# Automotive Computational Fluid Dynamics Simulation Of A Car Using ANSYS

• December 28, 2023/

## General Information

1. Objective of the simulation:- Computational Fluid dynamics analysis of a given box.

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Introduction:- 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 memory.[1]
1. Introduction to CFD:-

Question: What is CFD?

CFD is a method adopted to obtain a discrete solution of problems related to fluid in a real world. The discrete solution is a solution obtained by a finite collection of space points and the level of discrete time. CFD is physical quality of any fluid – flow that is having three governing fundamental principles:-

• Conservation of mass for the fluid.
• Newton’s Second Law: – Which say-s that the rate of the change of momentum is directly pro- portional to the force applied and this rate of change of moment-um is directly proportional to the applied force and in the direction of the applied force.
• Law of conservation of energy which is the first law of thermodynamics and it states that the summation of the rate of change of heat addition must be equal to the work done on the fluid.

In order to continue the understanding of CFD the person must first understand the fluid dynamics and its governing equation.

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The Computational Fluid Dynamics equations can be derived in two stages.

• First stage is the numerical discretization.
• Second stage is the specific technique.

The above two stages are used to solve the algebraic equations which is derived from the governing equations.

Discretization: – The discretization process are identified by some common methods that we are still using today. The two most common methods are the finite-element and spectral methods.

• Finite Element Method

The finite element method is an oldest method among all methods in solving the numerical solution of partial differential equations. This method was derived by Euler in year 1768. It is used to get numerical solutions of the differential equations by manual calculation i.e. by hand calculation. In this method at a number of grids/elements are defined with their respective nodal points. Each grid with the number of nodal points are use-d to describe the fluid – flow domain. Then the concept of Taylor series expansion is applied in-order to generate finite-difference approximation-s to the partial derivatives of the governing equations. These derivatives are then replaced by using finite-difference approximations and this all results in  an algebraic equation for the flow solution at each of the grid point. This method is most commonly used in structured grids since it requires a mesh having a high degree of regularity and accuracy. From all above discussion Finite Element Method can be summarized in three basic features:-

1. Bifurcate the whole body / structure into parts, finite element.
2. For each representative elements create the relations among secondary and primary variable.
3. Assemble of the elements to obtain the relations in form of equation or a matrix between the secondary and primary variables.

As per discretization is concerned the two compatibility conditions must be ensured:-

1. Compatibility of nodal displacement:- When a body is deformed without breaking, no crack appears in stretching and particles do not penetrates each other in elements. Such situation is called Nodal displacement compatibility. The compatibility condition confirms that the displacement is continuous and single value function of position.
2. Equilibrium of forces:- The equilibrium at the nodal forces must be ensured.

Although there are a numerous of commercial and research codes that are available and they can be employed but the in finite-element method CFD application is not so much fruitful. But apart from this there is one method which is in brief same as finite element method and is seems fruitful and commercially uses all codes and is essentially used by CFD. The method is called “Finite – Volume Method (FVM)”. The only differentiating feature is that FVM uses simple piecewise polynomial functions for local elements which tends to describe the variations of the un-known flow variables. The weighted residual concept is introduced in order to evaluate the errors associated with the approximate functions, which are later surely minimized. A set of non-linear algebraic equations for the unknown terms of the approximating functions is solved, hence resulting in the flow solution. The residual functions are solved and the flow solutions are obtained by, Collocation method, Galerkins method, Sub-domain method, and least square method.

• Spectral method

## What is CFD?

Spectral method has a same general approach as that of the finite-difference and finite-element methods, where the unknowns of the equations that are governed are replaced with a some short series. The difference is in only the methods of implementation. The previous two methods uses local approximations but the spectral method implements global approximation. That is by means of Fourier series, Legendre polynomials, for the entire flow body / domain. The conflict between the exact solution and the approximate solution is dealt with by the use of a weighted residuals concept similar to the finite-element method.

The instrument which has allows the practical growth of CFD has a high speed digital computer with a great efficiency. CFD solutions generally requires the repetitive manipulation of many thousands, even millions of numbers, a task that is impossible for any human without the aid of a computer. Therefore, advancement in CFD, and its applications to problems of more detail and sophistication, are intimately related to advances in computer hardware, particularly in regard to storage and execution speed. This is why the strongest force driving the development of new supercomputer is coming from CFD community.

1. Getting the real world flow problems
2. Mathematical modelling of the given body which includes the general equations, boundary conditions etc.
3. Generating the discrete equations (preferably the algebraic equations).
4. Finding the solution of the above algebraic equations.
5. Post processing and the data analysis and finally the flow visualization.
6. Introduction of CFD in fluid dynamics

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. These equations speak the physics. Basically the equations are the mathematical statements of three fundamental physical principles upon which all of the fluid dynamics is based upon:

• Conservation of mass.
• Newton’s second law i.e. F=ma.
• Conservation of energy.
• During the vehicle in motion when the fluid flows under adverse pressure condition, fluid loses its momentum. Near the surface the particles have less momentum so they loses their momentum fastly. At the point where momentum of the fluid becomes zero and after which near the surface the fluid surface the fluid moves under adverse pressure condition i.e. in reverse direction that point is known as point of separation. It is not compulsory that separation must be present in adverse pressure condition.

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. In order 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.

## Steps in CFD Analysis

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

1. 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.

1. Acceleration in fluid motion:- The velocity is the function of time and spaced in the fluid flow, 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.
2. Iso-surface:- An iso-surface is a 3D isoline. It is a type of surface representing the points of a constant value (e.g. pressure, temperature, velocity, density) which is within a volume of space; in other words, it is that level set of a continuous function whose domain is 3D-space. It is a surface which is defined by an implicit equation.

i.e. F (x,y,z) = f

where, F is the function of space and f is the constant.

The `Iso-surface’ is a representation that is used to compute and draw a surface within a volumetric data field on a 3-D surface corresponding to points with a single scalar value. It is displayed by data set, iso-value, draw (Points, Shaded Points, Wireframe, or Solid Surface), boundary, step and size. It is normally displayed by computer graphics. It used as data visualization methods in computational fluid dynamics (CFD) that helps the engineers to study the features of fluid flow. It is mostly helpful in design the system related to aerodynamics such as aircraft wings or the super cars models.

1. 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.
2. Circulation:- It is the line integration of tangential component of velocity along the closed loop. It is the scalar quantity.
3. Vorticity:- It is the mathematical measure of rationality. It is circulation per unit area. It is wice of the rotation. The direction of vorticity is as that of rotation.
1. Aim of the simulation

To create a computational model of the given box in order to do analyse the box showing its behaviour. .

1. Physical boundary is being defined for the given model and the problem.
2. The box is than divided into discrete particle called mesh. The uniformity of the mesh is arranged according to the situation.
3. The defined boundary conditions have specific fluid behaviour.
4. Starting the simulation and the equations is solved at steady state.
5. Postprocessor is then used for analysis and visualization of the results.
1. Aerospace industries.
2. Biomedical
3. Chemical processing.
4. Marines
5. Oil and gas piping industries.
6. Sports etc.
1. Eliminates the process of experimentation in laborartories.
2. Provides better details.
3. Provides better predictions in a short peroids of time.
4. Provides better and fast design meeting all the environmental regulations and ensures industry quality.
5. Provides shorter design cycles and supply products faster in the market.
6. Easy to install with minimum downtime.
7. Allows rapid prototyping.
8. More cost effective.
2. Initial investment cost is high.
3. Required skilled persons therefore costly in field of professionals.
4. 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.

CFD has already had a major impact on car design, and had became the critical technology for aerodynamic design over the next decade. There is no doubt that a major focus of CFD is to enhance the design process for any machine that deals with fluid.

Today, CFD is used to calculate complete three dimensional flow fields over real cars.

The major role of CFD is that of research, a tool to enhance our undersytanding of the basic physical nature of fluid dynamics.

References

Review: CFD Applications in the Automotive Industry. M. N. Dhaubhadel  J. Fluids Eng 118(4), 647-653 (Dec 01, 1996) (7 pages)doi:10.115/1.2835492History: Received March 28, 1996; Revised July 18, 1996; Online January 22, 2008.

Book:- Computational Fluid Dynamics- The basics with applications. John D. Anderson, Jr. Dept. Of Aerospace Engineering University of Maryland.

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.

Anderson, ‘Race Car Aerodynamics Part 2: Lift and Drag’, 2014.

Ducoste, ‘An Overview of Computational Fluid Dynamics’, 2008

Katz, J. 1995, ‘Race car aerodynamics: Designing for speed’, 1st edn, Robert Bentley.

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