PREDICTION OF TURBULENT HEAT TRANSFER IN THE ENTRANCE OF AN ARRAY OF HEATED BLOCKS USING LOW-REYNOLDS-NUMBER κ-ε MODEL

1995 ◽  
Vol 28 (3) ◽  
pp. 263-277 ◽  
Author(s):  
Y. Asako ◽  
Mohammad Faghri
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Low Reynolds Number ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Low Reynolds

scholarly journals Computation of Turbulent Heat Transfer on the Walls of a 180 Degree Turn Channel With a Low Reynolds Number Reynolds Stress Model

2002 ◽  
Author(s):  
D. L. Rigby ◽  
A. A. Ameri ◽  
E. Steinthorsson
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Reynolds Stress ◽  
Low Reynolds Number ◽  
Reynolds Stress Model ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Stress Model ◽  
Generalized Gradient ◽  
Low Reynolds

The Low Reynolds number version of the Stress-ω model and the two equation k-ω model of Wilcox were used for the calculation of turbulent heat transfer in a 180 degree turn simulating an internal coolant passage. The Stress-ω model was chosen for its robustness. The turbulent thermal fluxes were calculated by modifying and using the Generalized Gradient Diffusion Hypothesis. The results showed that using this Reynolds Stress model allowed better prediction of heat transfer compared to the k-ω two equation model. This improvement however required a finer grid and commensurately more CPU time.

scholarly journals Rayeilgh number effect on the turbulent heat transfer within a parallelepiped cavity

2011 ◽  
Vol 15 (suppl. 2) ◽  
pp. 341-356 ◽  
Author(s):  
Mohamed Aksouh ◽  
Amina Mataoui ◽  
Nassim Seghouani ◽  
Zoubida Haddad
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Nusselt Number ◽  
Natural Convection ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Turbulent Heat Transfer ◽  
Turbulent Heat ◽  
Practical Applications ◽  
Low Reynolds

This purpose is about a three dimensional study of natural convection within cavities. This problem is receiving more and more research interest due to its practical applications in the engineering and the astrophysical research The turbulent natural convection of air in an enclosed tall cavity with high aspect ratio (AR=H/W=28.6) is examined numerically. Two cases of differential temperature have been considered between the lateral cavity plates corresponding, respectively, to the low and high Rayleigh numbers: Ra=8.6?105 and Ra=1.43?106 [1]. For these two cases, the flow is characterized by a turbulent low Reynolds number. This led us to improve the flow characteristics using two one point closure low-Reynolds number turbulence models: RNG k-e model and SST k-w model, derived from standard k-e model and standard k-w model, respectively. Both turbulence models have provided an excellent agreement with the experimental data. In order to choose the best model, the average Nusselt number is compared to the experiment and other numerical results. The vorticity components surfaces confirm that the flow can be considered two-dimensional with stretched vortex in the cavity core. Finally, a correlation between Nusselt number and Rayleigh number is obtained to predict the heat transfer characteristics.

Prediction of Heat Transfer in Turbulent Channel Flow With Spanwise Rotation and Suction/Blowing Through Opposite Walls

2009 ◽  
Author(s):  
B. A. Younis ◽  
B. Weigand ◽  
A. Laqua
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Low Reynolds Number ◽  
Heat Fluxes ◽  
Function Approach ◽  
Wall Region ◽  
Turbulent Heat ◽  
Reynolds Stresses ◽  
Wall Function ◽  
Low Reynolds

This paper is concerned with the prediction of heat transfer rates in fully-developed turbulent flows in straight channels with mass transfer by suction and blowing through opposite walls, and with rotation about the spanwise axis. The predictions are based on the solution of the Reynolds-averaged forms of the governing equations using a second-order accurate finite-volume formulation. The effects of turbulence on momentum transport were accounted for by using turbulence closures based on the solution of modeled differential transport equations for the Reynolds stresses. A number of alternative models were assessed. These included a high turbulence Reynolds-number model in which the computationally-efficient ‘wall-function’ approach was used to bridge the near-wall region. As the effects of stabilizing system rotation can cause flow relaminarization, the wall-function approach becomes unreliable and integration must be carried out through the viscous sub-layer, directly to the walls. The suitability of three alternative low Reynolds-number models was assessed in these flows. Experimental data from flows in stationary channels with Reynolds numbers spanning the range of laminar, transitional and turbulent regimes were also used in this assessment. Excellent predictions of the wall skin-friction coefficient across the entire range were obtained with a low Reynolds-number model in which the effects of a rigid wall on the fluctuating pressure field in its vicinity were accounted for by a method which incorporates the gradients of the turbulence length scale and the invariants of turbulence anisotropy. For the cases of heated flows, two very different models for the turbulent heat fluxes were examined: one involved the solution of a differential transport equation for each component of the heat-flux tensor and another in which the heat fluxes were obtained from an explicit algebraic model derived from tensor representation theory. It was found that the two models yielded results that were essentially similar and in close agreement with results from recent Direct Numerical Simulations.

HEAT TRANSFER OF IMPINGING JET AT LOW REYNOLDS NUMBER

2018 ◽  
Author(s):  
Vadim V. Lemanov ◽  
Viktor I. Terekhov ◽  
Vladimir V. Terekhov
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Low Reynolds Number ◽  
Impinging Jet ◽  
Low Reynolds

Numerical Simulation of Turbine Blade Boundary Layer and Heat Transfer and Assessment of Turbulence Models

1997 ◽  
Vol 119 (4) ◽  
pp. 794-801 ◽  
Author(s):  
J. Luo ◽  
B. Lakshminarayana
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Reynolds Number ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Navier Stokes ◽  
Bypass Transition ◽  
Boundary Layer Development ◽  
Low Reynolds ◽  
Layer Development

The boundary layer development and convective heat transfer on transonic turbine nozzle vanes are investigated using a compressible Navier–Stokes code with three low-Reynolds-number k–ε models. The mean-flow and turbulence transport equations are integrated by a four-stage Runge–Kutta scheme. Numerical predictions are compared with the experimental data acquired at Allison Engine Company. An assessment of the performance of various turbulence models is carried out. The two modes of transition, bypass transition and separation-induced transition, are studied comparatively. Effects of blade surface pressure gradients, free-stream turbulence level, and Reynolds number on the blade boundary layer development, particularly transition onset, are examined. Predictions from a parabolic boundary layer code are included for comparison with those from the elliptic Navier–Stokes code. The present study indicates that the turbine external heat transfer, under real engine conditions, can be predicted well by the Navier–Stokes procedure with the low-Reynolds-number k–ε models employed.

Numerical Simulations of Resonant Heat Transfer Augmentation at Low Reynolds Numbers

2001 ◽  
Author(s):  
Miles Greiner ◽  
Paul F. Fischer ◽  
Henry Tufo
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Natural Frequency ◽  
Flow Rate ◽  
Low Reynolds Number ◽  
Reynolds Numbers ◽  
Spectral Element ◽  
Pumping Power ◽  
Number Systems ◽  
Low Reynolds

Abstract The effect of flow rate modulation on low Reynolds number heat transfer enhancement in a transversely grooved passage was numerically simulated using a two-dimensional spectral element technique. Simulations were performed at subcritical Reynolds numbers of Rem = 133 and 267, with 20% and 40% flow rate oscillations. The net pumping power required to modulate the flow was minimized as the forcing frequency approached the predicted natural frequency. However, mixing and heat transfer levels both increased as the natural frequency was approached. Oscillatory forcing in a grooved passage requires two orders of magnitude less pumping power than flat passage systems for the same heat transfer level. Hydrodynamic resonance appears to be an effective method of increasing heat transfer in low Reynolds number systems where pumping power is at a premium, such as micro heat transfer applications.

Numerical Study of Deteriorated Convection Heat Transfer of Supercritical Fluid Flowing Through Vertical Mini Tube at Relatively Low Reynolds Numbers

2018 ◽  
Author(s):  
Chen-Ru Zhao ◽  
Zhen Zhang ◽  
Qian-Feng Liu ◽  
Han-Liang Bo ◽  
Pei-Xue Jiang
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Reynolds Number ◽  
Low Reynolds Number ◽  
Convection Heat Transfer ◽  
Turbulence Models ◽  
Convection Heat ◽  
Flow Acceleration ◽  
Heat Transfer Deterioration ◽  
Low Reynolds

Numerical investigations are performed on the convection heat transfer of supercritical pressure fluid flowing through vertical mini tube with inner diameter of 0.27 mm and inlet Reynolds number of 1900 under various heat fluxes conditions using low Reynolds number k-ε turbulence models due to LB (Lam and Bremhorst), LS (Launder and Sharma) and V2F (v2-f). The predictions are compared with the corresponding experimentally measured values. The prediction ability of various low Reynolds number k-ε turbulence models under deteriorated heat transfer conditions induced by combinations of buoyancy and flow acceleration effects are evaluated. Results show that all the three models give fairly good predictions of local wall temperature variations in conditions with relatively high inlet Reynolds number. For cases with relatively low inlet Reynolds number, V2F model is able to capture the general trends of deteriorated heat transfer when the heat flux is relatively low. However, the LS and V2F models exaggerate the flow acceleration effect when the heat flux increases, while the LB model produces qualitative predictions, but further improvements are still needed for quantitative prediction. Based on the detailed flow and heat transfer information generated by simulation, a better understanding of the mechanism of heat transfer deterioration is obtained. Results show that the redistribution of flow field induced by the buoyancy and flow acceleration effects are main factors leading to the heat transfer deterioration.

Sign in / Sign up

Export Citation Format

Share Document