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STEADY-STATE SIMULATION OF FLOW OVER A THROTTLE BODY USING CONVERGE CFD l. INTRODUCTION A throttle is…
Himanshu Chavan
updated on 17 Jul 2021
STEADY-STATE SIMULATION OF FLOW OVER A THROTTLE BODY USING CONVERGE CFD
l. INTRODUCTION
A throttle is a mechanism by which fluid flow is managed by constriction or obstruction. An engine's power can be increased or decreased by the restriction of inlet gases (by the use of a throttle), but usually decreased. The term throttle has come to refer, informally, to any mechanism by which the power or speed of an engine is regulated, such as a car's accelerator pedal.
ll. OBJECTIVE
lll. GEOMETRY
The geometry consists of 4 basic components:
1. Geometry Setup
Geometry setup in converge studio.
2. Diagnosis Check
3. Boundary Flagging
lV. Case Setup
1. Fluid: Air
2. Solver:
A steady-state pressure-based solver is used to simulate the flow. In Misc, UseSharedMemory is unchecked and Steady-State Monitor is checked.
3. Simulation Cycles:
4. Boundary Conditions:
5. Regions and Initialization:
6. Turbulence Model: RNG k−ε
7. Grid Control:
8. Output Files:
V. RESULTS
1. Mesh
Decreasing the mesh size around the throttle helps in capturing the results at the boundary of the throttle more accurately and also results in the smoothing of the contours around the throttle. However, this also increases the computational time due to the increased number of cells.
Figure 1.1 - Mesh
Figure 1.2 - Mesh around the Throttle
2. Velocity Contours and Pressure Contours
There are three distinct regions around the throttle in which flow can be analyzed -
2.1 The region just before the throttle
The point of impact of the fluid with the throttle takes place in this region. In this region, the separation of the fluid takes place resulting in a sudden decrease in the velocity. This also results in a sudden increase in the pressure as the kinetic energy gets converted into pressure energy and the energy remains conserved.
2.2 The region below the throttle
Since there is sudden decrease in the are below the throttle, the velocity of the fluid will increase to ensure a constant mass flow rate. This also results in a decrease in the pressure in this region.
2.3 The region just after the throttle
The reattachment of the fluid takes place in this region. At this point of reattachment, the fluid flows in different directions, causing a decrease in the velocity of the fluid.
Figure 2.1 - Velocity Contour
Animation - Velocity Contour
The animation of the velocity contour shows that the steady-state solver only focuses on the final equilibrium results and not the actual behavior of fluid with respect to time, which in turn, would require the transient solver. Thus, we are only able to see the formation of the final velocity contour and not the actual behavior of the fluid at different time steps.
Figure 2.2 - Pressure Contour
3. Velocity Vectors
The velocity contours can be understood better by observing the direction of flow using velocity vectors.
Figure 3.1 - Velocity Vectors
Figure 3.2 - Velocity Vector around the throttle
4. Velocity Streamline
Since the case is solved using a steady-state splver, the velocity streamlines describe the motion of the velocity particles when the system is in equilibrium. Thus, the streamlines and the pathlines are identical at the end of the simulation.
Figure 4.1- Velocity Streamlines
Figure 4.2 - Velocity Streamlines around the Throttle
5. Variation Of Average Velocity w.r.t Number of Cycles
6. Variation of Pressure w.r.t Number of Cycles
7. Variation of Mass Flow Rate w.r.t Number of Cycles
8. Variation of Cell Count w.r.t. Number of Cycles
The cells are unevenly distributed among the four processors in order to achieve a good load balance. in this case, since the simulation is simple, the number of cells is distributed almost equally. Also, since there are no moving parts in the geometry, the number of cells remains constant throughout the simulation.
Vl. CONCLUSION:
Analyzing the separation of flow helps us to understand the equilibrium behavior of fluids under different boundary conditions. This helps to control the flow behaviour and output depending on the requirement or application of the model.
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