高超声速舵面热气动弹性不确定性及全局灵敏度分析

发布时间：2018-02-13 03:20

本文关键词： 高超声速热气动弹性不确定性分析全局灵敏度稀疏网格方法当地流活塞理论　出处：《力学学报》2016年02期 　论文类型：期刊论文

【摘要】：鉴于高超声速中气动热预测的不确定性影响热气动弹性分析的可靠性,提出一种温度分布参数化模型,基于此模型,对高超声速舵面热气动弹性中气动热的不确定性及全局灵敏度进行分析,分析方法:求解N-S方程得到物面的温度分布,对此温度分布进行参数化,分别采用蒙特卡罗模拟(Monte Carlo simulation,MCS)方法和稀疏网格数值积分(spare grid numerical integration,SGNI)方法生成不确定性及全局灵敏度分析所需样本,对所有样本都进行热气动弹性分析,热气动弹性分析过程为:由样本得到温度分布,基于此温度分布,考虑热应力和材料属性的影响,对结构进行模态分析,将结构模态插值到气动网格,采用基于CFD的当地流活塞理论进行了气动弹性分析.分别在两种飞行状态下进行分析,计算结果表明:(1)M=5,H=15 km,结构固有频率和颤振分析结果的变异系数约为5.83%;(2)M=6,H=15 km,结构和颤振分析结果的变异系数约为8.84%.两种状态下,两个不确定参数的全局灵敏度都在50%左右,两者耦合作用很小,约为0.与MCS方法相比,SGNI方法显著的提高了不确定性分析效率.
[Abstract]:Since the uncertainty of aerodynamic heat prediction in hypersonic velocities affects the reliability of thermal Aeroelastic analysis, a parameterized model of temperature distribution is proposed based on this model. The uncertainty and global sensitivity of aerodynamic heat in the thermo-Aeroelasticity of hypersonic rudder surface are analyzed. The temperature distribution of the surface is obtained by solving the N-S equation, and the temperature distribution is parameterized. Monte-Carlo simulation Monte Carlo simulation method and sparse grid numerical integration method are used to generate samples for uncertainty and global sensitivity analysis. The thermo-Aeroelastic analysis process is as follows: the temperature distribution is obtained from the sample. Based on the temperature distribution, considering the influence of thermal stress and material properties, the modal analysis of the structure is carried out, and the structural modal is interpolated to the pneumatic mesh. Aeroelastic analysis based on the local flow piston theory based on CFD is carried out. The calculated results show that the variation coefficients of the natural frequencies and flutter analysis results are about 5.83mand 5.83km and 8.84km respectively. The global sensitivity of the two uncertain parameters is about 50% in both states, the calculated results show that the variation coefficients of the structural and flutter analysis results are about 15 km, and the coefficients of variation of the structural and flutter analysis results are about 5.83 km and 8.84 km.The global sensitivity of the two uncertain parameters is about 50%, and the global sensitivity of the two uncertain parameters is about 50%. The coupling effect between the two methods is very small, about 0. Compared with the MCS method, the efficiency of uncertainty analysis is improved significantly.
【作者单位】：西北工业大学航空学院;
【基金】：国家自然科学基金重点资助项目(91216202)
【分类号】：V211.47

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