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研究生: 盧信甫
Xsin-Fu Lu
論文名稱: 以微粒循跡測速儀研究固體、液滴與氣泡誘發之聲射流
A Study of Acoustic Streaming Flows Induced by Solid, Droplet and Bubble Obstructions using Particle Tracking Velocimetry
指導教授: 田維欣
Wei-Hsin Tien
口試委員: 溫琮毅
Tsrong-Yi Wen
鄭逸琳
Yih-Lin Cheng
黃智永
Chih-Yung Huang
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 147
中文關鍵詞: 穩態射流微粒循跡測速儀聲射流流場可視化微粒影像測速儀微流體
外文關鍵詞: Steady Streaming, Acoustic streaming, Flow Visualization, Particle Image Velocimetry, Particle Tracking Velocimetry, Microfluidics
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  • 聲射流(Acoustic streaming)是一種透過高頻振盪,使流場中流體或邊界阻礙物交互作用產生之穩定流動現象。振動源可經由不同之媒介將振動傳入流體與流體產生交互作用誘發射流,常見之媒介包含氣泡或流場中之柱狀阻礙物。在本研究中則在微流道中設置了柱狀阻礙物、油滴與氣泡三種媒介,涵蓋固、液及氣相。實驗以流場可視化(Flow Visualization)以及微粒循跡測速儀(Particle Tracking velocimetry, PTV)技術比較其產生之流場。微流道採PDMS(dimethylsiloxane)為材料翻模製成,模具製作則以微銑削方法加工,以降低製造成本並減少流道表面粗糙度造成之背景反光。三種媒介物之幾何特徵尺寸皆為直徑為0.5 mm以及0.2 mm之半圓柱狀物。實驗中包含兩部分:第一部份透過放大倍率10倍以及20倍的顯微鏡以流場可視化觀察5微米的聚醯亞胺(polyimide)微粒在聲射流場中之流動軌跡。第二部分則以2.6微米的聚苯乙烯微粒(Polystyrene Particles),並利用20倍顯微鏡以微粒循跡測速儀技術量測聲射流之速度場。本研究中振盪頻率為1 kHZ、2 kHZ以及12 kHZ,並測試20 V以及40 V輸入電壓以觀察頻率及振幅對流場的影響。實驗結果顯示,氣泡在相同運行條件下可以產生最強的渦旋流動,但氣泡的大小較難以穩定保持。固體柱狀屏障引起的渦旋則是三者中最弱的,但其遠場具有較明顯之三維流場環流。液滴誘導的流動強度則在其兩者之間,且也可觀察到遠場環流特徵。以流場中最大絕對速度而言,氣泡引致之聲射流(21 mm/s)大於液滴(12 mm/s),而以固體柱狀屏障最小(2 mm/s)。另一方面,氣泡產生之聲射流較集中,在氣泡左右側有較大的瞬時絕對速度,絕大多數的情況下液滴所誘發的速度則大於氣泡,以多項式迴歸分析速度剖面資料則發現位於 Y/D=0.08附近氣泡有最快的絕對速度,其值為20 mm/s,而Y/D=0.66液滴則有最快的絕對速度其值為7 mm/s。


    Acoustic streaming is a steady flow phenomenon induced by high-frequency oscillation of the flow or obstructions in the flow regime. The oscillation can be transported through different media, usually by gas bubble or certain solid obstruction geometries in the flow. In this study, acoustic streaming flows inside micro-channels induced by three different media, which including air bubble, oil droplet and solid obstruction, are compared and investigated by flow visualization and Particle Tracking velocimetry (PTV). The micro-channels are made by poly(dimethylsiloxane) (PDMS) using a standard fabrication process for a microfluidic device. The casts are made by micro-milling process to reduce the manufacturing cost and minimize the background reflection due to channel surface roughness. The characteristic dimensions of the media are 0.2 mm and 0.5 mm in diameter, and the oscillation generated by piezoelectric actuators has frequencies of 1 kHZ, 2 kHz and 12 kHz and input voltages of 20 V and 40 V, respectively. The particle trajectories are visualized by a microscope with 10X and 20X magnification and long exposure experiments using 5 μm polyimide particles. The velocity fields are measured by PTV using 2.6 μm polystyrene tracer particles. The experimental results show that the gas bubble creates the strongest vortical streaming flow under the same operating condition, but the size of the bubble is hard to maintain steadily. The solid obstruction induced vortical flow is the weakest of the three, but the streaming flow in the far field has a large 3-D circulation feature. The strength of the droplet-induced streaming flow is in between the other two types, and a similar far field circulation feature is observed. PTV results show that bubble-induced acoustic streaming has the largest peak absolute velocity at 21 mm/s, followed by droplet-induced flows at 12 mm/s, and the solid obstruction has the smallest velocity of 2 mm/s. On the other hand, the streaming flow induced by bubbles is more concentrated at the side, but on average the droplet-driven streaming flows have larger mean velocity. The second order curve-fitted velocity profiles show that at Y/D = 0.08 the bubble-driven flow has the largest absolute velocity of 20 mm/s, and at Y/D = 0.66 the droplet-driven flow has the largest absolute velocity at 7 mm/s.

    目錄 摘要 I Abstract III 致謝 V 目錄 VI 圖表目錄 IX 第 1 章 緒論 1 1.1介紹 1 1.2文獻回顧 1 1.2.1 聲射流(Acoustic streaming) 1 1.2.1.1固體幾何產生的聲射流渦漩 2 1.2.1.2 氣體幾何產生的聲射流渦漩 6 1.2.1.3 氣泡大小的控制 12 1.2.1.4 其他微流體的應用 14 1.2.1.6 光學流場量測技術 16 1.2.1.6.1 微粒影像測速儀(Particle image velocimetry,PIV) 16 1.2.1.6.2微粒循跡測速儀(Particle tracking velocimetry,PTV) 19 1.2.2小結 20 1.3研究目的 22 1.4論文架構 22 第 2 章 實驗原理與方法 23 2.1實驗原理 23 2.1.1聲射流渦旋原理 23 2.1.2壓電陶瓷片原理 27 2.1.3 微粒循跡測速儀工作原理 28 2.2實驗方法 29 2.2.1聲射流微流體裝置製作流程 29 2.2.2實驗量測系統設置 43 2.3實驗步驟流程 57 2.4實驗設置參數 60 第 3 章 結果與討論 63 3.1利用視流法觀察 63 3.1.1固體阻礙物視流法觀察結果 63 3.1.2 氣體阻礙物視流法觀察結果 65 3.1.3 液體阻礙物視流法觀察結果 66 3.1.4 小結 67 3.2透過PTV量化處理 69 3.2.1固體阻礙物 71 3.2.2氣體阻礙物 78 3.2.3液體阻礙物 84 3.2.4 小結 91 第 4 章 結論與建議 101 4.1 結論 101 4.2建議與未來工作 102 第 5 章 附錄 104 附錄1 Arduino 訊號 Code 104 附錄2 利用Matlab將灰階影像平均成軌跡圖Code 105 附錄3 利用Matlab將影像上下拆開Code 108 附錄4 利用Matlab將奇數與偶數影像分別製作背景並取得僅有微粒的影像Code 109 附錄 5 利用Matlab修改影像名稱以及附檔名 Code 113 附錄 6 利用Matlab 合併PTV產生的資料,並繪出向量圖 Code 113 附錄 7 利用Matlab 將影像二值化Code 114 附錄 8 利用Matlab 刪除錯誤的向量資料Code 115 附錄 9 利用Matlab 將PTV輸出的資料轉為Dat檔Code 116 附錄 10 利用ipython notebook(jupyter) 取得特定位置資料 Code 118 附錄 11 利用ipython notebook(jupyter)取得不同相位在特定軸上的資料並透過matplotlib套件繪圖 Code 118 附錄 12 利用ipython notebook(jupyter)取得各垂直及水平線上所有資料並透過matplotlib套件繪圖 Code 119 附錄 13 利用ipython notebook(jupyter)並透過pandas整理資料 Code 120 附錄 14 利用ipython notebook(jupyter)將X軸資料取平均並利用matplotlib套件繪出Y軸上三相的絕對速度Code 121 附錄 15 利用ipython notebook(jupyter) 透過scikit-learn製作多項式回歸曲線 Code 122 附錄 16 利用ipython notebook(jupyter) 透過scikit-learn製作B-spline回歸曲線 Code 122 附錄 17 利用ipython notebook(jupyter)並透過seaborn套件將資料繪製成對圖表圖 Code 124

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