1. To communicate technical information using written and graphical techniques.

2. To analyse the results and discuss appropriately

3. To be able to critically assess the experiment.

4. To compare the results with numerical (or analytical results)

## Flow through pipe

A flow is said to be pipe flow if the flow is under full depth condition. In pipe flow there tre two different types of losses generally takes place:-

- Major losses:- They are due to viscous resistance through the wall. They have high magnitude and there occurrences are more. They are also known as constant velocity loss.
- Minor losses:- They are due to change in momentum of the fluid i.e. due to velocity either due to magnitude or direction or both. There occurrence is less as well as have less magnitude.

Ex. Sudden loss, exit loss, sudden contraction loss, entrance loss, bend loss and different pipe filling losses.

Apart from this concept of friction factor plays an important role in the pipe flow. There is proper formula derived for obtaining value of friction factor for laminar flow as well as for turbulent flow. Friction factor also depends upon the roughness as well as smoothness of the pipe surface or the body surface over which fluid has to flow. But there are some situations where it is not easy to determine the value of friction factor and it is important to know the value of friction factor because it directly tell us about the value of loss that encounter during the fluid flow. Therefore to overcome this situational problem Moody Diagram plays an important role.

In recent years we have seen a rapid increase in the use of computers for engineers in solving the problems. In the same contrast particularly Computational Fluid Dynamics (CFD) is true subject for the problem solving that involves fluid heat transfer and fluid flow which occur in applications related aerospace, power sector and automobile industry. The various factors that are the reasons for the development of CFD are:-

- Growth in the complexity of the engineering problems that can be unsolved in manual way.
- Need of quick solution with moderate accuracy.
- The expenses that an industry bears during laboratory experiment of physical prototype.
- The absence of analytical solutions.
- Exponential growth in the number crunching abilities and rigorous computer speed and its

CFD enables us to utilize its tools more in day today automobile and aircraft design and also helps in solving the fluid flow problems.. CFD applications in the any industries have large number of codes available for designing of any product. There are several applications ranging from system - level (e.g., exterior aerodynamics) to the components - level (e.g., disk brake cooling).

Study of motion of the fluid with reference of forces and moments is known as fluid dynamics. In fluid flow there different types of forces occurs in the flow like viscous forces, gravitational forces, pressure forces, surface tension forces, eddy forces (turbulent forces) and different type of other forces.

All CFD in one form is based on governing equations of fluid dynamics- the continuity equation, momentum equations and energy equations.

- Conservation of mass.
- Newton’s second law i.e. F=ma.
- Conservation of energy.

In fluid flow velocity is function of space and time, so the acceleration is the function of space and time. Space component is known as convective acceleration and time component is known as local acceleration. During the ANSYS analysis the above acceleration place an important role and help the engineer to make proper aerodynamic design of the vehicle. This is so because the acceleration and velocity component are responsible for lift and drag of the vehicle. Improper design leads to create serious lift of vehicle and this may results in serious accident. Inorder to avoid this impact in the absence of physical prototype graphically the prototype is designed and is tested through computer itself by the use of ANSYS and employing Computational Fluid Dynamics theory.

Apart from the above concept some terms need to be described which will helps to validate the whole analysis:-

- Flow Lines:- Fluid flow can be described by 3 flow lines

- Stream line:- It is an imaginary line or curve drawn in space such that tangent drawn gives velocity vector i.e. velocity vector and stream line vector coincides. The two streamlines never intersect each other as well as stream line also never intersects itself because at the point of intersection there will be two velocity fields which is impossible. So there is no flow across the streamlines.
- Path line:- The line drawn by tracing the path of single fluid particle at different time integrals. It is defined on the basis of ‘Langrangian description’.
- Streak line:- It is an instantaneous picture of all fluid particles passing through single point.

NOTE:- For the steady flow all three lines are identical i.e. all three line coincides.

- Acceleration in fluid motion:- In fluid flow velocity is the function of space and time, so the acceleration is the function of space and time. Space component is known as convective acceleration and time component is known as Local acceleration.
- Contours:- It is an outline representing or bounding the shape or form of something. It is used for representation of typical response system in other words we can say it is typical curve line which describes the response system.
- Circulation:- It is the line integration of tangential component of velocity along the closed loop. It is the scalar quantity.
- Vorticity:- It is the mathematical measure of rationality. It is circulation per unit area. It is wise of the rotation. The direction of vorticity is as that of rotation.

Software Product: Flow Simulation 2014 SP1.0. Build: 2573

CPU Type: Intel(R) Core(TM) i3-3110M CPU @ 2.40GHz

CPU Speed: 2400 MHz

RAM: 3994 MB / 134217727 MB

Operating System: (Build 9600)

Model Name: INTF_GREEN-1.sldprt

Project Name: car_cfd(2)

Unit System: SI (m-kg-s)

Analysis Type: External (exclude internal spaces)

Size

X min |
-2.084 m |

X max |
1.119 m |

Y min |
-1.322 m |

Y max |
2.180 m |

Z min |
-7.312 m |

Z max |
2.318 m |

Basic Mesh Dimensions

Number of cells in X |
30 |

Number of cells in Y |
50 |

Number of cells in Z |
128 |

Total Cell count: 192098

Fluid Cells: 188782

Solid Cells: 1823

Partial Cells: 1493

Trimmed Cells: 0

Heat Transfer Analysis: Heat conduction in solids: Off

Flow Type: Laminar and turbulent

Time-Dependent Analysis: Off

Gravity: Off

Radiation:

Humidity: Off

Default Wall Roughness: 0 micrometer

Ambient Conditions

Thermodynamic parameters |
Static Pressure: 101325.00 Pa Temperature: 293.20 K |

Velocity parameters |
Velocity vector Velocity in X direction: 0 m/s Velocity in Y direction: 0 m/s Velocity in Z direction: -28.000 m/s |

Turbulence parameters |
Turbulence intensity and length Intensity: 0.10 % Length: 0.008 m |

Global Goals

GG Normal Force (Z) 2

Type |
Global Goal |

Goal type |
Normal Force (Z) |

Coordinate system |
Global coordinate system |

Use in convergence |
On |

GG Normal Force (Y) 1

Type |
Global Goal |

Goal type |
Normal Force (Y) |

Coordinate system |
Global coordinate system |

Use in convergence |
On |

Calculation Time: 1074 s

Number of Iterations: 194

Warnings:

Goals

Name |
Unit |
Value |
Progress |
Use in convergence |
Delta |
Criteria |

GG Normal Force (Z) 2 |
N |
-13.413 |
100 |
On |
0.0205115416 |
0.42888513 |

GG Normal Force (Y) 1 |
N |
-5.307 |
100 |
On |
0.132240712 |
0.135369716 |

Min/Max Table

Name |
Minimum |
Maximum |

Pressure [Pa] |
100956.99 |
101951.25 |

Temperature [K] |
293.11 |
293.59 |

Density (Fluid) [kg/m^3] |
1.20 |
1.21 |

Velocity [m/s] |
0 |
31.454 |

Velocity (X) [m/s] |
-19.707 |
8.659 |

Velocity (Y) [m/s] |
-11.901 |
15.510 |

Velocity (Z) [m/s] |
-31.215 |
0 |

Temperature (Fluid) [K] |
293.11 |
293.59 |

Mach Number [ ] |
0 |
0.09 |

Vorticity [1/s] |
1.746e-005 |
276.745 |

Shear Stress [Pa] |
0 |
2.45 |

Relative Pressure [Pa] |
-368.01 |
626.25 |

Heat Transfer Coefficient [W/m^2/K] |
0 |
0 |

Surface Heat Flux [W/m^2] |
0 |
0 |

Advantages of CFD

It finds a critical broken process and offers a solution.

It involves simplified equations and simulations.

Provides better prediction in a short time period.

Disadvantages of CFD

Initial investment cost is high.

Required skilled persons therefore costly in field of professionals.

Future of CFD

After the above analysis we have reached a certain platform in understanding of and appreciation for CFD. CFD is the new “third dimension” in fluid dynamics, equally sharing the stage with the other dimension of pure theory and pure experiment. Throug CFD we come to know about the nature of fluid flow through the pipes and the most important is the understanding of flow over the aerofoils.

References

There are no sources in the current document.

- Automotive computational fluid dynamics simulation of a car using ANSYS. Praveen Padagannavar and Manohara Bheemanna School of Aerospace, Mechanical & Manufacturing Engineering Royal Melbourne Institute of Technology (RMIT University) Melbourne, VIC 3001, Australia
- Janvijay Pateriya, Raj Kumar Yadav, Vikas Mukhraiya and Pankaj Singh, Brake Disc Analysis with the Help of Ansys Software. International Journal of Mechanical Engineering and Technology, 6(11), 2015, pp. 114–122.
- Rakesh Jaiswal, Anupam Raj Jha, Anush Karki, Debayan Das, Pawan Jaiswal, Saurav Rajgadia, Ankit Basnet and Rabindra Nath Barman, Structural and Thermal Analysis of Disc Brake Using Solidworks and Ansys. International Journal of Mechanical Engineering and Technology, 7(1), 2016, pp. 67–77.
- Ducoste, ‘An Overview of Computational Fluid Dynamics’, 2008
- Mampeay, F., and Z. A.Xu “An experimental and simulation Study of mold filling combined with heat transfer”. In C. Hirsch, J, Periaux and W. Kordulla(eds.), Computational Fluid dynamics ’92, vol. 1, Elsevier, Amsterdam,1992,pp. 421-428.

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