Modal decomposition and rapid prediction of shock train oscillation for inlet
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摘要: 为研究隔离段自激振荡现象,采用2阶时间和空间精度、非结构网格、剪切应力输运(SST) k -ω湍流模型有限体积法程序对二元进气道在高反压下的非定常特性进行数值模拟,成功捕捉到激波串自激振荡现象,在此基础上利用本征正交分解(POD)和动力学模态分解(DMD)方法对其进行分析。结果表明:该自激振荡是低频主导、多频耦合的复杂振荡现象;基于本征正交分解和动力学模态分解构建的预测模型均能准确快速地预测出非定常流场的演变特性,预测误差小于0.2%,前者耗时为0.22 s,后者耗时为0.05 s。Abstract: To study the self-excited oscillation in the isolator, the unsteady characteristics of the two dimensional planar inlet were numerically simulated using the finite volume method program with time and space terms of the two-order implicit and upwind discrete schemes, unstructured grid, and shear stress transport (SST) k -ω turbulence model when the high backpressure was applied, and the self-excited oscillation of the shock train was successfully captured. On this basis, proper orthogonal decomposition (POD) and dynamic modal decomposition (DMD) methods were utilized to analyze the oscillation. The results showed that the self-excited oscillation is a complex oscillation phenomenon dominated by a low frequency and coupled with multiple frequencies. Both the predictive models based on the POD and DMD methods can accurately and quickly predict the evolutions of flow field with the prediction error less than 0.2%. The time consuming of the former and the latter was 0.22 s and 0.05 s, respectively.
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