisotropic temperature-dependent viscosity in forced convection turbulence. We present a systematic analysis of variable-viscosity effects, isolated from gravity, with relevance for aerospace cooling/heating applications. We performed an extensive campaign based on pseudo-spectral direct numerical simulations of turbulent water channel flow in the Reynolds number parameter space. We considered constant temperature boundary conditions and different temperature gradients between the channel walls. Results indicate that average and turbulent fields undergo significant variations. Compared with isothermal flow with constant viscosity, we observe that turbulence is promoted in the cold side of the channel, characterized by viscosity locally higher than the mean: in the range of the examined Reynolds numbers and in absence of gravity, higher values of viscosity determine an increase of turbulent kinetic energy, whereas a decrease of turbulent kinetic energy is determined at the hot wall. Examining in detail the turbulent kinetic energy budget, we find that turbulence modifications are associated with changes in the rate at which energy is produced and dissipated near the walls: specifically, at the hot wall (respectively cold wall) production decreases (respectively increases) while dissipation increases (respectively decreases).

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Email address for correspondence: soldati@uniud.it

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Also at Department of Fluid Mechanics, CISM, 33100, Udine, Italy.

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1. Adrian, R. J. 2007 Hairpin vortex organization in wall turbulence. Phys. Fluids 19, 041301.
2. Bae, J. H., Yoo, Y. J. & Choi, H. 2005 Direct numerical simulation of supercritical flows with heat transfer. Phys. Fluids 17, 105104.
3. Behzadmehr, A., Saffar-Avval, M. & Galanis, N. 2007 Prediction of turbulent forced convection of a nanofluid in a tube with uniform heat flux using a two phase approach. Intl J. Heat Fluid Flow 28, 211219.
4. Bernard, P. S., Thomas, J. M. & Handler, R. A. 1993 Vortex dynamics and the production of Reynolds stress. J. Fluid Mech. 253, 385419.
5. Buyukalaka, O. & Jackson, J. D. 1998 The correction to take account of variable property effects on turbulent forced convection to water in a pipe. Intl J. Heat Mass Transfer 41, 665669.
6. Campolo, M., Andreoli, M. & Soldati, A. 2009 Computing flow, combustion, heat transfer and thrust in a micro-rocket via hierarchical decomposition. Microfluid Nanofluid 7, 5773.
7. Iwamoto, K., Suzuki, Y. & Kasagi, N. 2002 Reynolds number effect on wall turbulence: toward effective feedback control. Intl J. Heat Fluid Flow 23, 678689.
8. Kang, S., Iaccarino, G. & Ham, F. 2009 DNS of buoyancy-dominated turbulent flows on a bluff body using the immersed boundary method. J. Comput. Phys. 228, 31893208.
9. Kim, J., Moin, P. & Moser, R. 1987 Turbulence statistics in fully-developed channel flow at low Reynolds number. J. Fluid Mech. 177, 133166.
10. Lam, K. & Banerjee, S. 1992 On the condition of streak formation in bounded flows. Phys. Fluids A 4, 306320.
11. Lee, J., Gharagozloo, P. E., Kolade, B., Eaton, J. K. & Goodson, K. E. 2010 Nanofluid convection in microtubes. Trans. ASME J. Heat Transfer 132, 092401.
12. Li, X., Hashimoto, K., Tominaga, Y., Tanahashi, M. & Miyauchi, T. 2008 Numerical study of heat transfer mechanism in turbulent supercritical CO2 channel flow. J. Therm. Sci. Tech. - JPN 3, 112123.
13. Lombardi, P., De Angelis, V. & Banerjee, S. 1996 Direct numerical simulation of near-interface turbulence in coupled gas–liquid flow. Phys. Fluids 8, 16431665.
14. Luchik, T. S. & Tiederman, W. G. 1987 Time scale and structure of ejections and bursts in turbulent channel flows. J. Fluid Mech. 174, 529552.
15. Maiga, S. E. B., Palm, S. J., Nguyen, C. T., Roy, G. & Galanis, N. 2005 Heat transfer enhancement by using nanofluids in forced convection flows. Intl J. Heat Fluid Flow 468, 283315.
16. Marchioli, C., Soldati, A., Kuerten, J. G. M., Arcen, B., Taniere, A., Goldensoph, G., Squires, K. D., Cargnelutti, M. F. & Portela, L. M. 2008 Statistics of particle dispersion in direct numerical simulations of wall-bounded turbulence: results of an international collaborative benchmark test. Intl J. Multiphase Flow 34, 879893.
17. Marchioli, C. & Soldati, A. 2002 Mechanisms for particle transfer and segregation in turbulent boundary layer. J. Fluid Mech. 468, 283315.
18. Monin, A. S. & Yaglom, A. M. 1975 Statistical Fluid Mechanics: Mechanism of Turbulence, book 2. MIT Press.
19. Pan, Y. & Banerjee, S. 1995 A numerical study of free-surface turbulence in channel flow. Phys. Fluids 7, 16491664.
20. Perry, A. & Chong, M. S. 1987 A description of eddying motions and flow patterns using critical point concepts. Annu. Rev. Fluid Mech. 9, 125148.
21. Pinarbasi, A., Ozalp, C. & Duman, S. 2005 Influence of variable thermal conductivity and viscosity for nonisothermal fluid flow. Phys. Fluids 17, 038109.
22. Popiel, C. O. & Wojtkowiak, J. 1998 Simple formulas for thermophysical properties of liquid water for heat transfer calculations (from to ). Heat Transfer Engng 19 (3), 87101.
23. Sameen, A. & Govindarajan, R. 2007 The effect of wall heating on instability of channel flow. J. Fluid Mech. 577, 417442.
24. Sewall, E. A. & Tafti, D. K. 2008 A time-accurate variable property algorithm for calculating flows with large temperature variations. Comput. Fluids 37, 5163.
25. Shin, S. Y., Cho, Y. I., Gringrich, W. K. & Shyy, W. 1993 Numerical study of laminar heat transfer with temperature dependent fluid viscosity in a 2:1 rectangular duct. Intl J. Heat Mass Transfer 36, 43654373.
26. Shishkina, O. & Thess, A. 2009 Mean temperature profiles in turbulent Rayleigh–Bénard convection of water. J. Fluid Mech. 633, 449460.
27. Sieder, E. N. & Tate, G. E. 1936 Heat transfer and pressure drop of liquids in tubes. Ind. Engng Chem. 28, 14291435.
28. Soldati, A. 2005 Particles turbulence interactions in boundary layers. Z. Angew. Math. Mech. 85, 683699.
29. Soldati, A. & Banerjee, S. 1998 Turbulence modification by large-scale organized electrohydrodynamic flows. Phys. Fluids 10, 17431756.
30. Stevens, R. J. A. M., Verzicco, R. & Lohse, D. 2010 Radial boundary layer structure and Nusselt number in Rayleigh–Bénard convection. J. Fluid Mech. 643, 495507.
31. Verzicco, R. & Sreenivasan, K. R. 2008 A comparison of turbulent thermal convection between conditions of constant temperature and constant heat flux. J. Fluid Mech. 595, 203219.
32. Weast, R. C. 1988 CRC Handbook of Chemistry and Physics. CRC Press.
33. Willmarth, W. W. & Lu, S. S. 1972 Structure of the Reynolds stress near the wall. J. Fluid Mech. 55, 6592.
34. Yu, W., France, D. M., Timofeeva, E. V., Singh, D. & Routbort, J. L. 2010 Thermophysical property-related comparison criteria for nanofluid heat transfer enhancement in turbulent flow. Appl. Phys. Lett. 96, 213109.
35. Zonta, F. 2010 Turbulence and thermal stratification in inhomogeneous shear flows. PhD thesis, University of Udine, Udine (Italy).
36. Zonta, F., Marchioli, C. & Soldati, A. 2008 Direct numerical simulation of turbulent heat transfer modulation in micro-dispersed channel flow. Acta Mech. 195, 305326.
37. Zonta, F., Onorato, M. & Soldati, A. 2012 Turbulence and internal waves in stably-stratified channel flows with temperature-dependent fluid properties. J. Fluid Mech. 697, 175203.
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Modulation of turbulence in forced convection by temperature-dependent viscosity

  • Francesco Zonta (a1), Cristian Marchioli (a1) and Alfredo Soldati (a1)

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