Showing posts with label aeronautic. Show all posts
Showing posts with label aeronautic. Show all posts

Friday 26 June 2020

Heaving Airfoil Simulation

This post is about a 2D NACA 0012 heaving aerofoil. Heaving motion is achieved by changing the angle of attack on the aerofoil based on the Eqn. 1.

αe = arctan[2*π*Sta*cos(2*π*fh*t)]+ αi               Eqn. 1

w.r.t. Eqn. 1, αe is the effective angle of attack, Sta is Strouhal number, fh is the heaving frequency.

The case S1 and H6 from [1] are compared in the animations below.


If you want to collaborate on the research projects related to turbomachinery, aerodynamics, renewable energy, please reach out. Thank you very much for reading.

References

[1] https://doi.org/10.1121/10.0001419

Monday 23 July 2018

11x7 Aeronautic Propeller Characteristics (Using CFD) (Verified and Validated) (Update 02)

     This post presents the results from an aeronautic propeller CFD analysis.
    
     An 11x7 propeller was modelled using SolidWorks CAD package using the geometry from [1]. The simulations were run at two different rotational velocities and each rotational velocity was simulated at three advance ratios. The mesh for the 3,000 RPM rotational velocity had 213,205 total cells among which 24,048 cells were at the solid fluid boundary. While, the mesh for the 5,000 RPM rotational velocity had 369,963 total cells among which 68,594 cells were at the solid fluid boundary. A mesh control was employed to refine the mesh near the propeller geometry and at the boundary of the rotating region and the stationery domain for all of the cases simulated. This was done to ensure accuracy of the results was within an acceptable range. The results of the numerical simulations are plotted along with the experimental results [1] in Fig. 1.


Fig. 1 J= Advance Ratio, ηprop = propeller efficiency

     It can be seen from Fig. 1 that the trends for the propeller efficiency are in agreement with the experimental results. To increase the mesh density for the mesh independence test, the number of cells in  each of the respective co-ordinate directions was increased by a factor of 1.1. The mesh is shown in the Fig. 2.

Fig. 2 The computational mesh around the propeller.

     The computational domain size was at 2D x 2D x 2.4D, D being the propeller diameter, as shown in Fig. 3. In Fig. 3, the curved teal arrow represents the direction of rotation of the sliding mesh. The blue arrow represents the direction of free stream velocity while the brown arrow represents the force of gravity.

 Fig. 3 The computational domain.


Fig. 4 The pressure distribution and the velocity vectors around the propeller.

     The CAD model files and the simulation setup files for the numerical analysis are available here.

     Thank you for reading. If you'd like to collaborate on research projects, please reach out.

[1] Brandt, J. B., & Selig, M. S., “Propeller Performance Data at Low Reynolds Numbers,” 49th AIAA Aerospace Sciences Meeting, AIAA Paper 2011-1255, Orlando, FL, 2011.
doi.org/10.2514/6.2011-1255
 

Update 01

     Results from the mesh independent study are now available.

Update 02

     CAD model files are now uploaded. The CFD simulation setup files are also included.

Sunday 22 July 2018

11x4.7 Aeronautic Propeller Characteristics (Using CFD) (Verified and Validated) (Update 02)

     This post presents the results from an aeronautic propeller CFD analysis.

     An 11x4.7 propeller was modelled using SolidWorks CAD package using the geometry from [1]. The simulations were run at two different rotational velocities and each rotational velocity was simulated at three advance ratios. The mesh for the 3,000 RPM rotational velocity had 206,184 total cells among which 22,103 cells were at the solid fluid boundary. While, the mesh for the 6,000 RPM rotational velocity had 357,300 total cells among which 64,012 cells were at the solid fluid boundary. A mesh control was employed to refine the mesh near the propeller geometry and at the boundary of the rotating region and the stationery domain for all of the cases simulated. This was done to ensure accuracy of the results was within an acceptable range. The results of the numerical simulations are plotted along with the experimental results [1] in Fig. 1.



Fig. 1 J= Advance Ratio, ηprop = propeller efficiency
 
     It can be seen from Fig. 1 that the trends for the propeller efficiency are in agreement with the experimental results. The fine mesh had the number of cells in each of the respective co-ordinate directions increased by a factor of 1.1. The mesh is shown in the Fig. 2.
 
Fig. 2 The computational mesh around the propeller.
 
     The computational domain size was at 2D x 2D x 2.4D, D being the propeller diameter, as shown in Fig. 3. In Fig. 3, the curved teal arrow represents the direction of rotation of the sliding mesh. The blue arrow represents the direction of free stream velocity while the brown arrow represents the force of gravity.

Fig. 3 The computational domain.

Fig. 4 The pressure distribution and the velocity vectors around the propeller.

     The CAD model and numerical simulation setup files are available here.
 
     Thank you for reading. If you'd like to collaborate on research projects, please reach out.

     [1] Brandt, J. B., & Selig, M. S., “Propeller Performance Data at Low Reynolds Numbers,” 49th AIAA Aerospace Sciences Meeting, AIAA Paper 2011-1255, Orlando, FL, 2011.
doi.org/10.2514/6.2011-1255
 

Update 01

     Mesh independent test results are now available.
 

Update 02

     CAD files for the propeller including the CFD analysis setup are now available.

Monday 11 June 2018

Marine Propeller Characteristics (Using CFD) (Verified and Validated)

     This post presents the results from a marine propeller CFD analysis. The key thing about this CFD analysis was that the propeller efficiency obtained was within 7% of the experimental results, by using only 112,081 total cells in the computational mesh, of these cells, 21,915 cells were at the solid fluid boundary. The results are, indeed, mesh independent. The software employed was Flow Simulation Premium. The results of the numerical simulations are plotted along with the experimental results in Fig. 1.

Fig. 1 KT = coefficient of thrust, 10KQ = coefficient of torque multiplied by a factor of 10, ηprop = propeller efficiency
 
     It can be seen from Fig. 1 that the trends for the thrust and the torque coefficients and the propeller efficiency are in agreement with the experimental results. The experimental data was taken from here. The flow conditions were following. The propeller diameter was at 0.254 m. Propeller rotational velocity was at 15 rev/s. The propeller inclination angle was at 12°. Fluid considered was water. To change the advance ratio, fluid flow velocity was altered. The computational domain size was at 2D x 2D x 3.2D, D being the propeller diameter, as shown in Fig. 3. The mesh is shown in the Fig. 2.

Fig. 2 The computational mesh around the propeller.
 
Fig. 3 The computational domain.
 
     In Fig. 3, the curved teal arrow represents the direction of rotation of the sliding mesh. The blue arrow represents the direction of free stream velocity while the brown arrow represents the force of gravity. The Pressure distribution on the propeller blades and the velocity streamlines are shown in Fig. 4. The streamlines were drawn using line integral convolution, relative to the rotating frame of reference.
 
Fig. 4 The pressure distribution and the velocity profile around the propeller.
 
     If you'd like to collaborate on research projects, please reach out. Thank you for reading.