本研究旨詳述臨界雷諾數下三維圓柱尾流特性，使用熱線式測速儀量測臨界雷諾數4×105 下的圓柱尾流的紊流訊號。從得到訊號，進行高階統計量的分析，例如偏度因子(skewness)以及平坦度(flatness)，從這些高階統計值可以看出流場中不同的結構以及相關的物理關聯。其中，偏袒度因子可以看出渦流拉伸的結構，這在剪應力層中是很重要的物理現象；平坦度可以看出紊流訊號的間歇性，而紊流的間歇性與自由流如何被捲入尾流區的機制息息相關。最後，我們回到最基本的紊流方程式，從方程式中可以看到雷諾應力在動量傳遞扮演重要的角色，藉此，可以看到下洗氣流和湧升氣流的影響，這兩個主要的動量傳遞主宰整個三維流場的結構，這兩個流動在探討臨界諾數下三維尾流的流場中有很重要的地位。
最後，我們分別對流場訊號進行線性和非線性的頻譜分析；由於快速傅立葉轉換屬於線性分析，分析出來的結果顯示出所有線性結果的總和，在數學上是正確的，但是物理上卻是有問題的，明顯地忽略掉許多非線性的系統特性。有鑑於紊流訊號非定常、非線性的特徵，第二步則採用希爾伯特轉換(EMD)拆解量測到的紊流訊號，針對不同的模態拆解出不同的特徵的訊號，IMF。從這些IMF中可以找到潛藏在紊流訊號中的特徵訊號。我們也成功地找到Karman渦流溢放的頻率。雖然FFT無法成功拆解能量頻譜，但卻能看出整體的能量分布，顯示出慣性力在近尾流區域主宰整個流場的趨勢。而EMD成功地轉換出相對應的渦流溢放頻率，但也拆出其他頻率的分量，這也是未來可以進一步研究的地方。

Presented research aims on the three dimensional turbulent wake structure at critical Reynolds number. Experiment was carried out in 4m×3m close type wind tunnel with a finite circular cylinder at Reynolds number 4×105, long time average measurement was carried out to measure the velocity signal within the near wake region by hot wire anemometer. We analyzed turbulence data with statistical approaches, like building probability density function (PDF), skewness, and flatness. These statistics represent different turbulence relevant physics respectively. For skewness, it indicates the vortex stretching in the free shear layer; flatness shows the intermittence of the turbulence and the feature of entrainment. Besides, from the turbulence momentum equation, the additional term, Reynolds stress, drives the momentum transport in turbulence flow. It indicates two important flow characteristics in finite cylinder wake i.e. downwash and upwash, dominating the whole flow structure in the cylinder wake.
Consequently, we analyzed the turbulence spectrum by both linear and nonlinear analysis. First, the fast Fourier transform provides linear analysis whose final solution is the sum of all linear solutions of the turbulence data, this is Fourier’s view. Nevertheless, turbulence is nonstationary and nonlinear, in this way, Hilbert transform (EMD) is applied. Processed by Hilbert transform, we decompose several modes, called IMF, in our signal. Such nonlinear analysis shows us the local turbulence structure, unlike the Fourier’s approach, and we successfully discover the Karman vortex shedding hidden in the three dimensional wake. Interestingly, there are some residuum modes which has its principle frequency, but is much lower than Karman vortex. This gives a way for future work.

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