Computational Fluid Dynamics (CFD) Analysis of a Horizontal Axis Tidal Turbine (Update 01)

     In this post, the results of numerical simulations carried out on a three-blade horizontal-axis tidal turbine blades are made available. These simulations are a part of larger project relating to a horizontal-axis tidal turbine.

 

     The turbine under investigation had a diameter of 4 m. The aero-foils employed include the NACA 4424 (chord length 0.25 m), NACA 4420 (chord length 0.2312 m), NACA 4418 (chord length 0.2126 m), NACA 4417 (chord length 0.1938 m), NACA 4416 (chord length 0.175 m), NACA 4415 (chord length 0.1562 m), NACA 4414 (chord length 0.1376 m), NACA 4413 (chord length 0.1188 m) and the NACA 4412 (chord length 0.1 m) at a distance of 0.4 m, 0.6 m, 0.8 m, 1 m, 1.2 m, 1.4 m, 1.6 m, 1.8 m, 2 m from the blade root, respectively [1].

 

     The numerical simulations were carried out on SolidWorks Flow Simulation Premium software. The software employs κ-ε turbulence model with damping functions, SIMPLE-R (modified) as the numerical algorithm and second order upwind and central approximations as the spatial discretization schemes for the convective fluxes and diffusive terms. The time derivatives are approximated with an implicit first-order Euler scheme. To predict turbulent flows, the Favre-averaged Navier-Stokes equations are used. The software employs a Cartesian mesh which is created using the immersed boundary method.

 

     The simulations were carried out using the Local rotating region(s) (Sliding) technique. The mesh had a total of 589,763 cells. 132,045 cells were at the turbine blade-rotating region boundary. While the process of mesh generation, a mesh control was employed to refine the mesh near the turbine blades and at the boundary of the rotating region and the stationery computational domain. To refine the mesh for the mesh independent test, the curvature level was increased i.e. the mesh in the areas of interest was refined by a factor of 8. As a result, the refined mesh had a total of 916,577 cells. A total of 221,978 were present around the turbine blade. The computational mesh around the turbine blade is shown in Fig. 1. The refined mesh in the areas of high gradients is also clearly visible. The computational domain had dimensions of 2D x 2D x 2.4D, where D is the diameter of the turbine. The dimensions for the computational domain resemble to those in [2].

     Fig. 2 shows computational domain around the turbine blades. In Fig. 2, the curved teal arrow represents the direction of rotation of the turbine. The green arrows represent the respective co-ordinate directions. The brown arrow represents the direction of the force of gravity. The blue arrow represents the direction of the fluid velocity. The circular disc represents the rotating region.

 

Fig. 1, The computational mesh.

    

Fig. 2, The computational domain and the orientation of the boundary conditions.

 

     The simulations were carried out for a total of 5 tip-speed ratios for the turbine ranging from 2 to 10. The fluid; water, velocity was set at 2 m/s. The results are indeed, mesh independent. The mesh independence test was conducted on the design point of the turbine i.e. at the TSR of 6. The plot between the turbine tip-speed ratio; TSR, and the co-efficient of power is shown in Fig. 3. It can be clearly seen from Fig. 3 that the results are in close agreement with the results from [1, 3]. The CFD results from both studies are lower then the BEM, Blade-Element Momentum, results because the three-dimensional effects are not considered while implementing the BEM method.

 

Fig. 3, Turbine efficiency plot.

 

     Fig. 4 shows velocity streamlines colored by velocity magnitude, both of these features are drawn relative to the rotating reference frame, around the turbine blade cross-section at various tip-speed ratios. It can be seen from Fig. 4 that the turbine stalls at TSR of 2 due to a large positive angle of attack. It can also be seen that as the TSR increases, the angle of attack on the blade decreases, it is because of this reason that the power output from the turbine increases.

 

 

Fig. 4, Row 1, L-R; TSR of 2 and 4. Row 2, L-R; TSR of 6 and 8. Row 3, TSR of 10.

 

     Thank you for reading. If you would like to collaborate with research projects, please reach out.

     [1] Binoe E. Abuan, and Robert J. Howell, "The Influence of Unsteady Flow to the Performance of a Horizontal Axis Tidal Turbine," Proceedings of the World Congress on Engineering. London, 2018.

     [2] Ibrahim, I. H., and T. H. New, "A numerical study on the effects of leading-edge modifications upon propeller flow characteristics," Proceedings of Ninth International Symposium on Turbulence and Shear Flow Phenomena. Melbourne, 2015.
     [3] Bahaj, A., Batten, W., & McCann, J. (2007). Experimental verifications of numerical predictions for the hydrodynamic performance of horizontal axis marine current turbines. Renewable Energy, 2479-2490.

Update 01:

     CFD post processing added. One more TSR simulated.

Steady-State VS Transient Propeller Numerical Simulation Comparison

     This post is about the comparison between steady-state and transient computational fluid dynamics analysis of two different propellers. The propellers under investigation are 11x7 and 11x4.7 propellers. The first number in the propeller nomenclature is the propeller diameter and the second number represents the propeller pitch, both parameters are in inch. The transient analysis was carried out using the sliding mesh technique while the steady-state results were obtained by the local rotating region-averaging method. For details about 11x7 propeller click here, for the details about 11x4.7 propeller, click here.

 

     As expected, the propeller efficiencies of transient and steady-state analysis are within 0.9% of each other, as shown in Fig. 1-2. Therefore, it is advised to simulate propellers and horizontal axis wind turbines using the steady-state technique as long as no time-dependent boundary conditions are employed.

 

Fig. 1, Propeller efficiency plot.

  

 Fig. 2, Propeller efficiency plot.

 

     It can be seen from Fig. 3-4 that time taken by the steady-state simulation to converge is on average 42.37% less that the transient analysis.  The steady-state analysis takes considerably less time to give a solution then a transient analysis.

 

Fig. 3, Solution time.

 

Fig. 4, Solution time.

 

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

SolidWorks Flow Simulation Premium: Propeller/Horizontal Axis Wind Turbine CFD Tutorial

The tutorial is in the attached video. Analysis such as: 11x7 Aeronautic Propeller Characteristics, 11x4.7 Aeronautic Propeller Characteristics and Wind Turbine SolidWorks Flow Simulation Premium Computational Fluid Dynamics are setup using the same method.

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, η_prop = 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.

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, η_prop = 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.

Desktop Computer Part List (Summer 2018-Pakistan Market)

     At the time of writing, 1 USD = Rs. 121.936. The prices mentioned in this post are based on the local market prices of computer components in Pakistan. Please remember that, prices vary from city-to-city within the country and shop-to-shop within a city. This is the reason why a price range is mentioned.

CPUs

     Intel Core i7-8700 for Rs. 41,500-Rs. 43,500. Top of the line processor from Intel. Always prefer a Core i7 or a Core i9 processor.

     Intel Core i5-8400 Processor Rs. 26,000-Rs. 28,000. Only buy this processor if there is a budget constraint.

Motherboard

     Gigabyte Z370 AORUS Gaming 3 for Rs. 21,200-Rs. 21,500. This motherboard has many USB ports and also comes equipped with a USB type-C port and M.2 slots etc. for future proofing.

Storage

     WD Blue 500GB Solid State Drive - WDS500G1B0A for Rs. 16,500-Rs. 17,500. Please do not buy a hard drive with rotating mechanism, it's 2018! When later in the year the SSD's prices go down, probably around November-December 2018, then buy another ~500 GB SSD. Do not waste money on a legacy hard drive.

Memory

     Corsair Vengeance LPX 16GB (1x16GB) DDR4 DRAM 3000MHz Rs. 25,800-Rs. 32,000. Please do not buy two sticks of 8 GB each. Save the remaining memory slots for future upgrading. Memory prices will fall significantly in October-November 2018 once the Chinese memory plants become operational. Don't fall for the shop keepers trickery. A common ploy employed by shopkeepers is that 1x16GB memory modules don't work in single channel mode for the 2400 MHz+ modules. It works perfectly well.

Casing

     Corsair Carbide Series® 100R Mid-Tower Case Rs.6,650-Rs. 7,500. This is the best option, really. Don't waste money on casing, it's just a box.

Power Supply

     Corsair VS550 - 550 Watt Power Supply Rs.5,800 -Rs. 6,000. A 550 Watt power supply for an i7 8700 CPU, 4 sticks of 1x16GB DDR4 memory modules, 1 SSD and up to a GTX 1x70 level graphic cards without any over clocking and 16 hours per day usage will be enough. May be this power supply will even be enough for GTX 1180 graphic card, as the graphic card chips are becoming more and more energy efficient. Yet again, do not fall for the shop keepers ploys.

Graphic Card

     Wait for the graphic new graphic cards from NVidia. The new cards are just around the corner. Local shops in Pakistan are selling 2 year old graphic cards, the GTX 10 series, at much inflated prices as compared to the rest of the world.

Conclusion

     This system will last at least 5 years, in terms of gaming with a GTX 1x70 level graphics card. It will even perform well for 10+ years if you keep upgrading it and take care of it cooling wise. Upgrade to a PCIe-NVMe SSD down the road when the prices drop, add more memory and update the graphic card every 5 years etc. Currently, the system will cost anywhere between Rs. 118,000 -Rs. 128,000, depending on you city and the shop, with an i7 processor.

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

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 K_T = coefficient of thrust, 10K_Q = coefficient of torque multiplied by a factor of 10, η_prop = 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.