A CFD four parameter heat transfer turbulence model for engineering applications in heavy liquid metals

Manservisi, Sandro; Menghini, F.

doi:10.1016/j.ijheatmasstransfer.2013.10.017

Cited by 76 publications

(70 citation statements)

References 31 publications

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“…The results obtained with the k-ε-k θ -ε θ turbulence model, in terms of the Nusselt number value for the evaluation of the global heat transfer, are more accurate than the ones obtained with the SED model when compared with the reference correlations for liquid metals [7,8,9]. The k-ε model better matches experimental results but shows poor numerical convergence due to the strong coupling of ε-ε θ with k-k θ on wall boundaries.…”

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 75%

“…The two eddy diffusivities are calculated as a function of the turbulent kinetic energy and of two characteristic time scales: τ lu for the dynamical and τ lθ for the thermal turbulence. These time scales have to be defined appropriately in the turbulence model, for details one can see [3,4,5,7].…”

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 99%

“…By defining the characteristic time τ u = k/ε one can model the local dynamical time τ lu in many ways [7,8,9]. For the thermal turbulence the two transport equations are…”

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 99%

“…For details on the time scales and functions to be used in the definition of the eddy viscosity and diffusivity one can see [5,7,8,9,10,11].…”

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 99%

“…We briefly recall the RANS equations and the first formulation of a four parameter k-ε-k θ -ε θ , then we derive the k-ω formulation already validated by the authors [6,7,8,9]. Finally the new logarithmic k-Ω-k θ -Ω θ model is presented.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Numerical Validation of a Four Parameter Logarithmic Turbulence Model

Cerroni¹,

Vià²,

Manservisi³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. Computational Fluid Dynamics codes are used in many industrial applications in order to evaluate interesting physical quantities, such as the heat transfer in turbulent flows. Commercial CFD codes use only turbulence models with an imposed constant turbulent Prandtl number P r t , which can give accurate results only for simulations when a strong similarity between the velocity field and the temperature field can be assumed. For fluids with a low Prandtl number, as for heavy liquid metals, a constant turbulent Prandtl number leads to an overestimation of the heat transfer, so experimental results and Direct Numerical Simulation cannot be reproduced. In this work we propose a new k-Ω-k θ -Ω θ turbulence model as an improvement of the k-ω-k θ -ω θ turbulence model, already validated by the authors, where Ω and Ω θ are calculated as the natural logarithm of the variables ω and ω θ . With this reformulation of the previous turbulence model we obtain some important advantages in numerical stability and robustness of the code. Results for the simulations of fully developed turbulent flows in two and three dimensional geometries are reported and compared with experimental correlations and DNS data, when available.

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Section: Transport Equations and Turbulence Modelsmentioning

confidence: 75%

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 99%

“…By defining the characteristic time τ u = k/ε one can model the local dynamical time τ lu in many ways [7,8,9]. For the thermal turbulence the two transport equations are…”

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 99%

“…For details on the time scales and functions to be used in the definition of the eddy viscosity and diffusivity one can see [5,7,8,9,10,11].…”

Section: Transport Equations and Turbulence Modelsmentioning

confidence: 99%