Projects

Steady Flow Around a Cylinder

Plot : Drag Coefficient vs Reynolds Number

In this project, a CFD study of a “Steady Flow Around a Cylinder” has been done using ANSYS Fluent. The study has been done for Re number- 20,40,100 for two different types of mesh- coarse mesh and fine mesh. The results indicate that with the increase of the Re number the drag co-efficient decreases gradually and there is a slight difference in the values for coarse and fine mesh.

The pressure contours from the coarse and fine mesh for the same Re number seem to be the same but they are different for different Re numbers. From the pressure contour, it can be seen that the pressure is higher along the x-axis in front of the cylinder from where the flow is moving. But the pressure is lower in the backside of the cylinder due to flow separation along the body. This results in a net pressure force along the x-axis which is the drag force. But the pressure on the top and bottom sides of the cylinder is low and the same to each other which means there is no pressure difference acting there. Thus, there is no lift force on the cylinder.

The velocity contours from the coarse and fine mesh for the same Re number seem to be the same but they are different for different Re numbers. From the velocity contour, it can be seen that the velocity is lower in the front of the cylinder and at the stagnation point it becomes zero. As the flow moves around the body the velocity starts to increase but it becomes lower in the back of the cylinder due to flow separation. The velocity over the top and bottom sides of the cylinder rises gradually and reaches the maximum value.

2D Turbulent Pipe Flows

Figure 1: Geometry of the 2D pipe

In this project, a CFD study of “Turbulent Pipe Flow” has been done using ANSYS Fluent. The simulation has been done on a 2D pipe at Reynolds numbers 10000 and 100000 which fall well within the turbulent flow regime. A pipe of 0.1 m in diameter and 6 m in length was modeled as a geometry (Figure- 1) of the simulation. The working fluid is water and the standard K-epsilon Model was used and the enhanced wall treatment was used for the near-wall treatment. For the solution method, the Spatial Discretization method was used and the pressure, momentum, turbulent kinetic energy, and turbulent dissipation rate was modified to second order.

Figure 2: Plot for the cross-sectional velocity at 5m downstream

From Figure - 2, it can be seen that the velocity increases with the change of the Reynolds number from 10000 to 10000 at different y-values. For Reynolds number 10000 the numerical and analytical results are almost similar. But for Reynolds number 100000 the numerical and analytical results are a bit different at various points.

Figure 3: Comparison of the normalized centerline velocity

For further visualization of the flow, the normalized centerline velocity was compared. From Figure - 3, it can be seen that for Re = 10000 the normalized velocity increases at first but it gets almost constant after x = 3 m. For Re = 100000, the normalized velocity gradually increases up to around 3.44 m but then it decreases gradually to the outlet. For Re = 10000 the velocities are more at some point than for Re = 100000 and they are less at some point than Re = 100000.

Figure 4: Comparison of wall Y-plus value

From Figure - 4 it can be seen that the Y-plus value is less at Re = 10000 but they are higher at Re = 100000. For the change of Reynolds number, the Y-plus value changes as Reynolds number is a function of shear velocity which changes the Y-plus value. So, for the increase of Reynolds number the wall Y-plus value increases.

Flow Past a NACA 4412 Airfoil

In this project, a CFD study of the flow past a NACA 4412 airfoil was done using ANSYS Fluent. For the geometry, the coordinates of the airfoil were imported from existing data and the meshing was done using the C-mesh approach. For the simulation, different angles of attack (0, 5, and 16 degrees) were considered to see the variation in the lift and drag coefficient of the airfoil alongside the flow behavior of the fluid around the airfoil.

Figure 1: Lift coefficients (C_L) vs. Angle of attack (α) comparing CFD results against Experimental and XFOIL data

Figure 2: Drag coefficients (C_L) vs. Angle of attack (α) comparing CFD results against Experimental and XFOIL data

For the validation of the simulation, the plots of the lift coefficient, C_L and the drag-coefficient, C_D vs different angles of attacks (0, 5, and 16 degrees) were generated (Figure-1 and Figure-2) and compared with the experimental and X-FOIL data.

From Fig-1, and Fig-2, the validation plots can be observed. The CFD simulation results show the same trend as the experimental and X-FOIL data but they are not exactly the same.

The same trend of the numerical data and the experimental data shows the acceptance of the validation of the numerical model though the datasets are not exactly the same at all points. For the comparison of the numerical results of different viscous models, the numerical data for all the models (Spalart-Allmaras, k-ε, k-ω SST) were compared with the existing experimental and X-FOIL data in the plots. The dataset for different numerical models was very close to each other and also followed the same trend as the existing datasets.

From the pressure contours, it can be seen that the pressure drop largely increases near the leading edge of the airfoil with the increase in angle of attack and a recirculation zone is created at the trailing edge for the flow over the airfoil.

From the velocity contours, it can be seen that the velocity increases largely near the leading edge of the airfoil with the increase of angle of attack due to high-pressure drop and a recirculation zone is created at the trailing edge for the flow over the airfoil.

Simulating Convective Heat Transfer Past a Pin Fin

In this project, a CFD study of heat transfer past a 3D copper pin fin was done using ANSYS Fluent. The convective heat transfer coefficient for copper was calculated from the data for the temperature at different locations along the pin fin. The k-ε model was used as the viscous model with enhanced wall treatment where the base temperature was set as 100 degrees Celsius.

Figure 1: Geometry of the Pin Fin and the flow domain

Figure 2: Mesh of the pin fin and the flow domain

Figure 3: Plot for the temperature distribution and comparison with experimental and analytical solution

Figure 4: Temperature contour of the copper pin fin

The temperature distribution from the experiment and CFD simulation were compared with the exact analytical solution that shows significant variation due to material selection and mesh quality. To improve the result an alternative CFD approach was implemented that shows a better result. The temperature distribution and the convective heat transfer coefficient are shown in Figure - 3. The temperature contour in Figure - 4 shows the temperature distribution along the pin fin which is higher at the inlet and as the flow moves the temperature reduces.

Performance Analysis of a JT8D Turbofan Engine

In this project, the performance of a JT8D turbofan engine was analyzed. The analysis was done using EES software. The effect of different operating conditions (altitude, bypass ratio, pressure ratio) on the performance of the engine were investigated.

Effect of Altitude

Figure 1: Thrust (lbf) versus Altitude, z (m)

From Figure - 1, the graph shows that with the increase in altitude the thrust starts to rise from the beginning up to z = 1200 m, but it gradually goes down after reaching a thrust of 3600 lbf. As the altitude increases, the density of air as well as the mass flow rate falls. For this reason, the thrust gradually decreases to 1500 lbf as we increase the altitude to 14000 m.

Figure 3: Thermal efficiency versus Altitude, z (m)

Figure 2: Cost ($) versus Altitude, z (m)

From Figure - 2, The graph shows that with the increase in altitude the cost gradually goes down. As the altitude increases, the density of air as well as the mass flow rate falls. As a result, less fuel is consumed inside the engine which lowers the fuel cost gradually. For this reason, the cost for flying from New York to San Francisco goes down from 8000$ to 2700$ as the altitude changes from 0 m to 14000 m.

From Figure - 3, the graph shows that with the increase of altitude from 0 m to 14000 m the thermal efficiency gradually increases from 36% to 46%. As the altitude increases, the temperature of the surroundings goes down. The maximum temperature is the temperature of the gas coming out of the combustion chamber and the minimum temperature is the outside air temperature. According to Carnot’s principle, if the temperature difference between the heat source and heat sink of a system increases, the efficiency of the system rises. Following that, as the outside temperature decreases, the engine can produce more work, and that eventually increases the thermal efficiency.

Effect of Bypass Ratio

Effect of Pressure Ratio

Figure 4: Specific Thrust (N·s/kg) vs Bypass Ratio, B

From Figure - 4, the graph shows that as the Bypass ratio, B increases specific thrust increases up to B= 6.8 but it goes down after that and the system fails when B=8. The engine core requires a certain mass flow rate to spin the fan which draws the air into the bypass. Therefore, if the core doesn’t receive enough air the low-pressure turbine can’t produce enough work to spin the low-pressure compressor and the fan. For this reason, when the B becomes more than 6.8 the thrust starts to go down and at B = 8 the engine fails.

Figure 5: Specific Thrust (N·s/kg) vs compress factor, x

From Figure - 5, The graph shows the specific thrust goes down with the increase of pressure ratio and at x = 1.25 the system fails. When the pressure ratio increases, the compressor requires more work to run. As a result, all the enthalpy is being spent in the turbine to run the compressor due to increase of compression action. If all the energy is spent in the turbine, the energy required to run the whole engine will go down and it won’t work. For this reason, when x is greater than 1.25 the engine fails.

Automated Robotic Arm with object detection by image processing

Figure 1: Automated Robotic Arm

Objectives and Roles: The goal of this project was to make a 360-degree robotic arm that can grab objects and sort them in different predetermined angular positions based on their color and shape. The objects weighted 50 gm. and circular, rectangular, and hexagonal shapes were used. The colors were blue, red, and green. This was an undergrad project of 3 group members where my role was to construct the mechanical structure, connect the electronic components, and control the robot.

Results: The robotic arm successfully detected the colors using image processing and sorted and placed the objects in their determined position. The object color data was fed into the system using a webcam connected to the laptop. Blob detection methodology was used for identifying the colors and 90-degree, 180-degree, and 270-degree position was used for placing the objects based on their shape and color.

Water waste collector robot (W-BOT)

Figure 1: Water waste collector robot prototype

Objectives and Roles: The goal of this project was to build a water waste collector robot for a small area of water that can grab waste from distant places and dispose that in a suitable location. This was an undergrad group project of 2 people where my role was to construct the mechanical structure, connect the electronic components, and control the robot.

Results: The working prototype of the robot fulfilled the objective successfully and could collect waste of 1 kg from a 500 m of distance. Servo motors were used for moving the arm of the robot and a Li-Po battery was used for the power source of the robot. A propeller was used for generating thrust that helped the robot to move and navigation was done by using radar. The robot was controlled by a remote controller.

Remote controlled flying plane

Figure 1: Remote controlled flying plane

Objectives and Roles: The goal of this project was to build a remote-controlled plane and understand the aerodynamics of the flight. This was an individual undergrad project where my role was to study the concepts of flight, build the structure, connect the electronics, and control the plane.

Results: The plane successfully flew after breaking initially 5 times. The flying altitude was 20 feet and the speed was slow. Servo motors were used for controlling the radar, aileron, and elevator. An electronic speed controller was used for running the BLDC motor which was powered by a 3 cell Li-Po battery.

Design and construction of a Pneumatic Load Cell

Figure 1: Construction model of pneumatic load cell

Objectives and Roles: The goal of this project was to study different load cells and design and construct a working pneumatic load cell. This was an undergrad academic project where I have done the literature review of different load cells, designed a pneumatic load cell, and built a working load cell.

Results: The load cell could measure the minimum load of 150N and maximum load of 493N. The maximum pressure was 4kg/cm². For different applied loads the pressure was measured in the pressure gauge connected with the pneumatic cylinder. From the values obtained in the pressure gauge for different loads, the load vs pressure curve was analyzed. The curve was almost linear and shows that with the increase of loads the pressure also increases gradually.

Line follower robot for obstacle detection

Figure 1: Line follower robot

Objectives and Roles: The goal of this project was to build a robot that can detect line colors and avoid obstacles during moving through the line. It was an undergrad group project of 3 people where I was responsible for the construction of the mechanical structure.

Result: The robot was controlled using Arduino and it was powered by a Li-Po battery. The robot could detect line colors successfully using IR sensors and avoided obstacles using sonar. These data were sent to the Arduino and then according to the code, the robot moved.

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