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Challenge

Ahmed Body Challenge

AAkshay Unnikrishnan24 Jul 2020

challenge 3#AHMED BODY

Aim

The aim is to investigate experimentally the aerodynamic behaviour of the Ahmed body under grid dependancy test by varying mesh size and to test the ability of the CFD simulation package Fluent to reproduce the experimental data.

Introduction

Optimized external car aerodynamics is necessary to achieve efficient vehicles with minimized fuel consumption,CO2 emissions, and noise, while keeping a good driving stability. Steadily increasing computer power has been raising the importance of simulating the external aerodynamics of vehicles and computing the corresponding aerodynamic characteristic numbers. At present, an efficient resource management gains increased importance everywhere. A substantial part of the development time of cars is therefore invested in optimization. This is possible only and particularly by virtual development. In order to establish such development processes in the car industry, reliable simulation models validated by experiments are needed. Model experiments suitable for providing validation data make use of model bodies with geometries characterized by variable parameters, such as the slant angle at the back. One such body is the Ahmed body.

Theory

The Ahmed body is a generic car body. The airflow around the Ahmed body captures the essential flow features around an automobile.Ahmed body allows us to capture characteristic features that are relevant to bodies in the automobile industry.This model is also used to describe the turbulent flow field around a car-like geometry. Once the numerical model in validated, it is used to design new models of the car.

The Ahmed body was described originally by S. R. Ahmed in 1984 . Three main features seen in the wake are:

1. The A recirculation region that is formed as the flow separates at the top of the vertical back surface of the model

2. The B recirculation region that is formed due to the separation at the base of the model.

3. The c-pillar vortices that form as the vorticity in the side boundary layers roll up over the slant edges.

The wake was shown to be highly dependent on slant angle. For slant angles less than 12°, the flow remains attached over the the slant. The flow is essentially two-dimensional and has low drag. Between 12° and 30° the flow becomes much more three-dimensional as the c-pillar vortices form. These reach maximum strength at 30°. The drag increases significantly as the low pressure cores act on the rear surfaces. Past 30° the flow separates fully off the slant. This results in a sudden decrease in drag and weaker c-pillar vortices.

The drag coefficient quantifies the resistance of an object in a fluid environment. It is not an absolute constant for a body’s shape because it varies with the speed and direction of flow, object shape and size, and the density and viscosity of the fluid. The lower the drag coefficient of an object, the less aerodynamic or hydrodynamic drag occurs. In terms of a car, the lower the drag coefficient, the more efficient the car is. As well as affecting the top speed of a vehicle, the drag coefficient also affects the handling. Cars with a low drag coefficient are sought after, but decreasing the drag drastically can reduce the downforce and lead to loss in road traction and a higher chance of car accidents.

Solving and Modelling approach

  • By creating one or more enclosure around the Ahmed body we can refine and reach the perfected experimental values of the Ahmed body model. making sure that there is no interference between these enclosure and should share topology between them.
  • As for more refinement finer meshes like hexahedral meshes are used.
  • As the Inlet velocity is 25m/s we should choose pressure based solver and the turbulance model is k epsilon,Run till convergence and find out the drag force coefficient ,lift coefficients and other parameters.
  • On cfd post visualise the contours of pressure and velocity generated by Ahmed body.

To perform a grid dependancy test We will divide the solution into 3 cases in order.

The ahmed body

Smaller enclosure:

Larger enclosure:

With both enclosures together:

Ahmed body with two enclosures

Inlet Symmetry Wall

Outlet Car wall

The boundary conditions for the 3 cases will be same as follows

Solver used in this case with inlet velocity 25m/s is pressure based solver under steady state.With k-Epsilon as turbulance model.

We are using Hybrid initialisation with 200 iterations

Case1:Elements 177679

Drag coefficient(0.38833845)

Lift Coefficient(0.26102638)

Cfd post

Case 2:elements 287147

Lift coefficient(0.26569252)

Drag coefficient(0.37131422)

Case 3:Element 429587

Drag coefficient(0.38099104)

lift coefficient(0.30256649)

Cfd post

Animation files of cases 1,2 and 3 are given below

Results

Pressure gradient is an is one of the factors that influences a flow immensely. It is easy to see that the shear stress caused by viscosity has a retarding effect upon the flow. This effect can however be overcome if there is a negative pressure gradient offered to the flow. A negative pressure gradient is termed a Favourable pressure gradient. Such a gradient enables the flow. A positive pressure gradient has the opposite effect and is termed the Adverse Pressure Gradient.

One of the severe effects of an adverse pressure gradient is to separate the flow. Consider flow past a curved surface as shown in Fig.6.4. The geometry of the surface is such that we have a favourable gradient in pressure to start with and up to a point P. The negative pressure gradient will counteract the retarding effect of the shear stress (which is due to viscosity) in the boundary layer. For the geometry considered we have a an adverse pressure gradient downstream of P.

Now the adverse pressure gradient begins to retard. This effect is felt more strongly in the regions close to the wall where the momentum is lower than in the regions near the free stream. As indicated in the figure, the velocity near the wall reduces and the boundary layer thickens. A continuous retardation of flow brings the wall shear stress at the point S on the wall to zero. From this point onwards the shear stress becomes negative and the flow reverses and a region of recirculating flow develops. We see that the flow no longer follows the contour of the body. We say that the flow has separated. The point S where the shear stress is zero is called the Point of Separation.

Depending on the flow conditions the recirculating flow terminate and the flow may become reattached to the body. A separation bubble is formed. There are a variety of factors that could influence this reattachment. The pressure gradient may be now favourable due to body geometry and other reasons. The other factor is that the flow initially laminar may undergo transition within the bubble and may become turbulent. A turbulent flow has more energy and momentum than a laminar flow. This can kill separation and the flow may reattach. A short bubble may not be of much consequence.

On aerofoils sometimes the separation occurs near the leading edge and gives rise to a short bubble. What can be dangerous is the separation occurring more towards the trailing edge and the flow not reattaching. In this situation the separated region merges with the wake and may result in stall of the aerofoil (loss of lift).

The total drag coefficient of the Ahmed body is the key measurement for this simulation. It is made up of measurements for the pressure coefficients in the front, slant, and base of the body as well as the body’s skin friction. In the results of our simulation, the total drag is very well predicted but the individual measurements deviate from the experimental results in varying amounts.

Conclusion

While doing grid dependency test we are refining the mesh making it an easier way to predict the Accurate results performed on the practical Ahmed body experiment.making us to validate and dictate the errors and corrections.

Although the data has quantitative differences, it is qualitatively equal to experimental results because the total drag coefficients are so close. There may be deviating details in the smaller data but the simulation still captures the major features of the flow over an Ahmed body. This simulation is more than adequate for calculating the overall drag coefficient.

Reference

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