Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-10T17:43:08.607Z Has data issue: false hasContentIssue false
  • English
  • Français

Blade element momentum theory extended to model low Reynolds number propeller performance

Part of: APISAT 2015

Published online by Cambridge University Press:  03 May 2017

R. MacNeill  and
D. Verstraete
R. MacNeill*
Affiliation:
The University of Sydney, School of Aerospace Mechanical and Mechatronic Engineering, Sydney, Australia
D. Verstraete
Affiliation:
The University of Sydney, School of Aerospace Mechanical and Mechatronic Engineering, Sydney, Australia
*
rens.macneill@sydney.edu.au
Get access Rights & Permissions [Opens in a new window]

Abstract

Propellers are the predominant propulsion source for small unmanned aerial vehicles. At low advance ratios, large sections of the propeller blade can be stalled, and the Reynolds number faced by each blade can be low. This leads to difficulties in modelling propeller performance, as the aerodynamic models coupled with blade element methods usually only provide aerodynamic data for an assumed aerofoil section, for a small angle-of-attack range and for a single Reynolds number, while rotational effects are often ignored. This is specifically important at low advance ratios, and a consistent evaluation of the applicability of various methods to improve aerodynamic modelling is not available. To provide a systematic appraisal, three-dimensional (3D) scanning is used to obtain the aerofoil sections that make up a propeller blade. An aerodynamic database is formed using each extracted aerofoil section, across a wide range of angles of attack and Reynolds numbers. These databases are then modified to include the effects of rotation. When compared with experimental results, significant improvement in modelling accuracy is shown at low advance ratios relative to a generic blade element-momentum model, particularly for smaller propellers. Notably, when considering small propeller performance, efficiency modelling is improved from within 30% relative to experimental data to within 5% with the use of the extended blade element momentum theory method. The results show that combining Viterna and Corrigan flat plate theory with the Corrigan and Schillings stall delay model consistently yields the closest match with experimental data.

Keywords

Propellerunmanned aircraftblade elementlow Reynolds number
Type
Research Article
Information
The Aeronautical Journal , Volume 121 , Issue 1240 , June 2017 , pp. 835 - 857
Copyright
Copyright © Royal Aeronautical Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This is an adaptation of a paper first presented at the 2015 Asia-Pacific International Symposium on Aerospace Technology in Cairns, Australia

References

REFERENCES

1. Glassock, R.R. Design, Modelling and Measurement of Hybrid Powerplant for Unmanned Aerial Vehicles (UAVs), Master’s Thesis, 2012, Queensland University of Technology.Google Scholar
2. Verstraete, D., Gong, A., Lu, D.D.-C. and Palmer, J.L. Experimental investigation of the role of the battery in the AeroStack hybrid, fuel-cell-based propulsion system for small unmanned aircraft systems, Int J Hydrogen Energy, January 2015, 40, (3), pp 1598-1606.CrossRefGoogle Scholar
3. Gong, A., Palmer, J. L., Brian, G., Harvey, J.R. and Verstraete, D. Performance of a hybrid, fuel-cell-based power system during simulated small unmanned aircraft missions, Int J Hydrogen Energy, July 2016, 41, (26), pp 11418–11426.CrossRefGoogle Scholar
4. Hendrick, P., Hallet, L. and Verstraete, D. Comparison of propulsion technologies for a HALE airship, AIAA Aviation Technology, Integration, and Operations Conference, 2007, 1, pp 527–534.Google Scholar
5. Verstraete, D. and Bowkett, C. Impact of heat transfer on the performance of micro gas turbines, Applied Energy, 2015, 138, pp 445–449.Google Scholar
6. Mair, W.A. and Birdsall, D.L. Aircraft Performance, 1992, Cambridge University Press.Google Scholar
7. Gur, O. and Rosen, A. Propeller performance at low advance ratio, AIAA Journal of Aircraft, March 2005, 42, (2), pp 435-441.Google Scholar
8. Morgado, M., Silvestre, M.Â.R. and Páscoa, J.C. Validation of new formulations for propeller analysis, AIAA J Propulsion and Power, January 2015, 31, (1), pp 467-477.Google Scholar
9. Uhlig, D.V. and Selig, M.S. Post stall propeller behavior at low Reynolds numbers, AIAA Aerospace Sciences Meeting and Exhibit, January 2008, Reno, Nevada, US.CrossRefGoogle Scholar
10. Tangler, J.L. and Ostowari, C. Horizontal axis wind turbine post stall airfoil characteristics synthesization, Tech Rep, 1991, United States Department of Energy.Google Scholar
11. Montgomerie, B. Drag coefficient distribution on a wing at 90 degrees to the wind, Tech Rep, 1996, The Energy Research Centre of the Netherlands.Google Scholar
12. Lindenburg, C. Aerodynamic airfoil coefficients at large angles of attack, IEA Symposium on the Aerodynamics of Wind Turbines, 2000, Colorado, US.Google Scholar
13. Ol, M., Zeune, C. and Logan, M. Analytical - experimental comparison for small electric unmanned air vehicle propellers, AIAA Applied Aerodynamics Conference, August 2008, Honolulu, Hawaii, US.Google Scholar
14. Anemaat, W.A.J., Schuurman, M., Liu, W. and Karwas, A. Aerodynamic design, analysis and testing of propellers for small unmanned aerial vehicles, Royal Aeronautical Society Applied Aerodynamics Conference, 2016, Bristol, UK.CrossRefGoogle Scholar
15. Critzos, C.C., Heyson, H.H. and Boswinkle, R.W. Jr. Aerodynamic characteristics of NACA 0012 airfoil section at angles of attack from 0° to 180°. Tech Rep, January 1955, National Advisory Committee for Aeronautics.Google Scholar
16. Ostowari, C. and Naik, D. Post-stall wind tunnel data for NACA 44XX series airfoil sections. Tech Rep, January 1985, Rockwell International Corp.CrossRefGoogle Scholar
17. Viterna, L.A. and Corrigan, R.D. Fixed pitch rotor performance of large horizontal axis wind turbines, Tech Rep, 1982, NASA Lewis Research Center.Google Scholar
18. Montgomerie, B. Methods for root effects, tip effects and extending the angle of attack range to plus/minus 180 degrees, with application to aerodynamics for blades on wind turbines and propellers, Tech Rep, June 2004, Swedish Defense Research Agency.Google Scholar
19. Lindenburg, C. Investigation into rotor blade aerodynamics, Tech Rep, July 2003, National Renewable Energy Laboratory.Google Scholar
20. Spera, D.A. Models of lift and drag coefficients of stalled and unstalled airfoils in wind turbines and wind tunnels, Tech Rep, 2008, National Aeronautics and Space Administration.Google Scholar
21. Marten, D. and Wendler, J. Qblade guidelines, Tech Rep, 2013, Technical University of Berlin, Germany.Google Scholar
22. Anderson, J.D. Fundamentals of Aerodynamics. McGraw Hill Series in Aeronautical and Aerospace Engineering, 2nd ed, 1991, McGraw-Hill.Google Scholar
23. McCrink, M.H. and Gregory, J.W. Blade element momentum modeling of low-Re small UAS electric propulsion systems, AIAA Aviation, 33rd AIAA Applied Aerodynamics Conference, June 2015, Dallas, Texas, US.CrossRefGoogle Scholar
24. Liller, W. The Design of Small Propellers Operating at Low Reynolds Numbers and Associated Experimental Evaluation, Master’s Thesis, August 2015, Baylor University.Google Scholar
25. Himmelskamp, H. Profile investigations on a rotating airscrew, MAP Volkenrode, Reports and Translation, 1947, (832).Google Scholar
26. Snel, H., Houwink, R. and Bosschers, J. Sectional prediction of lift coefficients on rotating wind turbine blades in stall, Tech Rep ECN-C–93-052, December 1994, National Aerospace Laboratory (NLR), Netherlands.Google Scholar
27. Corrigan, J.J. and Schillings, J.J. Empirical model for stall delay due to rotation, Tech Rep, January 1994, Bell Helicopters, San Francisco, California, US.Google Scholar
28. Tangler, J.L. and Selig, M.S. An evaluation of an empirical model for stall delay due to rotation for HAWTS, Windpower, June 1997.Google Scholar
29. Phillips, W.F. Mechanics of Flight, 2nd ed, 2012, Wiley.Google Scholar
30. Burdett, T., Gregg, J., and Van Treuren, K. An examination of the effect of Reynolds number on airfoil performance, ASME International Conference on Energy and Sustainability, August 2011, Washington, DC, US.Google Scholar
31. Gregg, J., Burdett, T. and Van Treuren, K. Design considerations, performance enhancing techniques, and wind tunnel testing for small scale, low Reynolds number wind turbines, ASME IMECE, November 2011, Denver, Colorado, US.Google Scholar
32. Van Treuren, K. Small-scale wind turbine testing in wind tunnels under low Reynolds number conditions, ASME J Energy Resources Technology, September 2015, 137, (5), 051208.Google Scholar
33. Johnson, W. Rotorcraft Aeromechanics, 2013, Cambridge University Press.Google Scholar
34. Tong, W. Wind Power Generation and Wind Turbine Design, 2010, Wessex Institute of Technology.Google Scholar
35. Drela, M. QPROP formulation, Tech Rep, June 2006, Massachusetts Institute of Technology.Google Scholar
36. Leishman, J.G. Principles of Helicopter Aerodynamics, 2006, Cambridge Aerospace. Cambridge University Press.Google Scholar
37. Drela, M. XFOIL: An Analysis and Design System for Low Reynolds Number Airfoils, 1989, Springer-Verlag.Google Scholar
38. Maughmer, M.D. and Coder, J.G. Comparisons of theoretical methods for predicting airfoil aerodynamic characteristics, Tech Rep, August 2010, The Pennsylvania State University.Google Scholar
39. Chen, W. and Bernal, L.P. Design and performance of low Reynolds number airfoils for solar-powered flight, AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada, US, January 2008, (46).Google Scholar
40. Borst, H.V. Aerodynamic design and analysis of propellers for mini-remotely piloted air vehicles: Volume 1 - open propellers, Tech Rep, ADA050593, January 1978, Applied Technology Laboratory, U.S. Army Research and Technology Laboratories.Google Scholar
41. van Rooij, R.P.J.O.M. Modification of the boundary layer calculation in RFOIL for improved airfoil stall prediction, Tech Rep, 1996, Institute for Wind Energy, Faculty of Civil Engineering, Delft University of Technology, Delft, The Netherlands.Google Scholar
42. Ramanujam, G., Özdemir, H. and Hoeijmakers, H. Improving airfoil drag prediction, AIAA Journal of Aircraft, 2016, 53, (6), pp 1844-1852.CrossRefGoogle Scholar
43. Ramanujam, G. and Özdemir, H. Improving airfoil lift prediction, AIAA SciTech Forum: 35th Wind Energy Symposium, January 2017, Grapevine, Texas, US.Google Scholar
44. Simons, M. Model Aircraft Aerodynamics, 4th ed, 1999, Special Interest Model Books.Google Scholar
45. Timmer, W.A. Two-dimensional low-Reynolds number wind tunnel results for airfoil NACA 0018, Wind Engineering, 2008, 32, (6), pp 525-537.Google Scholar
46. Xu, G. and Sankar, L. Application of a viscous flow methodology to the NREL phase-IV rotor, ASME Wind Energy Symposium, Reno, Nevada, US, 2002, pp 83-93.Google Scholar
47. Glauert, H. Airplane Propellers, Aerodynamic Theory - A General Review of Progress, volume 4, Julius Springer, 1935.Google Scholar
48. Brandt, J.B. Small-Scale Propeller Performance at Low Speeds, Master’s Thesis, 2005, University of Illinois at Urbana-Champaign, Urbana, Illinois, US.Google Scholar
49. APC Propellers. Engineering design process used to develop apc propellers, June 2016. URL https://www.apcprop.com/Articles.asp?ID=262airfoil.Google Scholar