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A semi-analytical approach for flutter analysis of a high-aspect-ratio wing

Published online by Cambridge University Press:  07 August 2020

R.F. Latif ,
M.K.A. Khan Open the ORCID record for M.K.A. Khan [Opens in a new window] ,
A. Javed ,
S.I.A. Shah  and
S.T.I. Rizvi
R.F. Latif
Affiliation:
CAE, National University of Sciences and Technology (NUST), Department of Aerospace Engineering, Islamabad, Pakistan
M.K.A. Khan*
Affiliation:
CAE, National University of Sciences and Technology (NUST), Department of Aerospace Engineering, Islamabad, Pakistan
A. Javed
Affiliation:
CAE, National University of Sciences and Technology (NUST), Department of Aerospace Engineering, Islamabad, Pakistan
S.I.A. Shah
Affiliation:
CAE, National University of Sciences and Technology (NUST), Department of Aerospace Engineering, Islamabad, Pakistan
S.T.I. Rizvi
Affiliation:
Air University, Aerospace and Aviation Campus, Kamra, Pakistan
*
[email protected]
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Abstract

We present a hybrid, semi-analytical approach to perform an eigenvalue-based flutter analysis of an Unmanned Aerial Vehicle (UAV) wing. The wing has a modern design that integrates metal and composite structures. The stiffness and natural frequency of the wing are calculated using a Finite Element (FE) model. The modal parameters are extracted by applying a recursive technique to the Lanczos method in the FE model. Subsequently, the modal parameters are used to evaluate the flutter boundaries in an analytical model based on the p-method. Two-degree-of-freedom bending and torsional flutter equations derived using Lagrange’s principle are transformed into an eigenvalue problem. The eigenvalue framework is used to evaluate the stability characteristics of the wing under various flight conditions. An extension of this eigenvalue framework is applied to determine the stability boundaries and corresponding critical flutter parameters at a range of altitudes. The stability characteristics and critical flutter speeds are also evaluated through computational analysis of a reduced-order model of the wing in NX Nastran using the k- and pk-methods. The results of the analytical and computational methods are found to show good agreement with each other. A parametric study is also carried out to analyse the effects of the structural member thickness on the wing flutter speeds. The results suggest that changing the spar thickness contributes most significantly to the flutter speeds, whereas increasing the rib thickness decreases the flutter speed at high thickness values.

Keywords

AeroelasticityFlutterFinite element modellingHigh aspect ratioReduced order modelUAV
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1284 , February 2021 , pp. 410 - 429
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

REFERENCES

Tsach, S., Tatievsky, A. and London, L. Unmanned Aerial Vehicles (UAVs), Encyclopedia of Aerospace Engineering, August 2006, pp 487–494.Google Scholar
Shakhatreh, H., Sawalmeh, A.H., Al-Fuqaha, A., Dou, Z., ALmaita, E., Khalil, I., Othman, N., Shamsiah, N.S., Khreishah, A. and Guizani, M. Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges, IEEE Access, 2019, 7, (5), pp 48572–48634.CrossRefGoogle Scholar
Mohammad, F., Idries, A., Mohamed, N., Al-JAroodi, A. and Jwahar, I. UAVs for smart cities: Opportunities and challenges, IEEE International Conference on Unmanned Aircraft Systems (ICUAS), 2014, Orlando, USA.Google Scholar
Gomez-Candon, D., De Castro, A.I. and Lopez-Granados, F. Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat, Precis. Agric., 2014, 15, (1), pp 44–56.CrossRefGoogle Scholar
Panagiotou, P., Tsavlidis, I. and Yakinth, K. Conceptual design of a hybrid solar MALE UAV, Aerosp. Sci. Technol., 2016, 53, pp 207–219.CrossRefGoogle Scholar
Gorniak, C., Goraj, Z.J. and Olszanski, B. Research and selection of MALE wing profile, Aircr. Eng. Aerosp. Technol., 2019, 91, (2), pp 264–271.CrossRefGoogle Scholar
Anderson, J.D. Jr, Aircraft Performance and Design, McGraw Hill, 2012.Google Scholar
Raymer, D. Aircraft Design: A Conceptual Approach, AIAA, 2012.CrossRefGoogle Scholar
Panagiotou, P., Kaparos, P. and Yakinthos, K., Winglet design and optimization for a MALE UAV using CFD, Aerosp. Sci. Technol., 2014, 39, pp 190–205.CrossRefGoogle Scholar
Abbas, A., De Vicente, J. and Valero, E., Aerodynamic technologies to improve aircraft performance, Aerosp. Sci. Technol., 2013, 28, (1), pp 100–132.CrossRefGoogle Scholar
Afonso, F., Vale, J., Oliveira, E., Lau, F. and Suleman, A. A review on non-linear aeroelasticity of high aspect-ratio wings, Prog. Aerosp. Sci., 2017, 89, pp 40–57.CrossRefGoogle Scholar
Kehoe, M. A Historical Overview of Flight Flutter Testing: NASA TM-4720, October 1995, p 995.Google Scholar
Hodges, D.H. and Pierce, G.A. Introduction to Structural Dynamics and Aeroelasticity, Cambridge University Press, 2011.CrossRefGoogle Scholar
Dowell, E. H. A Modern Course in Aeroelasticity, Springer, 2015.Google Scholar
Fung, Y.C. An Introduction to the Theory of Aeroelasticity, Dover Publications, 2008.Google Scholar
Shubov, M.A. Flutter phenomenon in aeroelasticity and its mathematical analysis, J. Aerosp. Eng., 2019, 19, (1), pp 1–12.Google Scholar
Anderson, K.R., White, K. and Neal, J. Survey of active aeroelastic control for flutter suppression, ASME International Mechanical Engineering Congress and Exposition, Anaheim, USA, 2004.Google Scholar
Livne, E. Aircraft active flutter suppression: State of the art and technology maturation needs, J. Aircr., 2018, 55, (1), pp 410–452.CrossRefGoogle Scholar
Zhao, Y.H. Flutter suppression of a high aspect-ratio wing with multiple control surfaces, J. Sound Vibr. 2009, 324, (3–5), pp 490–513.CrossRefGoogle Scholar
Marchetti, L., De Gaspari, A., Riccobene, L., Toffol, F., Fonte, F., Ricci, S., Mantegazza, P. Livne, E. and Hinson, K.A. Active flutter suppression analysis and wind tunnel studies of a commercial transport configuration, AIAA Scitech Forum, Orlando, USA, 2020.Google Scholar
Ghasemikaram, A.H., Mazidi, A., Fazel, M.R. and Fazelzadeh, S.A. Flutter suppression of an aircraft wing with a flexibly mounted mass using magneto-rheological damper. Proc. Inst. Mech. Eng. G J. Aerosp. Eng., 2020, 234, (3), pp 827–839.CrossRefGoogle Scholar
Friedmann, P.P., Renaissance of aeroelasticity and its future, J. Aircr., 1999, 36, (1), pp 105–121 CrossRefGoogle Scholar
Garrick, I.E. and Reed, W.H. III Historical development of aircraft flutter, J. Aircr., 2018, 18, (11), pp 897–912.CrossRefGoogle Scholar
Edwards, J.W. and Wieseman, C.D. Flutter and divergence analysis using the generalized aeroelastic analysis method, J. Aircr., 2008, 45, (3), pp 906–915.CrossRefGoogle Scholar
Livne, E. Aircraft active flutter suppression: State of the art and technology maturation needs, J. Aircr., 2018, 55, (1), pp 410–452.Google Scholar
Njuguna, J. Flutter prediction, suppression and control in aircraft composite wings as a design prerequisite: A survey, Struct. Cont. Health Monitor. Off. J. Int. Assoc. Struct. Cont. Monitor. Eur. Assoc. Cont. Struct., 2007, 15, (5), pp 715–758.Google Scholar
Schuster, D.M., Liu, D.D. and Huttsell, L.J. Computational aeroelasticity: Success, Progress, Challenge, J. Aircr., 2003, 40, (5), pp 843–856.CrossRefGoogle Scholar
Zhang, W., Wang, B., Ye, Z. and Quan, J. Efficient method for limit cycle flutter analysis based on nonlinear aerodynamic reduced-order models, AIAA J., 2012, 50, (5), pp 1019–1028.CrossRefGoogle Scholar
Eller, D. Flutter equation as a piecewise quadratic eigenvalue problem, J. Aircr., 2009, 46, (3), pp 1068–1070.CrossRefGoogle Scholar
Voss, G., Schaefer, D. and Vidy, C. Investigation on flutter stability of the DLR-F19/SACCON configuration, Aerosp. Sci. Technol., 2019, 93, p 105320.CrossRefGoogle Scholar
Gadomski, J., Hernik, B. and Goraj, Z. Analysis and optimisation of a MALE UAV loaded structure, Aircr. Eng. Aerosp. Technol., March 2006.CrossRefGoogle Scholar
Amsallem, D. and Farhat, C. Interpolation method for adapting reduced-order models and application to aeroelasticity, AIAA J., 2008, 46, (7), pp 1803–1813.CrossRefGoogle Scholar
Bostic, S.W. Lanczos Eigensolution Method for High-Performance Computers: NASA Technical Memorandum No 104108. Langley Research Center, September, 1991.Google Scholar