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Study of brownout prediction of helicopters based on the analysis of ground effect flow field eigen quantities

Published online by Cambridge University Press:  28 April 2025

L.Y. Qian Open the ORCID record for L.Y. Qian [Opens in a new window] ,
G.H. Xu  and
Y.J. Shi
L.Y. Qian
Affiliation:
National Key Laboratory of Helicopter Aeromechanics, Nanjing University of Aeronautics and Astronautics, Nanjing, China
G.H. Xu*
Affiliation:
National Key Laboratory of Helicopter Aeromechanics, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Y.J. Shi
Affiliation:
National Key Laboratory of Helicopter Aeromechanics, Nanjing University of Aeronautics and Astronautics, Nanjing, China
*
Corresponding author: G.H. Xu; Email: [email protected]
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Abstract

The ground effect phenomenon caused by helicopters in proximity to the ground results in helicopters experiencing a distinctive phenomenon known as brownout in a multiphase environment. However, the substantial computational volume associated with current numerical simulations conducted using the coupled CFD-DEM method restricts the scope of current studies on brownout to individual cases. Consequently, it is currently not feasible to make realistic predictions regarding the impact of rotor design parameters on brownout. In order to make full use of the conclusions of the existing theoretical studies and, at the same time, to save computational resources as much as possible, this paper proposes a novel approach of brownout prediction based on the analysis of the helicopter ground effect flow field eigen quantities in order to gain insight into the nature of the phenomenon of brownout. Firstly, a new approach for predicting helicopter brownout is constructed for the well-developed late-stage ground effect flow field. This is achieved by analysing the rotor flow field characteristics and combining the Greely-Iversen expression in particle dynamics to extract the eigen quantities of each region of the flow field. Secondly, the results of the flow field calculations at different heights are analysed using the aforementioned approach. The effectiveness of the approach is demonstrated by comparing the results with those of CFD-DEM calculations. Ultimately, the results of the numerical simulation of the flow field, when combined with the established prediction approach, allow for the prediction of the brownout phenomenon generated by multiple blade tip shape rotors with different design parameters. Furthermore, a comparative study of the influence of blade tip vortex strength on the development of brownout is conducted, which demonstrates that the rotors of the backswept blade tip have been observed to exert a certain positive effect on the inhibition of brownout, although this influence is limited. In contrast, the rotors of the anhedral blade tip have been seen to transport smaller but larger sand particles with greater efficiency and to re-enter the brownout cycle with greater directness. The rotors of the forward-swept blade tip have been found to cause larger sand particles to participate in the brownout, while simultaneously weakening the transport capacity, which has been resulted in a reduction in the overall degree of brownout.

Keywords

Computational fluid dynamicsRotorBrownoutGround effect
Type
Research Article
Information
The Aeronautical Journal , First View , pp. 1 - 24
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Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

Collins, P and Moore, C. Solutions to helicopter blade erosion-Improving aircraft availability and reducing costs, 2014.Google Scholar
Acquisition and Technology Programs Task Force (ATPTF). Department of Defense Aviation Safety Technologies Report. Washington, DC: Defense Safety Oversight Council, Office of the Under Secretary of Defense for Personnel and Readiness 2009,2009, pp 22–23.Google Scholar
Light, J.S. Tip vortex geometry of a hovering helicopter rotor in ground effect, J. Am. Helicopter Soc., 1993, 38, (2), pp 34–42.CrossRefGoogle Scholar
Lee, T.E., Leishman, J.G. and Ramasamy, M. Fluid dynamics of interacting blade tip vortices with a ground plane, J. Am. Helicopter Soc., 2010, 55, (2), pp 22005–22005.CrossRefGoogle Scholar
Milluzzo, J. Effects of Blade Tip Shape on Rotor In-Ground-Effect Aerodynamics, PhD thesis, University of Maryland, College Park, 2011.Google Scholar
Greeley, R., Balme, M.R., Iversen, J.D., Metzger, S., Mickelson, R., Phoreman, J. and White, B. Martian dust devils: Laboratory simulations of particle threshold, J. Geophys. Res. Planets, 2003, 108, (E5), p 5041.CrossRefGoogle Scholar
Johnson, B., Leishman, J.G. and Sydney, A. Investigation of sediment entrainment using dual-phase, high-speed particle image velocimetry, J. Am. Helicopter Soc., 2010, 55, (4), pp 42003–42003.CrossRefGoogle Scholar
Johnson, B. Mechanisms of Sediment Entrainment and Transport in Rotorcraft Brownout, Master’s thesis, University of Maryland, College Park, 2009.Google Scholar
Pulla, D. and Conlisk, T. The long time structure of the rotor wake in ground effect, 43rd AIAA Aerospace Sciences Meeting and Exhibit, 2005, p 1408.CrossRefGoogle Scholar
Kalra, T.S., Lakshminarayan, V.K. and Baeder, J.D. CFD validation of micro hovering rotor in ground effect, AHS International Specialists Conference Proceedings on Aeromechanics, San Francisco, CA, May 2010.Google Scholar
Thomas, S. and Baeder, J. Modeling the two-phase flowfield beneath a hovering rotor on graphics processing units using a FVM-RANS hybrid methodology, 21st AIAA Computational Fluid Dynamics Conference, 2013, p 2853.CrossRefGoogle Scholar
Shao, Y., Raupach, M.R. and Findlater, P.A. Effect of saltation bombardment on the entrainment of dust by wind, J. Geophys. Res. Atmos., 1993, 98, (D(7)), pp 12719–12726.CrossRefGoogle Scholar
Shao, Y. and Lu, H. A simple expression for wind erosion threshold friction velocity, J. Geophys. Res. Atmos., 2000, 105, (D(17)), pp 22437–22443.CrossRefGoogle Scholar
Syal, M. and Leishman, J.G. Comparisons of predicted brownout dust clouds with photogrammetry measurements, 67th Annual Forum Proceedings of the American Helicopter Society, Virginia Beach, VA, May 2011.Google Scholar
Syal, M. Development of a Lagrangian-Lagrangian Methodology to Predict Brownout Dust Clouds, PhD thesis, University of Maryland, College Park, 2012.Google Scholar
Phillips, C. and Brown, R.E. Eulerian simulation of the fluid dynamics of helicopter brownout, J. Aircraft, 2009, 46, (4), pp 1416–1429.CrossRefGoogle Scholar
Hu, J.P., Xu, G.H., Shi, Y.J. and Wu, L. Formation mechanism of brownout in full-scale helicopter based on CFD-DEM couplings numerical simulation, Acta Aeronaut. Sin, 2020, 41, (3), p 123363.Google Scholar
Hu, J., Xu, G., Shi, Y. and Huang, S. The influence of the blade tip shape on brownout by an approach based on computational fluid dynamics, Eng. Appl. Comput. Fluid Mech., 2021, 15, (1), pp 692–711.Google Scholar
Tan, J.F., He, L., Yu, L.J. and Zhou, G.C. Helicopter brownout modeling based on viscous vortex particle and sand particle DEM, Acta Aeronaut. Sin, 2022, 43, (08), pp 357–367.Google Scholar
Tan, J.F., Yon, T., He, L., Yu, L.J. and Wang, C. Accelerated method of helicopter brownout with particle-particle collisions, Aerospace Sci. Technol., 2022, 124, p 107511.CrossRefGoogle Scholar
Tan, J.F., Sun, Y.M. and Barakos, G.N. Vortex approach for downwash and outwash of tandem rotors in ground effect, J. Aircraft, 2018, 55, (6), pp 2491–2509.CrossRefGoogle Scholar
Norouzi, H.R., Zarghami, R, Sotudeh-Gharebagh, R. and Mostoufi, N. Coupled CFD-DEM Modeling: Formulation, Implementation and Application to Multiphase Flows, 2016, John Wiley Sons.CrossRefGoogle Scholar
Hu, H. Computational analysis of effects of blade shapes on tip-vortices, Adv. Eng. Software, 2003, 34, (5), pp 279–286.CrossRefGoogle Scholar
Brocklehurst, A. and Barakos, G.N. A review of helicopter rotor blade tip shapes, Progr. Aerospace Sci., 2013, 56, pp 35–74.CrossRefGoogle Scholar
Pátý, M., Cernat, B.C., De Maesschalck, C. and Lavagnoli, S. Experimental and numerical investigation of optimized blade tip shapes—Part II: Tip flow analysis and loss mechanisms, J. Turbomach., 2019, 141, (1), p 011007.CrossRefGoogle Scholar