الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
Nanofluid jet impingement of cooling is commonly used in many industrial applications due to its capability to dissipate large amounts of heat fluxes from surfaces. In the present study, heat transfer enhancement and fluid flow characteristics of multiple and single jet impingement were investigated experimentally and numerically using water and Al2O3-water nanofluid as coolants. The effects of changing holes arrangement, nanofluid concentration, and Jet-to-Jet spacing and jet-to-target plate distance on heat transfer were studied. The dimensionless jet-to-target distance (H/Djet) varied from 5 to 40, dimensionless jet-to-jet spacing (xn/Djet) varied from 3 to 9. Study was carried out at jet velocity range from 1.0 to 6.0 m/s corresponding to jet Reynolds number from 2440 to 14640 at constant heat flux of target plate. Five jet plates were employed; single, double jet, five jets, inline array and staggered array. The two step method is employed to prepare Al2O3-water nanofluid using nanoparticle size of 20 nm. Three nanofluid concentrations by volume (φ) were tested; 5 %, 8% and 10% and the results compared with that of water. A 3-D numerical model is adopted to simulate multiple and single nanofluid jet impingement system. Ansys CFX commercial software was employed to simulate heat transfer and fluid flow of the jet impingement cooling system. Free surface model is used as multiphase flow modeling in Ansys CFX solver. Geometry is generated by Solidworks R 16 software and modified in Ansys design modeler. Meshing is designed by Ansys meshing and grid independence study is created. Standard κ-ε, RNG κ-ε, Standard κ-ω and SST κ-ω turbulence model were checked to find out the appropriate for the present study. A validation test was conducted by comparing the results of the numerical model with the published results and the experimental results. Results are obtained in terms of average and local surface temperature, average transfer coefficients, average Nusselt numbers and pumping power. The velocity, pressure, volume fraction and surface temperature contours are presented.
The experimental results show that, the best heat transfer enhancement is recorded at H/Djet=20. Using nanofluid instead of pure water can enhance heat transfer more than water at the same condition where, using Al2O3-water with 10% concentration at jet velocity Vjet=6 m/s enhance average Nusselt numbers by 21%,34%, 48%, 50% and 57 % for single jet, double jets, five jets, inline and staggered arrays respectively. The average heat transfer coefficients increased by 100%, 150%, 230% and 275 % for double jet, five jets, inline and staggered arrays respectively compared with single jet at 10 % concentration and 6 m/s jet velocity. The best average Nusselt number among all jets plates is obtained by employing staggered jets plate arrays. The system performance indicator decreased by increasing the nanofluid concentration and the best system performance obtained at the nanofluid concentration φ = 5% nanofluid concentration. Empirical correlation equations are created to calculate average Nusselt number for each jet configuration.
The numerical results show that, from all the checked models, the standard κ-ε turbulence model gives better agreement with the experimental results with 7.4 % maximum deviation for inline jet configuration at jet Reynolds number Rejet = 23,000, φ=5% and H/Djet=20. For single jet, at Vjet=4 m/s and H/Djet=5, the predicted maximum velocity decay in the developing region is given by -1.11 while the linear decay starts at dimensionless velocity location-to-jet diameter x/Djet=4.8 and ends at x/Djet=11. The best heat transfer enhancement is obtained at Xn/Djet=7. The numerical results for all jet configurations show a good agreement of the κ-ε model with the experimental results particularly at low Reynolds number.