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Aim: External flow simulation over an Ahmed body. Objective: The objective of this project is to determine the aerodynamic forces on the Ahmed body such as drag and lift coefficient and to perform the grid independence test. The expected results will include 1. Velocity and pressure contours. 2. The drag coefficient…
Faizan Akhtar
updated on 30 Apr 2021
Aim: External flow simulation over an Ahmed body.
Objective: The objective of this project is to determine the aerodynamic forces on the Ahmed body such as drag and lift coefficient and to perform the grid independence test.
The expected results will include
1. Velocity and pressure contours.
2. The drag coefficient plot for a refined case. ( For a velocity of 25m/sec, the drag coefficient should be around 0.33).
3. The vector plot clearly showing the wake region.
4. Perform the grid independence test and provide the values of drag and lift with each case.
Abstract
Ahmed body: The Ahmed body was first created by S.R. Ahmed. It is an important benchmark for aerodynamic simulation tools. It will be clearly shown in the sketch below that it has a length of 1.044 meters, the height of 0.288 meters and the width of 0.389 meters. It also has a 50 millimeter cylindrical legs attached to the bottom of the body and the rear surface which has a slant that falls of at 35 degrees.
The flow for the model is turbulent which is based on velocity and body length. For the default mesh size in ANSYS-FLUENT we will use k-εk−ε model and for the later stage k-ωk−ωSST model is used.
Importance of Ahmed body
The drag force is an important factor considering fuel consumption. As the drag force increases the fuel consumption also increases which in turn becomes expensive for the car owners. As the burning of fossil fuels becomes an issue, the manufacturers are pressing for fuel-efficient cars. One of the main factors considering the car is fuel-efficient or not is the car's geometry.
Complex shaped cars are very challenging to model and its difficult to quantify the aerodynamic drag computationally. The Ahmed body is a benchmark model widely used in the automotive industry for validating simulation tools.
Negative pressure in the wake region
When the air moving over the vehicle is separated at the rear end, it leaves a large low-pressure turbulent region behind the vehicle which is known as the wake. This contributes to the formation of pressure drag which affects the vehicle performance.
When the vehicle is moving at a certain velocity the fluid imparts viscous force to the vehicle as long as it is in the viscous sublayer of the boundary. When the fluid reaches the rear end of the vehicle it gets detached from the surface of the body causing negative pressure in the wake region. The movement of the fluid around the vehicles depends on the geometry of the car and the Reynolds number.
Significance of point of separation
The point of separation will occur when there is a discontinuity in the surface or a region of the negative pressure gradient (a sharp end or rear portion of the car).
When the flow is attached to the body of the vehicle the viscous force will increase which will increase the pressure and a decrease in velocity before the rear end of the vehicle. As soon as the air encounters the sharp turn causing the velocity to decrease resulting in the negative pressure region which is in the wake region. The recirculation region happens beyond the point of separation.
If the rate of change of pressure is large the mixing process will not occur and the boundary layer flow stops.
The above figure shows that at the point of turning the flow gets separated from the boundary layer and there is a region of recirculation after which the flow attaches itself to the boundary layer.
In order to reduce the separation of fluid from the boundary layer, it is advisable to have a smooth edge to reduce the effect of drag on the vehicle.
Modeling approach
Baseline simulation approach using k-εk−ε model.
Simulation with a finer mesh using k-ωk−ωSSTSST.
Preprocessing and the solver settings
Case-1: External flow simulation over Ahmed body by creating a single closure and using default mesh value of ANSYS-FLUENT
Turbulence model: k-εk−ε
Ahmed body model
Creating an enclosure across Ahmed body
Creating a plane section on the origin
The three planes are normal to the x,y,z axes respectively.
As the body is perfectly symmetric, we can simulate by considering only half the body. This is the best practice where we can save on the number of cells and get the results faster as well.
To get half of Ahmed's body, the section mode is selected in SpaceClaim and the front view plain is selected to yield the desired result accordingly.
Once the geometry part is complete, it is loaded in the meshing window to perform the baseline meshing.
Simulating with a default mesh size of Ansys-Fluent
Creating named selection to set up physics and boundary conditions.
Inlet boundary condition (velocity inlet).
Outlet boundary condition (pressure outlet)
Symmetry boundary condition
Creating named selection for car walls
To create the named selection for car walls we need to hide the faces of the enclosure by hitting function key f8.
Performing meshing with default mesh size in ANSYS-FLUENT
Element size: 0.4136m0.4136m
Number of elements: 8378183781
The geometry is cut into two halves by using a section plane
Thus the mesh is created inside Ahmed's body which is not good for simulation because the flow outside Ahmed's body is taken into account. It can be fixed by going back to Spaceclaim, one of the copies should be suppressed for physics.
The required geometry is then loaded into the ANSYS-FLUENT window.
Simulation procedure
Setting up of physics
Reference values
The frontal area of Ahmed body
Area ==0.389⋆0.16350.389⋆0.1635==0.1120320.112032m2m2
Length of Ahmed's body ==1.0441.044mm
Material properties
Viscous model
Hybrid initialization is selected and the solution is initialized by hitting tt==00
Creating a cut plane to see the velocity change along Ahmed's body.
Creating contour plot along cut plane z
Results
Residual plot
After 700 iterations, the same repeating trends are observed.
Drag-coefficient plot
Lift-coefficient plot
Velocity contour
Pressure contour
Drag-coefficient | 0.7253 |
Lift-coefficient | 0.5865 |
It can be inferred from the following figure that the results of the base simulation are distorted and do not capture the turbulent flow behind the body perfectly. This simulation captures the wake length, high velocity, low-velocity areas which can be used to further refine the mesh value around the Ahmed body and add a local refinement around.
Case-2 (a) External flow simulation over Ahmed body with finer mesh in a double enclosure.
Turbulence model: k-ωk−ω SSTSST.
First refinement
A region of local refinement is added to the Ahmed body.
Share Topology: It is set to share. It is used for sharing the information between the two enclosures and also to make the mesh uniform.
The geometry is loaded into the meshing window.
Meshing
The meshing involves the following steps
Method
Outside the box, the hexahedral mesh is used. The mesh is of the highest quality and gives higher accuracy.
Multizone method: It is used to create hexahedral meshes wherever possible and for other regions where different mesh types are used it will connect it properly.
Sizing: It is defined as increasing the number of elements by decreasing the element size. The element size of the second closure is 0.050.05mm
Element size for the first enclosure: 100100mmmm or 0.10.1mm
Maximum size for the first enclosure: 100100mmmm or 0.10.1mm
Element size for the second enclosure: 5050mmmm
Element size of pillars of Ahmed body: 55mmmm
Number of elements : 1,92,628
Inflation layer: It is the process of adding layers to the boundary to cover the boundary layer thickness fully.
The first cell height predicted value is 55 mmmm
Inflation layer: 55
Last layer thickness: 1515 mmmm
Y+ value : 345
Residual plot
After 1750 iteration the same repeating trends are observed
Drag-coefficient plot
Lift coefficient plot
Velocity contour
Wake region
Pressure contour
Wake region
The vector plot showing the wake region
Drag coefficient | 0.38361 |
Lift coefficient | 0.30305 |
Case 2(b) : Second refinement
Turbulence model: k-ωk−ω SSTSST.
The multizone was used for the second area. The number of element size for the outer enclosure is taken as 9090 mmmm whereas the element size for the inner closure is taken as 4545 mmmm. Face sizing was implemented for the pillars of Ahmed's body ( 5mm5mm).
Inflation layer
First layer thickness: 33mmmm
Number of layers: 1010
Last layer thickness: 15.479315.4793mmmm
Number of elements: 253152253152
The value of y+ is around 207.
Residual plot
After 1600 iterations the same repeating trends are observed.
Drag coefficient
Lift coefficient
Velocity contour
Wake region
Pressure contour
Wake region
Vector plot showing the wake region
Drag coefficient | 0.3512 |
Lift coefficient | 0.2889 |
Case 2(c): Third refinement
Turbulence model: k-ωk−ω SSTSST.
Element size in the first enclosure: 80mm80mm
Element size in the second enclosure: 40mm40mm
Element size of the bottom leg of Ahmed body: 5mm5mm
Number of inflation layer: 1010
First layer thickness: 0.15mm0.15mm
Last layer thickness: 0.77mm
Number of elements: 348448
Y+ : 10
Residual plot
After 1200 iteration the repeating trends are observed.
Drag coefficient plot
Lift coefficient plot
Wake region
Pressure contour
Wake region
Vector plot near the wake region
Drag coefficient | 0.3498 |
Lift coefficient | 0.2884 |
Demonstration of grid independence test
Comparison of all cases
Steady-state, Turbulent flow, Density-based, Fluid material-Air | ||||
Grid Independence Test | Turbulence-model | Number of elements | Lift-Coefficient | Drag-Coefficient |
Baseline mesh | k-ε | 83781 | 0.5865 | 0.7253 |
First refinement | k-ωSST | 192628 | 0.3030 | 0.3836 |
Second refinement | k-ωSST | 253152 | 0.2889 | 0.3512 |
Third refinement | k-ωSST | 348448 | 0.2884 | 0.3498 |
It can be inferred that the imitation of the experimental result is obtained during the second refinement. Thus the grid independence test saves a lot of computational time and convergence can be achieved by using smaller cell sizes for calculation.
Conclusion
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