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Employing the reverse engineering technology, the three-dimension LED heat sink entity was rebuilt and the heat transfer characteristics of LED heat sink were analyzed by CFD numerical simulation and experimental measurement.
Numerical Simulation.
In numerical simulation, the grid of LED heat sink was built by using Gambit software as shown in Fig. 1(b).
The test grid number was from 1,237,854 to 2,453,362 in the simulation.
In addition, according to the graph of relation, the simulation resultsget agreement with the experimental measuremental result, proving that the numerical simulation can be used to simulate the heat transfer characteristics of LED heat sink accurately.

For all simulations performed, Reynolds and Prandtl numbers are kept fixed (ReH = 100, Pr = 0.71).
For this specific study, 46 simulations are performed.
Numeric Modeling The CFD used is FLUENT® with Gaus-Seidel based on pressure as the solver for the system of equations.
All simulations are performed using a computer with an Intel i5 processor clocked at 3.10 GHz and 8 GB RAM.
The processing time of each simulation is approximately 180s (3 min).

Alansari1,d 1Mechanical Engineering Department, Faculty of Engineering, University of Kufa, Iraq 2Chemical Engineering Department, Faculty of Engineering, University of Kufa, Iraq 3Mechanical Engineering Department, Faculty of Engineering, University of Baghdad, Iraq anasra.hamood@uokufa.edu.iq, bAlia.alshammary@uokufa.edu.iq cdrihsan@uobaghdad.edu.iq, dLuays.alansari@uokufa.edu.iq Keywords: Clinker, Cooling Process, Forced Convection, Porosity, CFD.
They studied the effects of air clinker height ratio and porosity of clinker using CFD modeling by (FLUENT 6.3.26).
Hesham, Variation of Feed Chemical Composition and Its Effect on Clinker Formation–Simulation Process.
Xie, Optimization and simulation of sinter cooling process, CIESC Journal, 62 (11), 3081-3087, (2011)

X.P Lu [3] uses CFD method to simulate indoor temperature field of air -conditioned room in which the position of split air conditioner is different.
Numerical Simulation Physical Model .This study is about a fourth floor office in Hengyang.
In the simulation, some assumptions were made to the window gap for the restrictions of mesh size and calculation, which might bring a certain impact on the simulation results.
Thus, some work can be done to improve the simulation in the following time.
Lei Jin for assisting numerical simulation.

It is robust and simple to program in comparison to Computational Fluid Dynamics (CFD) approaches.
Water is used as a fluid in the simulation so the particles are assigned an initial density of 1000 kg/m3.
However, in the simulation the tank is not emptied completely after about 5 s (see Fig. 3.f).
To match the numerical simulation with the analytical solution Eq. (11) was used with Cv=0.97 and Cd=0.65.
A good agreement is achieved between the numerical simulation and the analytical solution.

Furthermore, filling of a kind of panel was simulated, and the simulation results were analyzed.
（1） and According to consulting data and the knowledge of cfd obtained the best filling velocity of 200×150×10 plate casting is , followed .
Then it verified by the numerical simulation.
That Fills Process Numerical Simulation of The Present Situation and Development of Technology[J].
[10] GuoFaMi,xiangyuliu andkuangfeiwang development and application of numerical simulation for the mold filling process of casting [J].Journal of Henan Polytechnic University 2007, 26(3): 334-339.

COMPUTATIONAL FLUID DYNAMICS SIMULATION Parameters assigned for the FLUENT simulation.
The CFD analysis has proven precise for the liquid flow pressure variation inside the gear pump with the parameters assigned in GAMBIT and ANSYS FLUENT.

To reduce energy consumption, numerical simulations of combustion and decomposition processes in a precalciner were carried out with two types of locations of jetting coal pipes.
Today the CFD method[3–6] has been used widely in precalciner design and optimization.
In this paper, the processes of combustion and decomposition in a precalciner with two types of locations of jetting coal pipes were studied by numerical simulation.
Numerical simulation study on gas-particles two-phase flow in pre-calciner [J].
Numerical simulation of gas-solid flow in slc-s precalciner by adding a raw meal inlet [J].J Chin Ceram Soc, 2007, 35(10): 1382-1386

FIDAP has been used due to the ability of rigorous computational fluid dynamics (CFD) code.
SIMULATION METHODS 2.1 Implementation of the rheological model in FIDAP.
The FE model use CFD code to obtain independent numerical results for the pseudoplastic and the rheopectic behaviour of bone cements.
Simulation was performed for a period of twelve minutes using the transient analysis option.
“A computational fluid dynamics simulation of PMMA cement flow upon insertion of a femoral stem into a bone cavity during a total hip prosthesis procedure”.

Later, a more complex code based on computational fluid dynamics applied to the simulation of fire development (Fire Dynamics Simulator - FDS) is used to allow a comparison between the numerical results obtained in either way, and to check to what extent some available experimental results concerning similar tunnels can be fitted.
Several models have been developed to simulate fire conditions in tunnels, ranging from simple analytical expressions to complex and computationally-demanding ``zone models'' and ``field models'', the latters based on computational fluid dynamics (CFD) [1].
Successively, a field model based on computational fluid dynamics - CFD applied to fire-development simulation - FDS is used (Pyrosim [5]).The use of CFAST is presented in some detail, as this code is based on the subdivision of a construction into compartments (but there are no compartments in a tunnel!).
A number of simulations were performed by means of CFAST for different values of the compartment length and for the same cross section.
Sharma: Numerical Simulation of Fire in a Tunnel: Comparative Study of CFAST and CFX Predictions, Tunnelling and Underground Space Technology, 2008, 23:160-170 [9] P.