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跨音速极限环型颤振的高效数值分析方法

High efficient numerical method for lco analysis in transonic flow

  • 摘要: 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.

     

    Abstract: Non-linearities can be present in an aeroelastic systemdue to some aerodynamic phenomena that occur in transonic flight regime orat large angles of attack. The candidate sources are motions of shock waveand separated flow. With the recently well-developed software and hardwaretechnologies, numerical simulation of complex aeroelasticity phenomenabecomes possible, such as limit cycle oscillations (LCOs) due to theaerodynamic nonlinearity. However, the computational cost of solvingaeroelastic problem in nonlinear flow field is very high, so it is aconvenient method to solve this kind of problem by constructing a properunsteady aerodynamic model previously. Many research works are carried outin reduced order modeling (ROM) for aeroelastic analysis. Most of thereduced order aerodynamic models are dynamic linear models and in proportionto the structural motions. In this study, by using Radial Basis Function(RBF) neural network model, the nonlinear unsteady reduced order aerodynamicmodel is constructed. The ROM is used to analyze LCOs behaviors for twolinear structural models with large shock motion in transonic flow.Different from the traditional design method of the input signals, signalsof self-excited vibration of the aeroelastic system are designed as theinput signals in this paper. Coupled the structural equations of motion andnonlinear aerodynamic ROM, the system responses are determined by timemarching of the governing equations using a kind of hybrid linear multi-stepalgorithm and the limit cycle behaviors changing with velocities (dynamicpressure) can be analyzed. Two transonic aeroelastic examples show that boththe structural responses and the limit cycle oscillation (LCO)characteristics simulated by ROM agree well with those obtained by directCFD method, and the computational efficiency of ROM based method can beimproved by 1-2 orders of magnitude compared with the direct CFD method.

     

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