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中文核心期刊
Ye Kun, Ye Zhengyin, Qu Zhan, Wu Xiaojin, Zhang Weiwei. UNCERTAINTY AND GLOBAL SENSITIVITY ANALYSIS OF HYPERSONIC CONTROL SURFACE AEROTHERMOELASTIC[J]. Chinese Journal of Theoretical and Applied Mechanics, 2016, 48(2): 278-289. DOI: 10.6052/0459-1879-14-406
Citation: Ye Kun, Ye Zhengyin, Qu Zhan, Wu Xiaojin, Zhang Weiwei. UNCERTAINTY AND GLOBAL SENSITIVITY ANALYSIS OF HYPERSONIC CONTROL SURFACE AEROTHERMOELASTIC[J]. Chinese Journal of Theoretical and Applied Mechanics, 2016, 48(2): 278-289. DOI: 10.6052/0459-1879-14-406

UNCERTAINTY AND GLOBAL SENSITIVITY ANALYSIS OF HYPERSONIC CONTROL SURFACE AEROTHERMOELASTIC

  • Considering that the uncertainty of hypersonic aerothermodynamics prediction affects the reliability of aerothermoelastic analysis, a parameterized model for temperature distribution is therefore proposed.Based on this model, uncertainty and global sensitivity analysis on aerothermodynamics of hypersonic control surface aerothermoelastic are conducted.In the present analysis method, temperature distribution of the control surface is first obtained by solving NS equation and then parameterized.Using Monte Carlo simulation(MCS) method and spare grid numerical integration(SGNI) method to generate samples for analyzing uncertainly and global sensitivity and then analyzing all the samples, aerothermoelastic analysis is carried out as following:To get temperature distribution by the sample, then to analyze structural modal under the effect of structure thermal stress and material property, interpolate structural mode to the aerodynamic grid, and then to analyze aeroelasticity of the control surface in state space based on CFD local piston theory.Under two fly conditions, the calculation results show that:(1) With M=5 and H=15 km, the variation coefficient of natural frequency and flutter analysis is 5.83%,(2) With M=6 and H=15 km, variation coefficient of natural frequency of the structure and flutter analysis is 8.84%, and the global sensitivity of the two uncertainty parameters is about 50% under the two conditions.And the coupling of two parameters is about 0%, which is very small.Comparing with MCS method, SGNI method can be used to improve the efficiency of uncertainty analysis significantly.
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