Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-25T23:02:06.408Z Has data issue: false hasContentIssue false
  • English
  • Français

Impact of spanwise non-uniform discrete gusts on civil aircraft loads

Published online by Cambridge University Press:  27 February 2019

M. Lone  and
G. Dussart
M. Lone*
Affiliation:
Cranfield University, School of Aerospace Transport and Manufacturing, Bedford, UK
G. Dussart
Affiliation:
Cranfield University, School of Aerospace Transport and Manufacturing, Bedford, UK
*
*[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The drive for increasing flight efficiency is resulting in wing designs that are of higher aspect ratios, lower in weight, increased wingspans and, consequently, require greater attention in the disciplines of aeroelastics and loads. This trend in aircraft design, along with past research experience with flexible aircraft, motivate a review of assumptions in gust models; especially, that of the gust maintaining a uniform spanwise profile. In this paper, the authors investigate the use of spanwise varying 1−cos gust models for loads prediction using a non-linear aeroelastic model of a conventional large transport aircraft. The comparison between a test case using conventional uni-dimensional approach and another, using multidimensional gusts, illustrates the impact of stepping away from traditional discrete tuned gust processes and adding a spanwise varying gust component. A methodology for processing and analysing the loads data arising due to the added dimension is also developed and both envelope and correlated loads are considered. Gust characteristics and resulting load factor are, respectively, considered for comparison between the two models, as both metrics define realistic gust encounters. In this case, it has been shown that spanwise variation of gust profiles leads to lower envelope loads if viewed in terms of conventional gust gradients. However, higher envelope loads are found if the maximum load factors are matched.

Keywords

Discrete gustsLoadsNon-uniformAeroelasticityLarge civil aircraft
Type
Research Article
Information
The Aeronautical Journal , Volume 123 , Issue 1259 , January 2019 , pp. 93 - 120
Copyright
© Royal Aeronautical Society 2019 

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.)

References

1. ATAG. A sustainable flightpath towards reducing emissions, 2012.Google Scholar
2. ACARE. Flightpath 2050—Europe’s Vision for Aviation, 2011.Google Scholar
3. Noll, T.E., Brown, J.M., Perez-Davis, M.E., Ishmael, S.D., Tiffany, G.C. and Gaier, M. Investigation of the Helios prototype aircraft mishap, Tech Rep, January 2004.Google Scholar
4. Houbolt, J.C. Atmospheric turbulence, AIAA 10th aerospace science meetings, 1972, p 23. https://doi.org/10.2514/6.1972-219.Google Scholar
5. Hoblit, F.M. Gust loads on aircraft: concepts and applications. AIAA education series, 1988. https://doi.org/10.2514/4.861888.Google Scholar
6. Authorities. Certification specifications and acceptable means of compliance for large Aeroplanes CS Â25, 2012. https://doi.org/10.1002/9780470664797.Google Scholar
7. Authorities. Airworthiness standards: transport category planes. Federal Aviation Regulations, 2013.Google Scholar
8. Fuller, J.R., Richmond, L.D., Larkins, C.D. and Russell, S.W. Contributions to the development of a power spectral gust design procedure for civil aircraft, Tech. Rep, 1966.Google Scholar
9. Hoblit, F.M., Paul, W., Shelten, J.D. and Ashford, F.E. Development of a power-spectral gust design procedure for civil aircraft, Tech Rep, 1966.Google Scholar
10. Guo, S., De Espinosa de Los Monteros, J. and Liu, Y. Gust alleviation of a large aircraft with a passive twist Wingtip. Aerospace, 2015, 2, pp 135–154. ISSN 2226-4310. https://doi.org/10.3390/aerospace2020135.Google Scholar
11. Castrichini, A., Hodigere Siddaramaiah, V., Calderon, D.E., Cooper, J.E., Wilson, T. and Lemmens, Y. Nonlinear folding wing tips for gust loads alleviation. J Aircraft, 2016, 53, (5), pp 1391–1399. ISSN 0021-8669. https://doi.org/10.2514/1.C033474.Google Scholar
12. Castrichini, A., Hodigere Siddaramaiah, V., Calderon, D.E., Cooper, J.E., Wilson, T. and Lemmens, Y. Preliminary investigation of use of flexible folding wing-tips for static and dynamic loads alleviation, Aeronautical J, 2017, 121, (June), pp 1–18.Google Scholar
13. Wilson, E.B. Theory of an aeroplane encountering gusts, Proceedings of the National Academy of Sciences, 1916, 2, (5), pp 294–297.Google Scholar
14. Kussner, H.G. Stresses produced in airplane wings by gusts. Tech Rep, 1931.Google Scholar
15. Jones, J.H. and Connoly, D.H. Airplane airworthiness – CAM04-civil aeronautic manual, 1941.Google Scholar
16. Pratt, K.G. A revised formula for the calculation of gust loads. Tech Rep, June 1953.Google Scholar
17. Jones, J.G. Studies of time-phased vertical and lateral gusts: development of multiaxis one-minus-cosine gust model, Tech Rep, Washington, DC, October 1999.Google Scholar
18. Pratt, K.G. and Walker, W.G. A revised gust load formula and re-evaluation of V-G data taken on civil transport airplanes from 1933 to 1950, Tech Rep, NACA, 1964.Google Scholar
19. Press, H., Medows, M.T. and Hadlock, I. A re-evaluation of data on atmospheric turbulence and airplane gust loads for application in spectral calculations. NACA Report 1272, Tech Rep, NACA, Washington, DC, 1956.Google Scholar
20. Diederich, F.W. and Drischler, J.A. Effect of spanwise variations in gust intensity on the lift due to atmospheric turbulence, Tech Rep, NACA, Washington, DC, 1957.Google Scholar
21. Eichenbaum, F.D. A general theory of aircraft response to three-dimensional turbulence, J Aircr, 1971, 8, (5), pp 353–360. https://doi.org/10.2514/3.59108.Google Scholar
22. Eichenbaum, F.D. Response of aircraft to three dimensional random turbulence, Tech Rep July 1971–March 1972, 1972.Google Scholar
23. Pratt, K.G. Effect of spanwise variation of turbulence on the normal acceleration of airplanes with small span relative to turbulence scale, Tech Rep, NASA, NASA Langley Research Center Hampton, VA, USA, 1975.Google Scholar
24. Coupry, G. Effect of spanwise variation of gust velocity on airplane response to turbulence, J Aircr, 1972, 9, (8), pp 569–574; ISSN 0021-8669.Google Scholar
25. Teufel, P., Hanel, M. and Well, K.H. Integrated flight mechanic and aeroelastic modelling and control of a flexible aircraft considering multidimensional gust input. Structural Aspects of Flexible Aircraft Control. Defense Technical Information Center, 1999, pp 1–10.Google Scholar
26. Jones, J.G. A relationship between the power spectral density and statistical discrete gust methods of aircraft response analysis, Tech Rep, Royal Aircraft Establishment – TMS, 1984, 347.Google Scholar
27. Jones, J.G. Documentation of the linear statistical discrete gust method, Tech Rep, Office of Aviation Research, Washington, DC, 2004.Google Scholar
28. Authorities. Dynamic gust loads advisory circular, U.S. Department of Transportation Federal Aviation Administration, 2014.Google Scholar
29. Seitz, A., Kruse, M., Wunderlich, T., Bold, J. and Heinrich, L. The DLR Project LamAiR: design of a NLF forward swept wing for short and medium range transport application. 29th AIAA applied aerodynamics conference, June, 2011, pp 1–14. https://doi.org/10.2514/6.2011-3526.Google Scholar
30. Krüger, W.R., Klimmek, T., Liepelt, R., Schmidt, H., Wait, S. and Cumnuantip, S. Design and aeroelastic assessment of a forward-swept wing aircraft, CEAS Aeronautical J, 2014, 5, (4), pp 419–433; ISSN 18695590. https://doi.org/10.1007/s13272-014-0117-0.Google Scholar
31. Bradley, M.K. and Droney, C.K. Subsonic ultra green aircraft research: phase II, Tech Rep, 2012. https://doi.org/2060/20150017039.Google Scholar
32. Porter, D., Stevens, J.N., Roe, K., Kono, S., Kress, D. and Lau, E. Wind environment in the Lee of Kauai Island, Hawaii during trade wind conditions: weather setting for the Helios mishap, Boundary-Layer Meteorol, 2007, 123, pp 463–480. https://doi.org/10.1007/s10546-007-9155-z.Google Scholar
33. Roe, K., Stevens, D. and Porter, J. NASA Helios mishap investigation. Application Briefs 2005. https://doi.org/10.1.1.107.443.Google Scholar
34. DARPA. Broad Agency Announcement (BAA), Vulture II Appendices, Appendix A. 6: Simplified Gust Load Criteria, 2009.Google Scholar
35. Ricciardi, A.P., Patil, M.J., Canfield, R.A. and Lindsley, N. Evaluation of quasi-static gust loads certification methods for high-altitude long-endurance aircraft, J Aircr, 2013, 50, (2), pp 457–468; ISSN 0021-8669. https://doi.org/10.2514/1.C031872.Google Scholar
36. Heinrich, R. and Reimer, L. Comparison of different approaches for modeling of atmospheric effects like gusts and wake-vortices in the Cfd code tau, Tech Rep, June 2017.Google Scholar
37. Kaiser, C., Thormann, R., Dimitrov, D., and Nitzsche, J., Time-linearized analysis of motion-induced and gust-induced airloads with the DLR-tau code, 2015.Google Scholar
38. Reimer, L., Ritter, M., Heinrich, R. and Krüger, W. CFD-based gust load analysis for a free-flying flexible passenger aircraft in comparison to a DLM-based approach. 22nd AIAA computational fluid dynamics conference, 2015. ISBN 978-1-62410-366-7. https://doi.org/10.2514/6.2015-2455.Google Scholar
39. Kier, T.M. and Looye, G. Unifying manoeuvre and gust loads analysis models. International Forum of Aeroelasticity and Structural Dynamics (IFASD) 2009, pp 1–20.Google Scholar
40. Krüger, W.R. and Klimmek, T. Definition of a comprehensive loads process in the DLR project iLOADS, Tech Rep, 2016.Google Scholar
41. Ricci, S. and Scotti, A. Gust response alleviation on flexible aircraft using multi-surface control. 51st AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials conference 18th AIAA/ASME/AHS adaptive structures conference 12th, April 2010, p 3117. ISBN 978-1-60086-961-7. https://doi.org/10.2514/6.2010-3117.Google Scholar
42. Dillsaver, M., Cesnik, C. and Kolmanovsky, I. Gust response sensitivity characteristics of very flexible aircraft. AIAA atmospheric flight mechanics conference, Minneapolis, Minnesota, August 2012, pp 1–20. ISBN 9781624101847. https://doi.org/10.2514/6.2012-4576.Google Scholar
43. Hesse, H. and Palacios, R. Reduced-order aeroelastic models for dynamics of maneuvering flexible aircraft, AIAA J, 2014, 52, (8), pp 1717–1732; ISSN 0001-1452. https://doi.org/10.2514/1.J052684.Google Scholar
44. Andrews, S. Modelling and Simulation of Flexible Aircraft: Handling Qualities and Active Load Control, PhD thesis, Cranfield University, 2011.Google Scholar
45. Lone, M. and Cooke, A. Pilot-model-in-the-loop simulation environment to study large aircraft dynamics, J Aerospace Engineering, 2012, 227, (3), pp 555–568. https://doi.org/10.1177/0954410011434342.Google Scholar
46. Lone, M., Lai, C.K., Cooke, A. and Whidborne, J. Framework for flight loads analysis of trajectory-based manoeuvres with pilot models, J Aircr, 2014, 51, (2), pp 637–650; ISSN 00218669. https://doi.org/10.2514/1.C032376.Google Scholar
47. Dussart, G., Portapas, V., Pontillo, A. and Lone, M Flight dynamic modelling and simulation of large flexible aircraft. Flight Physics – Models, Techniques and Technologies. InTech, Rijeka, Croatia, 2018. https://doi.org/10.5772/intechopen.71050.Google Scholar
48. Carrizalez, M., Dussart, G., Portapas, V., Pontillo, A. and Lone, M Comparison of reduced order aerodynamic models and RANS simulations for whole aircraft aerodynamics. AIAA atmospheric flight mechanics conference, 2018, January 2018. ISBN 9781624105258. https://doi.org/10.2514/6.2018-0773.Google Scholar
49. Andrews, S. and Cooke, A An aeroelastic flexible wing model for aircraft simulation. 48th AIAA aerospace sciences meeting including the new horizons forum and aerospace Exposition, 0 (January), 2010. https://doi.org/10.2514/6.2010-35.Google Scholar
50. Lone, M. Pilot Modelling for Airframe Loads Analysis, PhD Thesis, Cranfield University, 2013.Google Scholar
51. Portapas, V., Cooke, A.K. and Lone, M Modelling framework for flight dynamics of flexible aircraft. Aviation, 2016, 20, (4), pp 173–182. https://doi.org/10.3846/16487788.2016.1264719.Google Scholar
52. Timme, S., Badcock, K.J. and Da Ronch, A Linear reduced order modelling for gust response analysis using the DLR-TAU Code. IFASD, 2013, p 15.Google Scholar
53. Kroll, N., Abu-Zurayk, M., Dimitrov, D., Franz, T., Führer, T., Gerhold, T., Görtz, S., Heinrich, R., Ilic, C., Jepsen, J., Jägersküpper, J., Kruse, M., Krumbein, A., Langer, S., Liu, D., Liepelt, R., Reimer, L., Ritter, M., Schwöppe, A., Scherer, J., Spiering, F., Thormann, R., Togiti, V., Vollmer, D. and Wendisch, J.H. DLR project Digital-X: towards virtual aircraft design and flight testing based on high-fidelity methods, CEAS Aeronautical J, 2016, 7, (1): 3–27; ISSN 18695590. https://doi.org/10.1007/s13272-015-0179-7.Google Scholar
54. Simeone, S., Rendall, T. and Da Ronch, A. A gust reconstruction framework applied to a nonlinear reduced order model of a wing typical section. 58th AIAA/ASCE/AHS/ASC structures, structural dynamics, and materials conference, Grapevine, Texas, AIAA, January 2017, pp 2017–0634. https://doi.org/10.2514/6.2017-0634.Google Scholar