基于非线性状态空间辨识的气动弹性模型降阶

高维、非线性气动弹性系统的模型降阶是当前气动弹性力学与控制领域的研究热点之一.然而国内外现有的非线性模型降阶方法仍存在辨识算法复杂、精度有待提高等问题.本研究提出了一种基于非线性状态空间辨识的跨音速气动弹性模型降阶方法.首先,该方法基于非定常空气动力的单位脉冲响应数据,采用特征系统实现算法对非线性状态空间模型的线性动力学部分进行系统辨识.其次,引入状态和控制输入的非线性函数,采用优化算法对非线性函数的系数矩阵进行优化,进而得到考虑非线性效应的空气动力降阶模型.为了验证该降阶模型在预测跨音速气动弹性力学行为的精确性,本文以三维机翼为研究对象,分别从基于非线性降阶模型的气动力辨识、跨声速颤振边界计算和极限环振荡预测三方面进行了算例验证,并与现有的模型降阶方法进行了对比,进一步说明本文所提出方法的有效性.研究结果表明,该降阶模型对上述三类问题的计算精度与直接流-固耦合方法相吻合,可用于高效预测飞行器跨声速气动弹性力学行为.     

大长细比导弹的气动弹性降阶模型

对于大长细比导弹,需要在设计阶段准确计算气动弹性/气动伺服弹性,但其复杂的气动力给计算带来困难,因此气动力降阶模型是突破大长细比导弹跨音速气动弹性分析与控制瓶颈的关键技术.虽然气动力模型降阶方法已在预测二维机翼结构的气动弹性方面取得重要进展,但几乎未见关于全机模型的气动力降阶模型研究报道.本文基于递归Wiener模型的气动力降阶方法,利用CFD计算的气动力作为模型辨识数据,用鲁棒子空间和Levenberg-Marquardt算法辨识降阶模型参数,建立了大长细比导弹气动力降阶模型.在此基础上与大长细比导弹有限元模型相结合,构造出气动弹性降阶模型,并在数值仿真中测试气动弹性降阶模型在不同马赫数下的适用性.数值仿真结果表明,该气动弹性降阶模型能够精确预测导弹模型在不同飞行条件下的非定常气动力和导弹模型的气动弹性频率响应特性.     

基于ROM技术的阵风响应分析方法

阵风响应分析是大型飞机设计过程中必不可少的环节. 现有的阵风响应分析主要采用基于线化升力面理论的气动力模型,不能考虑到各种非线性效应,不适合于跨音速气动弹性的分析. 基于CFD技术,采用系统辨识方法,在状态空间内建立了降阶的非定常气动力模型(reduced order model, ROM). 耦合结构运动方程、非定常气动力模型(结构运动)、外激阵风的气动力模型,建立了基于CFD技术的阵风响应分析模型.算例研究了某一典型机翼在方波激励下的阵风响应问题,对比了各阶模态位移的响应以及翼根弯矩的响应. 基于ROM技术的计算结果与CFD/CSD直接耦合仿真结果吻合,证明了该方法的正确性和精度.      

基于随机森林算法的非定常气动力建模研究

针对现有的非定常气动力建模方法对气动弹性预测的准确性和效率问题,将随机森林算法引入非定常气动力建模研究领域,构建了基于随机森林算法的非定常气动力降阶模型。将所得模型用于预测气动弹性,选择二维NACA0012翼型进行颤振边界的预测,选用NACA64A010翼型预测LCO特性,并说明了该降阶模型建模的详细过程,将其计算结果与CFD/CSD耦合计算结果及试验结果进行了对比。研究结果表明,该模型可行、高效且精确,可以快速准确地预测飞行器气动弹性特性。     

基于气动力降阶模型的跨音速气动弹性稳定性分析

基于离散型输入输出差分模型,运用非定常CFD方法训练信号,然后运用最小二乘方法进行参数辨识,得到降阶的非定常气动力模型,再将该离散差分模型转换为连续时间域内的状态方程。耦合气动状态方程和结构状态方程,得到耦合系统的气动弹性状态方程。求解不同动压下状态矩阵的特征值,根据根轨迹图分析系统的稳定性特性。分析结果与直接耦合CFD/CSD方法结果相吻合,可以计算跨音速非线性气动弹性问题。其计算效率比直接耦合CFD/CSD方法提高1~2个数量级。针对Isogai wing在跨音速出现的S型颤振边界进行了较为细致的分析,阐述了该现象是由于系统诱发颤振的分支随着速度(来流动压)的提高而发生转移所导致的。     

CFD结合降阶模型预测阵风响应

传统的阵风响应主要在频域内进行分析,气动载荷基于线性方法计算,不能考虑黏性和跨声速流动影响. 飞机设计需考虑不同频率和不同形状阵风的响应,基于CFD的阵风响应预测由于计算工况太多,工作量巨大. 本文发展了一种CFD结合非定常气动力ARMA(autoregressive-moving-averagemodel)降阶模型的阵风响应分析方法,CFD只要针对给定频率和形状的一种阵风响应进行计算,对获得的气动力时间历程运用线性最小二乘法参数辨识ARMA降阶模型的系数,则对任意频率和形状的阵风,代入降阶模型即可确定该阵风的响应,大大提高了计算效率. 为效验发展的方法,先计算NACA0012翼型在低马赫数0.11的阵风响应,通过对比CFD、ARMA降阶模型及早期发展的不可压阵风响应预测方法的结果,验证了方法的有效性. 再对比CFD、ARMA在跨声速马赫数0.8的阵风响应预测结果,证实所发展的方法对跨声速阵风响应预测亦是有效的.      

基于CFD的气动力建模及其在气动弹性中的应用

CFD技术为带有气动力非线性的气动弹性分析提供了一种研究途径,但是基于CFD的气动弹性直接数值模拟方法的计算量很大,不便开展定性分析和参数设计.基于CFD的非定常气动力模型的降阶技术为缓解计算效率与计算精度之间的矛盾以及系统的复杂性与易分析、易设计性之间的矛盾提供了行之有效的技术途径.综述了近年来发展的两类基于CFD技术的非定常气动力降阶技术和一种非线性气动力的谐波平衡方法,以及这些方法在非线性气动弹性研究中的运用.对比了各种方法的优越性并作了进一步的展望.      

跨音速极限环型颤振的高效数值分析方法

事先建立一个低阶的非线性、非定常气动力模型是开展非线性流场中气动弹性问题研究的一个捷径. 基于CFD方法, 通过计算结构在流场中自激振动的响应来获得系统的训练数据. 采用带输出反馈的循环RBF神经网络, 建立时域非线性气动力降阶模型.耦合结构运动方程和非线性气动力降阶模型, 采用杂交的线性多步方法计算结构在不同速度(动压)下的响应历程, 从而获得模型极限环随速度(动压)变化的特性. 两个典型的跨音速极限环型颤振算例表明, 基于气动力降阶模型方法的计算结果与直接CFD仿真结果吻合很好, 与后者相比其将计算效率提高了1~2个数量级.      

基于气动力辨识的ASE模型降阶研究

CFD/CSD耦合计算能够准确预测跨音速段飞行器弹性振动的非定常气动力, 但其带来的巨大 计算量及高阶维数不利于气动弹性系统的分析与综合. 针对于此,采用系统辨识及 均衡截断技术对高阶气动伺服弹性模型进行降阶处理,并利用所得到的低阶模型进行系统综 合：(1) 基于Volterra级数气动力辨识技术,得到非定常气动力的时域降阶模型(ROM), 耦合结构动力学模型及控制机构动力学模型获得气动伺服弹性(ASE)状态空间方 程;(2) 利用均衡截段法对时域ASE模型进行进一步降阶,得到能够较真实反映所关心频域内系统响应 的低阶ASE模型;(3) 针对建模误差和降阶误差存在造成的系统不确定性问题,结合降阶模型 采用混合灵敏度$H_{\infty}$控制方法设计颤振主动抑制鲁棒控制律,保证其作用 于真实系统的有效性;对控制器进行 均衡阶段降阶并保持其鲁棒性,得到低阶鲁棒的颤振抑制控制器. 最后利用典型的BACT模型 进行气动伺服弹性的降阶及主动颤振抑制控制,仿真结果表明,基于ROM建立的低阶气动弹 性模型能够较真实地反应系统的颤振特性;而基于截断后的降阶模型所设计的低阶鲁棒控制 器能够有效应用于存在不确定性摄动的实际系统,并将系统颤振速度提高36%.     

基于边界元方法的气动弹性降阶模型及仿真

传统气动弹性的时域计算耗费了大量时间,为了提高计算效率,本文发展了基于边界元方法的降阶模型技术。首先基于边界元方法建立非定常流场的求解模型,结合特征值分析技术建立了非定常气动力的低阶模型;然后,利用边界元方法建立了气动网格和结构网格之间的信息转换矩阵;最后将非定常气动力降阶模型和结构动力学方程联合,建立了气动弹性系统的低阶状态空间模型。将所发展的降阶模型方法应用于NACA0012翼型的非定常气动力求解中,结果表明降阶模型可以在保证原系统计算精度的同时提高了计算效率;将降阶模型技术应用到三维机翼的气动弹性响应计算中,在系统阶数仅为12阶的情况下可以得到与原系统一致的极限环响应,说明降阶模型技术在求解气动弹性问题中的巨大优势。     

An improved nonlinear reduced-order modeling for transonic aeroelastic systems

In this study, an improved nonlinear reduced-order model composed of a linear part and a nonlinear part is explored for transonic aeroelastic systems. The linear part is identified via the eigensystem realization algorithm and the nonlinear part is obtained via the Levenberg–Marquardt algorithm. The impulsive signal is chosen as the training signal for the linear part and the sinusoidal signal is used to determine the order of the linear part. The training signal for the nonlinear part is selected as the filtered white Gaussian noise with the maximal amplitude and frequency range to be designed via the aeroelastic responses. An NACA64A010 airfoil and an NACA0012 airfoil are taken as illustrative examples to demonstrate the performance of the presented reduced-order model in modeling transonic aerodynamic forces. The aeroelastic behaviors of the two airfoils are obtained via computational fluid dynamics to solve the Euler equation and the Navier–Stokes equation, respectively. The numerical results demonstrate that the presented reduced-order model can successfully predict the nonlinear aerodynamic forces with and without viscous flows. Moreover, the presented reduced-order model is capable of capturing the flutter velocity and modeling complex aeroelastic behaviors, including limit-cycle oscillations, beat phenomena and nodal-shaped oscillations at the transonic Mach numbers with high accuracy.     

Unsteady aerodynamic reduced-order modeling of an aeroelastic wing using arbitrary mode shapes

Computational fluid dynamics (CFD) based unsteady aerodynamic reduced-order model (ROM) can offer significant improvements to the efficiency of transonic aeroelastic analysis. To construct a ROM based on mode shapes, one run of CFD solver is needed to compute aerodynamic responses corresponding to mode excitations. When mode shapes change with structure, another run of the CFD solver is required to construct the new ROM. The typically large computational cost associated with repeated runs of the CFD solver impedes the application of existing unsteady aerodynamic reduced-order modeling methods to transonic aeroelastic design optimization and aeroelastic uncertainty analysis. This paper demonstrates a method that can replace the CFD solver used in the process of existing unsteady aerodynamic reduced-order modeling. It can produce aerodynamic responses corresponding to mode excitations for arbitrary mode shapes within a few seconds. Computational cost can be reduced by two orders of magnitude using the mode excitations and the corresponding aerodynamic responses computed by the method to construct the ROMs used for flutter analyses in aeroelastic design optimization or aeroelastic uncertainty analysis in transonic regime compared with the existing unsteady aerodynamic reduced-order modeling methods. Results show that the method can accurately produce the aerodynamic responses corresponding to the mode excitations and predict the flutter characteristics of AGARD 445.6 wings root-attached in three different ways.     

Nonlinear dynamics of an aeroelastic airfoil with free-play in transonic flow

Nonlinear dynamic behaviors of an aeroelastic airfoil with free-play in transonic air flow are studied. The aeroelastic response is obtained by using time-marching approach with computational fluid dynamics (CFD) and reduced order model (ROM) techniques. Several standardized tests of transonic flutter are presented to validate numerical approaches. It is found that in time-marching approach with CFD technique, the time-step size has a significant effect on the calculated aeroelastic response, especially for cases considering both structural and aerodynamic nonlinearities. The nonlinear dynamic behavior for the present model in transonic air flow is greatly different from that in subsonic regime where only simple harmonic oscillations are observed. Major features of the responses in transonic air flow at different flow speeds can be summarized as follows. The aeroelastic responses with the amplitude near the free-play are dominated by single degree of freedom flutter mechanism, and snap-though phenomenon can be observed when the air speed is low. The bifurcation diagram can be captured by using ROM technique, and it is observed that the route to chaos for the present model is via period-doubling, which is essentially caused by the free-play nonlinearity. When the flow speed approaches the linear flutter speed, the aeroelastic system vibrates with large amplitude, which is dominated by the aerodynamic nonlinearity. Effects of boundary layer and airfoil profile on the nonlinear responses of the aeroelastic system are also discussed.     

Aeroelastic analysis of large horizontal wind turbine baldes

A nonlinear aeroelastic analysis method for large horizontal wind turbines is described. A vortex wake method and a nonlinear finite element method (FEM) are coupled in the approach. The vortex wake method is used to predict wind turbine aerodynamic loads of a wind turbine, and a three-dimensional (3D) shell model is built for the rotor. Average aerodynamic forces along the azimuth are applied to the structural model, and the nonlinear static aeroelastic behaviors are computed. The wind rotor modes are obtained at the static aeroelastic status by linearizing the coupled equations. The static aeroelastic performance and dynamic aeroelastic responses are calculated for the NH1500 wind turbine. The results show that structural geometrical nonlinearities significantly reduce displacements and vibration amplitudes of the wind turbine blades. Therefore, structural geometrical nonlinearities cannot be neglected both in the static aeroelastic analysis and dynamic aeroelastic analysis.     

变后掠翼的参变气动弹性建模与分析

参变气动弹性建模是可变后掠翼气动弹性研究中的难点之一. 当地建模技术是一种构造线性参变 (LPV) 模型的实用方法, 但一直缺乏有效途径来解决当地气动弹性模型的不一致问题. 气动弹性模型的不一致性体现在当地结构动力学模型和非定常气动力模型随参数变化的不连续性. 本文提出了一种自下而上的方法, 对变后掠翼不一致的当地气动弹性模型进行了一致性处理. 首先, 采用匈牙利算法跟踪结构模态并按模态分支进行排序, 使得匹配后的模态能够保证结构动力学模型的一致性; 其次, 对有理函数拟合表达式中的系数矩阵进行缩放处理, 解决了空气动力系数矩阵的不一致问题. 采取上述两项措施后, 最终生成了一致的当地状态空间气动弹性模型. 这样, 对一致的状态空间模型进行插值, 就可快速生成任意后掠角下的气动弹性模型, 使得系统的稳定性分析和慢参变响应计算得以高效进行. 数值仿真结果验证了一致性处理的必要性:未经一致性处理的原始模型经插值后得到的模型会出现严重的模型误差. 本文为变后掠翼的参变气动弹性系统建模提供了一种实用、准确和高效的建模方法.      

Efficient unsteady aerodynamic loads prediction based on nonlinear system identification and proper orthogonal decomposition

In the present work, an efficient surrogate-based framework is developed for the prediction of motion-induced surface pressure fluctuations and integral force and moment coefficients. The model construction is realized by performing forced-motion computational fluid dynamics (CFD) simulations, while the result is processed via the proper orthogonal decomposition (POD) to obtain the predominant flow modes. Subsequently, a nonlinear system identification is carried out with respect to the applied excitation and the resulting POD coefficients. For the input/output model identification task, a recurrent local linear neuro-fuzzy approach is employed in order to capture the linear and nonlinear characteristics of the dynamic system. Once the reduced-order model (ROM) is trained, it can substitute the flow solver within unsteady aerodynamic or aeroelastic simulation frameworks for a given configuration at fixed freestream conditions. For demonstration purposes, the ROM approach is applied to the LANN wing in high subsonic and transonic flow. Due to the characteristic lambda-shock system, the unsteady aerodynamic surface pressure distribution is dominated by nonlinear effects. Numerical investigations show a good correlation between the results obtained by the ROM methodology in comparison to the full-order CFD solution. In addition, the surrogate approach yields a significant speed-up regarding unsteady aerodynamic calculations, which is beneficial for multidisciplinary computations.