Skip to main content
Log in

Frequency domain approach for probabilistic flutter analysis using stochastic finite elements

  • Published:
Meccanica Aims and scope Submit manuscript

A Correction to this article was published on 03 March 2021

A Correction to this article was published on 08 January 2020

This article has been updated

Abstract

In this work, a stochastic finite element method based on first order perturbation approach is developed for the probabilistic flutter analysis of aircraft wing in frequency domain. Here, both bending and torsional stiffness parameters of the wing are treated as Gaussian random fields and represented by a truncated Karhunen–Loeve expansion. The aerodynamic load on the wing is modeled using Theodorsen’s unsteady aerodynamics based strip theory. In this approach, Theodorsen’s function, which is a complex function of reduced frequency, is also treated as a random field. The applicability of the present method is demonstrated by studying the probabilistic flutter of cantilever wing with stiffness uncertainties. The present method is also validated by comparing results with Monte Carlo simulation (MCS). From the analysis, it is observed that torsional stiffness uncertainty has significant effect on the damping ratio and frequency of the flutter mode as compared to bending stiffness uncertainty. The probability density functions of damping ratio and frequency using perturbation technique and MCS are also discussed at various free stream velocities due to stiffness uncertainties. Furthermore, the flutter probability of the cantilever wing is studied by defining implicit limit state function in conditional sense on flow velocity for the flutter mode. Both perturbation and MCS are considered to study the flutter probability of the wing. From the cumulative distribution functions of flutter velocity, it is noticed that the presence of uncertainty in torsional rigidity lowers the predicted flutter velocity in comparison to uncertainty in bending rigidity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

Change history

References

  1. Adhikari S, Friswell MI (2001) Eigenderivative analysis of asymmetric non-conservative systems. Int J Numer Methods Eng 51(6):709–733

    Article  Google Scholar 

  2. Beran P, Stanford B, Schrock C (2017) Uncertainty quantification in aeroelasticity. Annu Rev Fluid Mech 49:361–386

    Article  MathSciNet  Google Scholar 

  3. Beran PS, Pettit CL, Millman DR (2006) Uncertainty quantification of limit-cycle oscillations. J Comput Phys 217(1):217–247

    Article  Google Scholar 

  4. Borello F, Cestino E, Frulla G (2010) Structural uncertainty effect on classical wing flutter characteristics. J Aerosp Eng 23(4):327–338

    Article  Google Scholar 

  5. Bueno DD, Góes LCS, Gonçalves PJP (2015) Flutter analysis including structural uncertainties. Meccanica 50(8):2093–2101

    Article  MathSciNet  Google Scholar 

  6. Canor T, Caracoglia L, Denoël V (2015) Application of random eigenvalue analysis to assess bridge flutter probability. J Wind Eng Ind Aerodyn 140:79–86

    Article  Google Scholar 

  7. Castravete SC, Ibrahim RA (2008) Effect of stiffness uncertainties on the flutter of a cantilever wing. AIAA J 46(4):925–935

    Article  Google Scholar 

  8. Cheng J, Xiao RC (2005) Probabilistic free vibration and flutter analyses of suspension bridges. Eng Struct 27(10):1509–1518

    Article  Google Scholar 

  9. Dai Y, Yang C (2014) Methods and advances in the study of aeroelasticity with uncertainties. Chin J Aeronaut 27(3):461–474

    Article  Google Scholar 

  10. Danowsky BP, Chrstos JR, Klyde DH, Farhat C, Brenner M (2010) Evaluation of aeroelastic uncertainty analysis methods. J Aircr 47(4):1266–1273

    Article  Google Scholar 

  11. Desai A, Sarkar S (2010) Uncertainty quantification and bifurcation behavior of an aeroelastic system. In: ASME 3rd joint US-European fluids engineering summer meeting and 8th international conference on nanochannels, microchannels, and minichannels, Montreal, Canada, Paper No. FEDSM-ICNMM2010-30050

  12. Friswell MI, Adhikari S (2000) Derivatives of complex eigenvectors using Nelson’s method. AIAA J 38(12):2355–2357

    Article  Google Scholar 

  13. Fung YC (2008) An introduction to the theory of aeroelasticity. Courier Dover Publications, Mineola

    MATH  Google Scholar 

  14. Ghanem R, Ghosh D (2007) Efficient characterization of the random eigenvalue problem in a polynomial chaos decomposition. Int J Numer Methods Eng 72(4):486–504

    Article  MathSciNet  Google Scholar 

  15. Ghanem RG, Spanos PD (2003) Stochastic finite elements: a spectral approach. Courier Corporation, Chelmsford

    MATH  Google Scholar 

  16. Goland M (1945) The flutter of a uniform cantilever wing. J Appl Mech Trans ASME 12(4):A197–A208

    Article  Google Scholar 

  17. Guedria N, Chouchane M, Smaoui H (2007) Second-order eigensensitivity analysis of asymmetric damped systems using Nelson’s method. J Sound Vib 300(3–5):974–992

    Article  Google Scholar 

  18. Hassig HJ (1971) An approximate true damping solution of the flutter equation by determinant iteration. J Aircr 8(11):885–889

    Article  Google Scholar 

  19. Huang SP, Quek ST, Phoon KK (2001) Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes. Int J Numer Methods Eng 52(9):1029–1043

    Article  Google Scholar 

  20. Irani S, Sazesh S (2013) A new flutter speed analysis method using stochastic approach. J Fluid Struct 40:105–114

    Article  Google Scholar 

  21. Irwin C, Guyett PR (1965) The subcritical response and flutter of a swept-wing model. HM Stationery Office, Richmond

    Google Scholar 

  22. Khodaparast HH, Mottershead JE, Badcock KJ (2010) Propagation of structural uncertainty to linear aeroelastic stability. Comput Struct 88(3–4):223–236

    Article  Google Scholar 

  23. Kleiber M, Hien TD (1992) The stochastic finite element method: basic perturbation technique and computer implementation. Wiley, Hoboken

    MATH  Google Scholar 

  24. Kurdi M, Lindsley N, Beran P (2007) Uncertainty quantification of the \(\text{Goland}^+\) wing’s flutter boundary. In: AIAA atmospheric flight mechanics conference and exhibit, Hilton Head, South Carolina, Paper No. 2007-6309

  25. Le Maître O, Knio OM (2010) Spectral methods for uncertainty quantification: with applications to computational fluid dynamics. Springer, Berlin

    Book  Google Scholar 

  26. Marques S, Badcock KJ, Khodaparast HH, Mottershead JE (2010) Transonic aeroelastic stability predictions under the influence of structural variability. J Aircr 47(4):1229–1239

    Article  Google Scholar 

  27. Melchers RE (1999) Structural reliability analysis and prediction, 2nd edn. Wiley, Hoboken

    Google Scholar 

  28. Murthy DV, Haftka RT (1988) Derivatives of eigenvalues and eigenvectors of a general complex matrix. Int J Numer Methods Eng 26(2):293–311

    Article  MathSciNet  Google Scholar 

  29. Pettit CL (2004) Uncertainty quantification in aeroelasticity: recent results and research challenges. J Aircr 41(5):1217–1229

    Article  Google Scholar 

  30. Pitt D, Haudrich D, Thomas M, Griffin K (2008) Probabilistic aeroelastic analysis and its implications on flutter margin requirements. In: 49th AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials conference, 16th AIAA/ASME/AHS adaptive structures conference, 10th AIAA non-deterministic approaches conference, 9th AIAA gossamer spacecraft forum, 4th AIAA multidisciplinary design optimization specialists conference, Schaumburg, IL, Paper No. 2008-2198

  31. Pourazarm P, Caracoglia L, Lackner M, Modarres-Sadeghi Y (2016) Perturbation methods for the reliability analysis of wind-turbine blade failure due to flutter. J Wind Eng Ind Aerodyn 156:159–171

    Article  Google Scholar 

  32. Reddy JN (2017) An introduction to finite element method, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  33. Riley ME, Grandhi RV (2014) Quantification of modeling-induced uncertainties in simulation-based analyses. AIAA J 52(1):195–202

    Article  Google Scholar 

  34. Riley ME, Grandhi RV, Kolonay R (2011) Quantification of modeling uncertainty in aeroelastic analyses. J Aircr 48(3):866–873

    Article  Google Scholar 

  35. Theodorsen T (1935) General theory of aerodynamic instability and the mechanism of flutter. Tech. Rep. NACA 496

  36. Ueda T (2005) Aeroelastic analysis considering structural uncertainty. Aviation 9(1):3–7

    Article  Google Scholar 

  37. Van Trees HL (2004) Detection, estimation, and modulation theory. Wiley, Hoboken

    MATH  Google Scholar 

  38. Verhoosel CV, Scholcz TP, Hulshoff SJ, Gutiérrez MA (2009) Uncertainty and reliability analysis of fluid-structure stability boundaries. AIAA J 47(1):91–104

    Article  Google Scholar 

  39. Wang X, Qiu Z (2009) Nonprobabilistic interval reliability analysis of wing flutter. AIAA J 47(3):743–748

    Article  Google Scholar 

  40. Wu S, Livne E (2017) Alternative aerodynamic uncertainty modeling approaches for flutter reliability analysis. AIAA J 55(8):2808–2823

    Article  Google Scholar 

  41. Yao G, Zhang Y (2016) Reliability and sensitivity analysis of an axially moving beam. Meccanica 51(3):491–499

    Article  MathSciNet  Google Scholar 

  42. Yao G, Zhang Y, Li C (2018) Aeroelastic reliability and sensitivity analysis of a plate interacting with stochastic axial airflow. Int J Dyn Control 6(2):561–570

    Article  MathSciNet  Google Scholar 

Download references

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Amit Kumar Onkar.

Ethics declarations

Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

The weak forms of the governing Eqs. (5) and (6) are obtained by multiplying weight functions \(v_1\) and \(v_2\) respectively and integrating over an \(i^{th}\) element length as [32]:

$$\begin{aligned} \int _{y_i}^{y_{i+1}}v_1\left( m\ddot{h}+mx_{\alpha }b\ddot{\alpha }+\frac{\partial ^2}{\partial y^2}\left( EI\frac{\partial ^2h}{\partial y^2}\right) +L\right) dy= \,& {} 0 \end{aligned}$$
(43)
$$\begin{aligned} \int _{y_i}^{y_{i+1}}v_2\left( I_p\ddot{\alpha }+mx_{\alpha }b\ddot{h}-\frac{\partial }{\partial y}\left( GJ\frac{\partial \alpha }{\partial y}\right) -M\right) dy= \,& {} 0 \end{aligned}$$
(44)

Substituting the expressions for lift (L) and moment (M), and performing integration by parts, the above equations can be expressed as:

$$\begin{aligned}&\int _{y_i}^{y_{i+1}}v_1m\ddot{h}dy+\int _{y_i}^{y_{i+1}}v_1\pi \rho _{\infty }b^2\ddot{h}dy+\int _{y_i}^{y_{i+1}}v_1mx_{\alpha }b\ddot{\alpha }dy\nonumber \\&\quad -\,\int _{y_i}^{y_{i+1}}\pi \rho _{\infty }b^3a\ddot{\alpha }dy+\int _{y_i}^{y_{i+1}}v_1UC(k)2\pi \rho _{\infty }b\dot{h}dy\nonumber \\&\quad +\,\int _{y_i}^{y_{i+1}}v_1U\pi \rho _{\infty }b^2\dot{\alpha }dy+\int _{y_i}^{y_{i+1}}v_1UC(k)\pi \rho _{\infty }b^2(1-2a)\dot{\alpha }dy\nonumber \\&\quad +\,\int _{y_i}^{y_{i+1}}v_1U^2C(k)2\pi \rho _{\infty }b{\alpha }dy+\int _{y_i}^{y_{i+1}}\frac{\partial ^2v_1}{\partial y^2}\left( EI\frac{\partial ^2h}{\partial y^2}\right) dy\nonumber \\&\quad +\,\left( -v_1S^b-\frac{\partial {v_1}}{\partial {y}}M^b\right) \arrowvert _{y_i}^{y_{i+1}}=0 \end{aligned}$$
(45)
$$\begin{aligned}&\int _{y_i}^{y_{i+1}}v_2I_p\ddot{\alpha }dy+\int _{y_i}^{y_{i+1}}v_2\pi \rho _{\infty }b^4\left( \frac{1}{8}+a^2\right) \ddot{\alpha }dy\nonumber \\&\quad +\,\int _{y_i}^{y_{i+1}}v_2mx_{\alpha }b\ddot{h}dy-\int _{y_i}^{y_{i+1}}v_2\pi \rho _{\infty }b^3a\ddot{h}dy\nonumber \\&\quad -\,\int _{y_i}^{y_{i+1}}v_2U\pi \rho _{\infty }b^3\left( -\frac{1}{2}+a\right) \dot{\alpha }dy\nonumber \\&\quad -\,\int _{y_i}^{y_{i+1}}v_2UC(k)\pi \rho _{\infty }b^3\left( \frac{1}{2}+a\right) \left( 1-2a\right) \dot{\alpha }dy\nonumber \\&\quad -\,\int _{y_i}^{y_{i+1}}v_2UC(k)2\pi \rho _{\infty }b^2\left( \frac{1}{2}+a\right) \dot{h}dy\nonumber \\&\quad -\,\int _{y_i}^{y_{i+1}}v_2U^2C(k)2\pi \rho _{\infty }b^2\left( \frac{1}{2}+a\right) {\alpha }dy\nonumber \\&\quad +\,\int _{y_i}^{y_{i+1}}\frac{\partial {v_2}}{\partial {y}}\left( GJ\frac{\partial {\alpha }}{\partial {y}}\right) dy-v_2\tau \arrowvert _{y_i}^{y_{i+1}}=0 \end{aligned}$$
(46)

where \(M^b\), \(S^b\), and \(\tau\) are bending moment, shear force, and torsional moment respectively and can be written as:

$$\begin{aligned} M^b= \,& {} EI\frac{\partial ^2h}{\partial y^2}\\ S^b= \,& {} -\frac{\partial }{\partial {y}}\left( EI\frac{\partial ^2h}{\partial y^2}\right) \\ \tau= \,& {} GJ\frac{\partial {\alpha }}{\partial {y}} \end{aligned}$$

Now by using finite element approximation functions, the heave (h) and pitch \((\alpha )\) displacements can be expressed as:

$$\begin{aligned} h(y,t)= \,& {} \lfloor N_w\rfloor \{w_e(t)\}\nonumber \\ \alpha (y,t)= \,& {} \lfloor N_\alpha \rfloor \{\alpha _e(t)\} \end{aligned}$$
(47)

where \(\lfloor N_w\rfloor =\lfloor N_1, N_2, N_3, N_4\rfloor\) and \(\lfloor N_\alpha \rfloor =\lfloor \bar{N}_1,\bar{N}_2\rfloor\) are Hermite and Lagrange shape functions [32] respectively and \(\{w_e\}\) and \(\{\alpha _e\}\) are the bending and torsional degrees of freedom respectively. The weight functions \(v_1\) and \(v_2\) can be also written as \(v_1= \lfloor N_w\rfloor ^T\) and \(v_2=\lfloor N_\alpha \rfloor ^T\) respectively. On substitution of the above approximation functions and weight functions, the elemental equations can be written in notational form as:

$$\begin{aligned}&\left[ M_{SB}\right] \{\ddot{w}_e\}+\left[ M_{AB}\right] \{\ddot{w}_e\}+\left[ M_{SC}\right] \{\ddot{\alpha }_e\}+\left[ M_{AC}\right] \{\ddot{\alpha }_e\}\nonumber \\&\qquad +\,\left[ C_{AB}\right] \{\dot{w}_e\}+\left[ C_{AC}^{12}\right] \{\dot{\alpha }_e\}+\left[ K_{AC}\right] \{\alpha _e\}+\left[ K_{SB}\right] \{w_e\}\nonumber \\&\quad =\{F_i\} \end{aligned}$$
(48)
$$\begin{aligned}&\left[ M_{ST}\right] \{\ddot{\alpha }_e\}+\left[ M_{AT}\right] \{ \ddot{\alpha }_e\}+\left[ M_{SC}\right] \{\ddot{w}_e\}+\left[ M_{AC}\right] \{\ddot{w}_e\}\nonumber \\&\qquad +\,\left[ C_{AT}\right] \{\dot{\alpha }_e\}+\left[ C_{AC}^{21}\right] \{\dot{w}_e\}+\left[ K_{AT}\right] \{\alpha _e\}+\left[ K_{ST}\right] \{\alpha _e\}\nonumber \\&\quad =\{\tau _i\} \end{aligned}$$
(49)

where \(\{F_i\}=\lfloor -S_{y_{i}}^{b}, -M_{y_{i}}^{b}, S_{y_{i+1}}^{b}, M_{y_{i+1}}^{b}\rfloor ^T\) and \(\{\tau _i\}=\lfloor -\tau _{y_i},\tau _{y_{i+1}}\rfloor ^T\). The terms involved in Eq. (48) are:

$$\begin{aligned} \left[ M_{SB}\right]= \,& {} m\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_w\rfloor dy}\nonumber \\ \left[ M_{AB}\right]=\, & {} \pi \rho _{\infty }b^2\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_w\rfloor dy}\nonumber \\ \left[ M_{SC}\right]=\, & {} mx_{\alpha }b\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ M_{AC}\right]=\, & {} -\pi \rho _{\infty }b^3a\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ C_{AB}\right]=\, & {} UC(k)2\pi \rho _{\infty }b\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_w\rfloor dy}\nonumber \\ \left[ C_{AC}^{12}\right]= \,& {} U\pi \rho _{\infty }b^2\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\&+\,UC(k)\pi \rho _{\infty }b^2(1-2a)\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ K_{AC}\right]= \,& {} U^2C(k)2\pi \rho _{\infty }b\int _{y_i}^{y_{i+1}}{\lfloor {N_w}\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ K_{SB}\right]=\, & {} \int _{y_i}^{y_{i+1}}{EI\lfloor {N_w^{''}}\rfloor ^T\lfloor N_w^{''}\rfloor dy} \end{aligned}$$
(50)

and the terms in Eq. (49) can be written as:

$$\begin{aligned} \left[ M_{ST}\right]= \,& {} I_p\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ M_{AT}\right]= \,& {} \pi \rho _{\infty }b^4\left( a^2+\frac{1}{8}\right) \int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ M_{SC}\right]= \,& {} mx_{\alpha }b\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_w\rfloor dy}\nonumber \\ \left[ M_{AC}\right]= \,& {} -\pi \rho _{\infty }b^3a\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_w\rfloor dy}\nonumber \\ \left[ C_{AT}\right]= \,& {} -U\pi \rho _{\infty }b^3(-0.5+a)\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\&-\,UC(k)\pi \rho _{\infty }b^3(0.5+a)(1-2a)\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ C_{AC}^{21}\right]= \,& {} -UC(k)2\pi \rho _{\infty }b^2(0.5+a)\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_w\rfloor dy}\nonumber \\ \left[ K_{AT}\right]= \,& {} -U^2C(k)2\pi \rho _{\infty }b^2(0.5+a)\int _{y_i}^{y_{i+1}}{\lfloor {N_\alpha }\rfloor ^T\lfloor N_\alpha \rfloor dy}\nonumber \\ \left[ K_{ST}\right]= \,& {} \int _{y_i}^{y_{i+1}}{GJ\lfloor {N_\alpha ^{'}}\rfloor ^T\lfloor N_\alpha ^{'}\rfloor dy} \end{aligned}$$
(51)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, S., Onkar, A.K. & Maligappa, M. Frequency domain approach for probabilistic flutter analysis using stochastic finite elements. Meccanica 54, 2207–2225 (2019). https://doi.org/10.1007/s11012-019-01061-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11012-019-01061-9

Keywords

Navigation