考虑随机型不确定性的浸入式颤振求解方法
收稿日期: 2013-11-18
修回日期: 2014-01-14
网络出版日期: 2014-01-22
基金资助
国家自然科学基金(11302011,11172025);高等学校博士学科点专项科研基金(20131102120051)
Intrusive Flutter Solutions with Stochastic Uncertainty
Received date: 2013-11-18
Revised date: 2014-01-14
Online published: 2014-01-22
Supported by
National Natural Science Foundation of China (11302011, 11172025); Research Fund for the Doctoral Program of Higher Education of China (20131102120051)
气动弹性模型中的参数不确定性一般具有一定的分布规律,为了定量分析随机型参数不确定性对颤振的影响特性,考虑气动弹性系统中广义刚度的随机型不确定性,基于浸入式随机多项式展开(PCE)方法,在传统的颤振求解方法——p-k法的基础上,提出了针对不确定性气动弹性系统稳定性分析的增广p-k法——PCEPK (Polynomial Chaos Expansion with p-k)法,并将该方法应用到某机翼的颤振分析中,研究了均匀分布下的广义刚度不确定性对颤振边界的影响,并同基于结构奇异值μ理论的鲁棒颤振分析的结果和计算效率进行了对比。最后,采用标准的蒙特卡罗模拟(Monte Carlo Simulation, MCS)方法验证了结果的正确性。研究结果表明,PCEPK法计算的颤振边界范围是该分布下的“确定”结果,不因随机样本数而改变,克服了随机方法依赖样本数的缺点。同时,与基于结构奇异值理论的鲁棒颤振分析方法相比,它能够考虑不确定性参数分布对颤振特性的影响,具有更广泛的适用范围。
戴玉婷 , 杨超 . 考虑随机型不确定性的浸入式颤振求解方法[J]. 航空学报, 2014 , 35(8) : 2182 -2189 . DOI: 10.7527/S1000-6893.2013.0520
There is generally a certain distribution for parameter uncertainty in an aeroelastic model. In order to quantify the influence of stochastic uncertain parameters on the flutter boundary, a flutter analysis with generalized stiffness stochastic uncertainty is conducted in this work, based on the intrusive polynomial chaos expansion (PCE) theory. According to the traditional flutter solution method, namely the p-k method, an augmented PCEPK (polynomial chaos expansion with p-k) method for an uncertain aeroelastic system is presented to analyze its aeroelastic stability range. This flutter uncertainty analysis method is applied to a wing model, considering structural uncertainties with uniform distribution. A comparison of accuracy and computational time indicates that the range of flutter velocity by the PCEPK method is consistent with that obtained by the robust μ method. Finally, the standard Monte Carlo simulation (MCS) are employed to validate the results of the PCEPK method. In addition, though the parameter uncertainty is stochastic, the flutter velocity range is deterministic, invariant with the sample number, which resists the dependence on the random samples by the usual stochastic method. Moreover, the influence of the different distribution types of parameter uncertainty on flutter boundary can be obtained by the PCEPK method, which is more applicable when compared with the robust flutter analysis with μ method.
Key words: aeroelasticity; flutter; p-k method; uncertainty; polynomial chaos expansion; intrusive
[1] Pettit C L. Uncertainty quantification in aeroelasticity: recent results and research challenges[J]. Journal of Aircraft, 2004, 41(5): 1217-1229.
[2] Wang X, Qiu Z. Interval finite element analysis of wing flutter[J]. Chinese Journal of Aeronautics, 2008, 21(2): 134-140.
[3] Wu Z, Dai Y, Yang C, et al. Aeroelastic wind tunnel test for aerodynamic uncertainty model validation[J]. Journal of Aircraft, 2013, 50(1): 47-55.
[4] Li Y, Yang Z C. Exploring wing flutter risk assessment with parametric uncertainty[J]. Journal of Northwestern Polytechnical University, 2011, 28(3): 458-463. (in Chinese) 李毅, 杨智春. 基于参数不确定性的机翼颤振风险评定[J]. 西北工业大学学报, 2011, 28(3): 458-463.
[5] Dai Y T, Wu Z G, Yang C. Quantification analysis of uncertain flutter risks[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(9): 1788-1795. (in Chinese) 戴玉婷, 吴志刚, 杨超. 不确定性颤振风险定量分析[J]. 航空学报, 2010, 31(9): 1788-1795.
[6] Najm H N. Uncertainty quantification and polynomial chaos techniques in computational fluid dynamics[J]. Annual Review of Fluid Mechanics, 2009, 41: 35-52.
[7] Eldred M S. Recent advances in non-intrusive polynomial chaos and stochastic collocation methods for uncertainty analysis and design, AIAA-2009-2274. Reston: AIAA, 2009.
[8] Pitt D M, Haudrich D P, Thomas M J, et al. Probabilistic aeroelastic analysis and its implications on flutter margin requirements, AIAA-2008-2198. Reston: AIAA, 2008.
[9] Song S, Lu Z, Zhang W, et al. Uncertainty importance measure by fast Fourier transform for wing transonic flutter[J]. Journal of Aircraft, 2011, 48(2): 449-455.
[10] Beran P S, Pettit C L, Millman D R. Uncertainty quantification of limit-cycle oscillations[J]. Journal of Computational Physics, 2006, 217(1): 217-247.
[11] Pettit C L, Beran P S. Spectral and multiresolution wiener expansions of oscillatory stochastic processes[J]. Journal of Sound and Vibration, 2006, 294(4-5): 752-779.
[12] Badcock K J, Timme S, Marques S, et al. Transonic aeroelastic simulation for instability searches and uncertainty analysis[J]. Progress in Aerospace Sciences, 2011, 47(5): 392-423.
[13] Ghommem M, Hajj M, Nayfeh A. Effects of parameter uncertainties on the response of an aeroelastic system, AIAA-2010-2765. Reston: AIAA, 2010.
[14] Yang C, Wu Z G, Wan Z Q, et al. Aeroelastic principles of aircraft[M]. Beijing: Beihang University Press, 2011, 141-142. (in Chinese) 杨超, 吴志刚, 万志强, 等. 飞行器气动弹性原理[M]. 北京: 北京航空航天大学出版社, 2011: 141-142.
[15] Rodden W P, Johnson E H. MSC/Nastran aeroelastic analysis user's guide V68[M]. Los Angeles, CA: MSC.Software Corporation, 1994.
[16] Wu Z, Yang C. A new approach for aeroelastic robust stability analysis[J]. Chinese Journal of Aeronautics, 2008, 21(5): 417-422.
[17] Dai Y T, Wu Z G, Yang C. A new method for calculating structured singular value subject to real parameter uncertainty[J]. Control Theory and Application, 2011, 28(1): 114-117. (in Chinese) 戴玉婷, 吴志刚, 杨超. 实参数摄动下结构奇异值计算的新方法[J]. 控制理论与应用, 2011, 28(1): 114-117.
[18] Lind R, Brenner M. Robust flutter margins of an F/A-18 aircraft from aeroelastic flight data[J]. Journal of Guidance Control and Dynamics, 1997, 20(3): 597-604.
/
〈 | 〉 |