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CLARIFYING LOW-FREQUENCY VARIATOIONS PHENOMENON USING A NOVEL MODE DECOMPOSITION METHOD

机译:使用新模式分解法澄清低频变异现象

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Low-frequency variations in wake flow are complex and many aspects of its behavior remain poorly understood. A mode decomposition method developed by Huang et al is utilized herein because it can decompose any complicated data set into a finite number of intrinsic modes without distorting their original characteristics. The results of decomposition analysis of the measured base pressure signals reveal that a finite number of various kinds of flow structure modes, with their own characteristic time scales, coexist with the residue that exhibits most of the low-frequency variations in flow at Re = 11760 and 31600, respectively. As the Reynolds number increases, the decomposition method yields more components. Results also show exactly the vortex shedding structure in an intrinsic mode and the low-frequency variations that appear in the residue during vortex shedding process.
机译:尾流的低频变化很复杂,对其行为的许多方面仍然知之甚少。本文使用了Huang等人开发的模式分解方法,因为它可以将任何复杂的数据集分解为有限数量的固有模式,而不会破坏它们的原始特征。对测得的基本压力信号进行分解分析的结果表明,有限数量的各种流动结构模式(具有自己的特征时间尺度)与残渣共存,而残渣在Re = 11760时表现出大部分的低频低频变化和31600。随着雷诺数的增加,分解方法会产生更多的组分。结果还准确显示了固有模式下的涡旋脱落结构以及在涡旋脱落过程中残留物中出现的低频变化。

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