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Research Papers: Forced Convection

Experimental Validation of a Computational Fluid Dynamics Methodology for Transitional Flow Heat Transfer Characteristics of a Steady Impinging Jet

[+] Author and Article Information
Sajad Alimohammadi

Department of Mechanical and
Manufacturing Engineering,
Trinity College Dublin,
Dublin, Ireland
e-mail: alimohas@tcd.ie

Darina B. Murray

Department of Mechanical and
Manufacturing Engineering,
Trinity College Dublin,
Dublin, Ireland
e-mail: dmurray@tcd.ie

Tim Persoons

Department of Mechanical and
Manufacturing Engineering,
Trinity College Dublin,
Dublin, Ireland
e-mail: tim.persoons@tcd.ie

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received January 29, 2014; final manuscript received June 3, 2014; published online June 27, 2014. Assoc. Editor: W. Q. Tao.

J. Heat Transfer 136(9), 091703 (Jun 27, 2014) (9 pages) Paper No: HT-14-1049; doi: 10.1115/1.4027840 History: Received January 29, 2014; Revised June 03, 2014

This paper presents a computational fluid dynamics (CFD) methodology to accurately predict the heat transfer characteristics of an unconfined steady impinging air jet in the transitional flow regime, impinging on a planar constant-temperature surface. The CFD methodology is validated using detailed experimental measurements of the local surface heat transfer coefficient. The numerical model employs a transitional turbulence model which captures the laminar–turbulent transition in the wall jet which precisely predicts the intensity and extent of the secondary peak in the radial Nusselt number distribution. The paper proposes a computationally low-cost turbulence model which yields the most accurate results for a wide range of operating and geometrical conditions. A detailed analysis of the effect of mesh grid size and properties, inflow conditions, turbulence model, and turbulent Prandtl number Prt is presented. The numerical uncertainty is quantified by the grid convergence index (GCI) method. In the range of Reynolds number 6000 ≤ Re ≤ 14,000 and nozzle-to-surface distance 1 ≤ H/D ≤ 6, the model is in excellent agreement with the experimental data. For the case of H/D = 1 and Re = 14,000, the maximum deviations are 5%, 3%, and 2% in terms of local, area-averaged and stagnation point Nusselt numbers, respectively. Experimental and numerical correlations are presented for the stagnation point Nusselt number.

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References

Figures

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Fig. 1

Computational domain and boundary conditions used in the simulation of the unconfined axisymmetric impinging jet

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Fig. 2

Schematic diagram of the experimental setup: (a) pipe nozzle, (b) mass flow meter, (c) pressure reducer valve, (d) instrumented isothermally heated plate, (e) embedded heat flux sensor, and (f) data acquisition unit and computer

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Fig. 3

Heat transfer coefficient at the stagnation point of a steady impinging jet plotted as Nu0/(Re0.5Pr0.4) as a function of nozzle-to-surface spacing H/D

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Fig. 6

Radial distribution of (a) normalized turbulence kinetic energy and (b) radial velocity gradient (s−1) near the wall (at 0.01D) for different inlet velocity profiles (Re = 6000, H/D = 1)

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Fig. 5

Comparison of radial distribution of Nusselt number for different inlet velocity profiles to experimental data (Re = 6000, H/D = 1; error bars display exp. uncertainty)

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Fig. 4

(a) Radial distribution of Nusselt number for different mesh sizes, F1 to F5, listed in Table 1 (Re = 6000, H/D = 1) and (b) local distribution of numerical uncertainty (GCI(%)) as error band on the selected mesh size for simulation (F4)

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Fig. 7

Comparison of radial distribution of Nusselt number for different (a) inlet turbulence intensities (%), (b) turbulence models, and (c) turbulent Prandtl numbers to experimental data (Re = 6000, H/D = 1; Exp. uncertainty = 6%)

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Fig. 8

Comparison of radial distribution of Nusselt number for different Reynolds numbers to experimental data (H/D = 1; Re = 6000, 10,000, and 14,000; error bars display exp. uncertainty)

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Fig. 9

Comparison of radial distribution of Nusselt number for different nozzle-to-surface distances to experimental data: (a) H/D = 2, (b) H/D = 3, (c) H/D = 4, and (d) H/D = 6 (Re = 6000, 10,000, and 14,000; error bars display exp. uncertainty)

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