臺灣博碩士論文加值系統

本研究以影像處理技術分析實驗水槽之風剪驅動自由液面紊流邊界層的水面流場之結構。首先應用二維整體經驗模態分解法進行風浪表面熱圖像的分離，將影像區分為重力波、表面張力波、朗繆爾環流（Langmuir circulations）、以及風剪產生之沿流向擬序渦流（coherent vortices）所造成的結構，並計算各機制於不同風速下於熱圖像結構之貢獻。結果發現：在低風速時，擬序渦流造成的貢獻最大，而朗繆爾環流的貢獻最小；隨著風速上升，擬序渦流的影響持續減弱，而朗繆爾環流的貢獻則持續上升，直到與其他機制的貢獻相當。重力波之貢獻隨著風速的變化不大，但當波浪的微破碎（micro-breaking）事件發生時，破碎所產生的紊流於重力波峰處構成了明顯的跨流向結構，並被歸類於重力波所造成的結構，導致重力波的貢獻遠大於其他機制。而表面張力波所造成的貢獻於大多時候都小於其他機制，但於高風速時則明顯變大，其亦可能與波浪完全破碎所產生的跨流向渦流結構有關。擬序渦流所造成的水面條痕結構可進一步以圖像分割技術（image segmentation technique）分析，並探討其特性隨風剪力之變化。結果發現：條痕間距之分布於不同風速皆呈現對數常態分布；平均條痕間距隨著風速愈大而變小，而透過黏滯長度（viscous length）無因次化之平均條痕間距則隨著風速愈大而變大，不同於牆面紊流邊界層，其為 100 個黏滯長度單位之定值。

An image processing technique, which is based on 2-D ensemble empirical mode decomposition, is developed to decompose the thermal images at wind-wave surfaces with various wind conditions. Four components attributed to different flow processes, including the gravity waves, parasitic capillary waves, Langmuir circulations, and the streamwisely elongated coherent vortices induced by wind shear, and the corresponding contribution fractions are derived. In the lowest wind speed case, coherent vortices contribute the most to the surface signatures, and Langmuir circulations contribute the least. As wind speed grows, the contribution of coherent vortices decreases; in contrast, the contribution of Langmuir circulations keeps growing and becomes competitive with that of other flow processes in moderate wind conditions. The contribution of gravity waves does not change much with the present cases, except the micro-breaking case, in which the contribution of gravity waves is much larger than the others, since the signatures induced by spilling breakers are classified into the attribution of gravity waves. The capillary waves contribute little to the thermal images, but become significant at the present highest wind speed, which may also be attributed to the spanwisely elongated small vortices due to fully wave breaking. The surface streaky signatures attributed to the coherent vortices can be further identified utilizing the image segmentation techniques, and the statistics of spanwise streak spacing can therefore be calculated. It is found that the distributions of streak spacing from low to high wind speed match log-normal probability density distributions. Furthermore, the mean streak spacing decreases as wind speed grows; the non-dimensional mean streak spacing in viscous length scale, however, increases with wind speed, different from that of wall turbulent boundary layer, which is a constant 100 viscous unit.

中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 Data descriptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 Numerical simulation data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Infrared images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3 Signature decomposition methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.1 One-dimensional empirical mode decomposition . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2 Two-dimensional empirical mode decomposition . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.3 Direction-based component combination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23
3.4 Scale-based IMF combination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.4.1 Combination of wave-associated IMFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26
3.4.2 Combination of vortex-associated IMFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27
4 Decomposition of surface signatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31
4.1 Decomposition of numerical surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32
4.2 Decomposition of infrared image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35
5 Identification of streaky signatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
5.1 Detection of streak regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.2 Enhancement of streaky signatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44
5.3 Grouping of streak regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
6 Statistics of streak spacing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51
7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57
Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61
A The analyzed results of another set of experiments conducted in Aeolotron . . .63
B The effect of image rotation to signature decomposition . . . . . . . . . . . . . . . . . . .69
C The sensitivity test of the decomposition criteria . . . . . . . . . . . . . . . . . . . . . . . . .73
D Image enhancement methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77
D.1 Historgram equalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77
D.2 Gamma correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

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