A Logarithmic Turbulent Heat Transfer Model in Applications with Liquid Metals for Pr = 0.01–0.025
Source abstract
Abstract
The study of turbulent heat transfer in liquid metal flows has gained interest because of applications in several industrial fields. The common assumption of similarity between the dynamical and thermal turbulence, namely, the Reynolds analogy, has been proven to be invalid for these fluids. Many methods have been proposed in order to overcome the difficulties encountered in a proper definition of the turbulent heat flux, such as global or local correlations for the turbulent Prandtl number and four parameter turbulence models. In this work we assess a four parameter logarithmic turbulence model for liquid metals based on the Reynolds Averaged Navier-Stokes (RAN) approach. Several simulation results considering fluids with P r = 0.01 and P r = 0.025 are reported in order to show the validity of this approach. The Kays turbulence model is also assessed and compared with integral heat transfer correlations for a wide range of Peclet numbers.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Fluid Dynamics and Turbulent Flows · Heat Transfer Mechanisms · Particle Dynamics in Fluid Flows
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
SuperComputing Applications and Innovation Department—CINECA, 40033 Bologna, Italy
DIN, Montecuccolino Laboratory, University of Bologna, 40136 Bologna, Italy
References (36)
Show source-provided references
1. Challenges in low-Prandtl number heat transfer simulation and modeling10.1016/j.nucengdes.2012.09.039 ↗
2. Numerical analysis of a solar tower receiver tube operated with liquid metals10.1016/j.ijthermalsci.2016.02.002 ↗
3. Fazio, C. (2015). Handbook on Lead-Bismuth Eutectic Alloy and Lead Properties, Materials Compatibility, Thermal-hydraulics and Technologies, OECD.
4. Investigation on turbulent heat transfer to lead–bismuth eutectic flows in circular tubes for nuclear applications10.1016/j.nucengdes.2005.09.006 ↗
5. Assessment of RANS and improved near-wall modeling for forced convection at low Prandtl numbers based on LES up to Reτ = 200010.1016/j.ijheatmasstransfer.2014.03.080 ↗
6. Direct and large eddy simulation of turbulent heat transfer at very low Prandtl number: Application to lead-bismuth flows10.1016/j.nucengdes.2011.07.010 ↗
7. Assessment and calibration of an algebraic turbulent heat flux model for low-Prandtl fluids10.1016/j.ijheatmasstransfer.2014.08.018 ↗
8. A CFD four parameter heat transfer turbulence model for engineering applications in heavy liquid metals10.1016/j.ijheatmasstransfer.2013.10.017 ↗
9. DNS of turbulent heat transfer in channel flow with respect to Reynolds and Prandtl number effects10.1016/S0142-727X(99)00014-4 ↗
10. DNS of turbulent channel flow with conjugate heat transfer at Prandtl number 0.0110.1016/j.nucengdes.2012.08.008 ↗
11. Reynolds number effects on the Reynolds-stress budgets in turbulent channels10.1063/1.3005862 ↗
12. Effect of the computational domain on direct simulations of turbulent channels up to Reτ = 420010.1063/1.4862918 ↗
13. Turbulent Prandtl number. Where are we?10.1115/1.2911398 ↗
14. A low Reynolds number two-equation kt-et model to predict thermal field10.1016/S0017-9310(98)00382-2 ↗
15. Towards the development of a Reynolds-averaged algebraic turbulent scalar-flux model10.1016/S0142-727X(00)00062-X ↗
16. A new turbulence model for predicting fluid flow and heat transfer in separating and reattaching flows I. Flow field calculations10.1016/0017-9310(94)90168-6 ↗
17. Development of a two equation heat transfer model based on direct simulations of turbulent flows with different Prandtl numbers10.1063/1.869124 ↗
18. A new turbulence model for predicting fluid flow and heat transfer in separating and reattaching flows II. Thermal field calculations10.1016/0017-9310(94)00252-Q ↗
19. Triangular rod bundle simulations of a CFD k-ε-kθ-εθ heat transfer turbulence model for heavy liquid metals10.1016/j.nucengdes.2014.03.022 ↗
20. CFD simulations in heavy liquid metal flows for square lattice bare rod bundle geometries with a four parameter heat transfer turbulence model10.1016/j.nucengdes.2015.10.006 ↗
21. Numerical validation of a k-ω-kθ-ωθ heat transfer turbulence model for heavy liquid metals10.1088/1742-6596/655/1/012046 ↗
22. A k-Ω-kθ-Ωθ four parameter logarithmic turbulence model for liquid metals10.1016/j.ijheatmasstransfer.2016.05.084 ↗
23. A unified finite element algorithm for two-equation models of turbulence10.1016/S0045-7930(97)00039-X ↗
24. Numerical simulation of forced and mixed convection turbulent liquid sodium flow over a vertical backward facing step with a four parameter turbulence model10.1016/j.ijheatmasstransfer.2019.01.129 ↗
25. Wilcox, D.C. (2006). Turbulence Modeling for CFD, DCW Industries, Inc.. [3rd ed.].
26. Hanjalić, K., and Launder, B. (2011). Modelling Turbulence in Engineering and the Environment, Cambridge University Press.10.1017/CBO9781139013314 ↗
27. Analysis of turbulent heat transfer under various thermal conditions with two-equation models
28. (2020, June 23). Official Repository for Multigrid Finite Element Code FEMuS, Github Link. Available online: https://github.com/FemusPlatform/femus.
29. Liquid metal heat transfer coefficients
30. Lyon, R. (1952). Liquid-Metals Handbook, Atomic Energy Comm.
31. Investigation of heat transfer in the turbulent flow of liquid metals in tubes
32. Stromquist, W.K. (1953). Effect of Wetting on Heat Transfer Characteristics of Liquid Metals, University of Tennessee.
33. Heat transfer to liquid metals: Specific features, methods of investigation, and main relationships
34. Heat transfer to molten lead–bismuth eutectic in turbulent pipe flow10.1115/1.4015579 ↗
35. Determination des coefficients de convection d’un alliage sodium-potassium dans un tube circulaire10.1016/0017-9310(65)90077-3 ↗
36. Temperature and eddy diffusivity profiles in NaK10.1016/0017-9310(73)90184-1 ↗