27 Solid Work is a software which is used for solid modeling computer aided design (CAD) and computer aided engineering (CAE). Through this software we can easily sketch 2D structure and by extruding feature we can get it 3D model very easily. From this software we can design separate parts according to our own dimensions and assemble those parts together easily. And also from this software we can designed mechanical system as well as we can simulate through this software. But in this research we have used different kind of software to simulate the solid work design.

28 From sketch option we can create different kind of shapes like rectangle, circle, lines, curves and etc. And also from this we can insert smart dimensions, so that we could able to make a design according to our own dimensions. Mirror option also could be used through this sketch option.
29 Through the feature option we can convert 2D model to 3D model easily by using extrude option. And if we want to make a hole or cut in that 3D object we could use extrude cut option in this feature panel. If we want some smooth edges, some other features like fillet, shell and draft could be used. To create airfoil, curve feature has used in the designing stage.
30 We can flow simulate through the solid work Flow Simulation option but it is not much accurate as Open Foam and other simulation software. So throughout this experiment we didn’t use that option in solid work.
31 We can assembly parts through this software. We can sketch different parts of model in different pages and after completing the parts, it can be assembled together and complete with one solid 3D model.
32 We can use different kind of constraints while drawing the sketch such as horizontal, perpendicular, vertical, coincident and etc.
33 OpenFOAM is a structure for creating application executables that utilization bundled usefulness contained inside an accumulation of roughly 100 C+ libraries. OpenFOAM is dispatched with around 250 pre-incorporated applications that fall with two classifications: solvers, that are each intended to take care of a speci?c issue in ?uid (or continuum) mechanics; and utilities, that are intended to perform assignments that include information control. The solvers in OpenFOAM cover an extensive variety of issues in fluid dynamics. Some of them are compressible, multiphase, incompressible, heat transfer etc. The users in OpenFOAM can expand the accumulation of solvers, utilities and libraries in OpenFOAM, utilizing some pre-essential learning of the hidden strategy, physics and programming procedures included. The pre-processing and post-processing conditions are made associated with OpenFOAM. The interface to the pre-and post-preparing are themselves OpenFOAM utilities, subsequently guaranteeing steady information dealing with over all conditions. The post handling is went with ParaView programming.
34 There are some limited numbers of CFD simulations done so far using dynamic mesh in openFOAM. These simulation projects are done with pimpleDyMFoam solver. For example: the simulation of the wind turbines and propellers. Therefore we have proceeded with our CFD project on Bell 412 main rotor with the very close studies of the simulations of wind turbine and propeller. Most of the techniques and ideas are drawn from these existing simulations and modified appropriately for our CFD project.

35 Computational Fluid Dynamic (CFD) is one of the main tool to perform in Researches and the industrial applications. From this CFD analysis we can predict, how the system component are working, how the fluid flow behavior and it provides a qualitative and quantitative prediction of fluid flows by means of following methods,
Numerical Method
Software tools
Mathematical Modeling
So that we can implement our design and make necessary development in design. And it has been using in industry for many years. Some of basic applications are given bellow;
Flow and heat transfer in industrial processes
Aerodynamics of ground vehicles, aircraft, missiles.
Film coating, thermoforming in material processing applications.
Flow and heat transfer in propulsion and power generation systems.
Ventilation, heating, and cooling flows in buildings.
Heat transfer for electronics packaging applications.
36 CFD is the latest branch of engineering In CFD it used numerical method and the algorithm method to solve and analyze the problem in fluid flows. This analysis have done through the basic governing equation in CFD which are in partial differential form. This equation will convert in to computer programs by using high level computer languages. Existing commercial CFD codes are capable of simulating a very wide variety of physical processes besides fluid flow. This CFD describe the pressure, temperature, density and the velocity of the moving fluid, which given in the Naiver-stoke equations. In Naiver-Stock equation it contain energy equation, momentum equation and the continuity equation which are given bellow.

Continuity Equation:
??/?t+ ?( ?u/?x+ ?v/?y+ ?w/?z )=0 (1)
Momentum Equations;
For X direction;
??u/?t+ (?(?uu))/?x+ (?(?uv))/?y+ (?(?uw))/?z= -?p/?x+ ?((?^2 u)/??x?^2 + (?^2 u)/??y?^2 + (?^2 u)/??z?^2 ) (2)

For Y direction;
??u/?t+ (?(?uu))/?x+ (?(?uv))/?y+ (?(?uw))/?z= -?p/?y+ ?((?^2 v)/??x?^2 + (?^2 v)/??y?^2 + (?^2 v)/??z?^2 ) (3)
For z direction;
??u/?t+ (?(?uu))/?x+ (?(?uv))/?y+ (?(?uw))/?z= -?p/?z+ ?((?^2 w)/??x?^2 + (?^2 w)/??y?^2 + (?^2 w)/??z?^2 ) (4)

Energy Equation;
??E/?t+ (?(?uE))/?x+ (?(?vE))/?y+ (?(?wE))/?z= -?pu/?x-?pv/?y- ?pw/?z+S (5)
x, y and z – three different directions component
? – Density of air
u, v and w – Velocity component in different direction.
37 From this CFD analysis, it can have great control over the physical process and provides the ability to isolate specific phenomena for study. And from experiment we could only have data in limited number of locations in the system but through the CFD simulation it can analysis data in large number of locations and give comprehensive set of flow parameters for examination. Experimental process may get much expensive compare to the CFD process and the cost of CFD process may get reduce when the computers get more powerful. The simulation could be executed in short period of time as well as we could simulate in real conditions. This are the main advantage of computational fluid dynamic.
38 When we discuss about the limitation of CFD, the CFD solutions relay in physical model of real world processes such as compressibility, chemistry, turbulence and many more. Through the CFD it can get much accurate data as the physical model on which they are based on. When the computer solve the equation it invariably introduce numerical errors which include round-off errors and due to the approximation in numerical mode it will give truncation errors. The accuracy of the solution mainly depend on the initial boundary conditions given in to the numerical mode.
39 In CFD it divided in to three main processing which are pre-processing, solving and post-processing. In pre-processing, it need to be created Mesh for the solid work model. For that software like Open Foam and Gambit could be used according to our own boundary conditions.

40 To solve CFD problems it consist of three main components which are geometry and grid generation, setting up a physical model and post processing the compute data. In the turbulence it results in increasing energy dissipation, mixing, heat transfer and the drag. The way geometry and the grid are generated and the set problem is computed are very well known. Precise theories are available. But it is not true for setting up a physical model for turbulence flow. There for it need to create the ideal model with the minimum amount of complexity. The complexity of the model will increase with the amount of information required about the flow field. The key elements of turbulence are time dependent and the three dimensional. 17
41 Turbulence models can be categorized in to several different approaches which are by solving the Reynolds-averaged Navier-Stokes equations with suitable models for turbulent quantities or by computing them directly.
Reynolds-Averaged Navier-Stokes (RANS) Models
Eddy Viscosity Model (EVM)
Non-linear Eddy Viscosity Model (NLEVM)
Differential Stress Model (DSM)
Detached eddy simulation (DES)
Large-eddy simulation (LES)
Direct numerical simulation (DNS)
Reynolds stress transport models
Direct numerical simulations

42 This method is the mainly use method in Engineering industry. This can be categorized according to the wall function, number of variables and their types. So we mainly focus on following models in RANS.
K-Epsilon(?) Model
K-Omega(?) Model
43 Here this k-Epsilon model further divided in to two types of models, which are standard K-Epsilon model (SK-?) and the Realizable K-Epsilon model (RNGK-?). And also this K-omega model also divided in to two models which are standard K-omega model (SK-?) and the shear stress transport K-Omega model (SSTK-?).
44 This equation solves a modelled transport equation for kinematic eddy turbulent viscosity. It easy to resolve near the wall. From this model it shows good results for boundary layer subjected to adverse pressure gradient in especially wall bounded flows involve in aerospace applications. This could be used for the supersonic and transonic applications. This model is not calibrated for the general industrial flows. This model is very effective in low Reynolds numbers. Minimum boundary layer resolution of 10-15 cells should be there to resolve the equation. The formulation provide wall shear stress and heat transfer coefficient. This model cannot rely on the turbulence isotropic calculations. 18
45 This model mainly focus on the affect the turbulent kinetic energy. In this model it take the kinetic viscosity is isotropic as an assumption, or the ratio between rater of deformation and the Reynolds’ number is same in all directions. This model used commonly in industrial applications rather than the other two models. This model gives reasonably accurate results. Under different pressure gradients it gives the equilibrium boundary layers and free shear flows. This usually use for free shear layer flow with small pressure gradient. This model poorly perform in strong separations, large pressure gradients, unconfined flows, curved boundary layers, rotating flows and flows in non-circular ducts. Among the two type of this model (RNG) K-? model perform better than the SK-? model.
For k and ? it use two transport equations for turbulent length and the viscosity.
Equation for turbulent length;
l=k^(3/2)/? (6)
Equation for turbulent viscosity;
v_t=c_? k^(1/2) l=c_? k^2/? (7)

Turbulent kinetic energy;
?/?t (?k)+ ?y/(?x_i ) (?ku_i )= ?y/(?x_i )(?+?_t/?_k ) ?k/(?x_i )+P_k+P_d+??+Y_M+S_k (8)

Dissipation ?;
?y/?x (??)+ ?y/(?x_i ) (??u_i )= ?/(?x_j )(?+?_t/?_? ) ??/(?x_j )+C_1? ?/k (P_k+?C_3? P?_b )-C_2? ? ?^2/k+S_k (9)

C1? = 1.44, C2? = 1.92, C3? = 0.09, ?k = 1.0, ?? = 1.3

2.6.3 K-OMEGA (?) MODEL
46 It is two equation model which means it use two transport equations to represent the turbulent properties of the flow. This also a common equation model. This can be integrated to the wall without using the wall functions. From this equations, it accounts history effects such as diffusion and convection of turbulence energy. Here kinetic energy (k) is one of variable. It determines the energy in turbulence. The other variable is dissipation (?), it determine the scale of turbulence.
For kinematic eddy viscosity;
v_t=(a_1 k)/(max?(a,?,?SF?_2)) (10)
Turbulence kinetic energy;
?y/?x+U_j ?k/(?x_j )=P_k-?^* k?+?/(?x_j )(v+?_k+v_T ) ?k/(?x_j ) (11)

Specific dissipation rate;
??/?t+U_j ??/(?x_j )=?S^2-??^2+?/(?x_j ) (v+?_k v_T ) ??/(?x_j )+2(1-F_1)?_(?^2 ) 1/? ?k/(?x_j ) ??/(?x_j ) (12)