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系統識別號 U0026-0201202023220200
論文名稱(中文) 以主流道入口和側壁形狀的最佳化來增進光流體分光器的效能
論文名稱(英文) Enhancing the performance of optofluidic beam splitters based on optimization of inlet and sidewall shapes of main channel
校院名稱 成功大學
系所名稱(中) 機械工程學系
系所名稱(英) Department of Mechanical Engineering
學年度 108
學期 1
出版年 108
研究生(中文) 李敦弘
研究生(英文) Tun-Hung Lee
學號 N16064315
學位類別 碩士
語文別 中文
論文頁數 77頁
口試委員 指導教授-吳志陽
口試委員-張錦裕
口試委員-溫昌達
中文關鍵字 微光流體分光器  折射率梯度  光追跡  田口法  基因演算法 
英文關鍵字 optofluidics  beam splitter  gradient refractive index  optimization  transmission efficiency 
學科別分類
中文摘要 本文探討一具有三維入口流道及圓弧形側流道壁的微光流體分光器,它會在主流道內產生漸進式的折射率梯度,引導進入主流道的光線往兩側前進,達到分光的功能。本研究使用氯化鈣水溶液(A,核心流體)及去離子水(B,包覆流體)作為流道內的工作流體,將流體由左右對稱的六個入口注入流道內,其中外圍的四個入口注入的是去離子水,包圍由中央注入口注入的氯化鈣水溶液,在主流道匯流後包覆流體會包覆住核心流體,形成中間高兩邊低的折射率分佈,由於注入口為左右對稱,進入主流道的光線會朝兩側高折射率區域前進,達到分光的效果,同時可以由控制入口流率的方式,改變流道內的折射率分佈,使進入流道內的光線產生不同的分光角。本研究使用ANSYS Fluent數質模擬軟體模擬流道內的速度場和濃度場,再以自行寫作的C++程式進行光追跡,模擬光線穿過流道時的軌跡。接著對流道的幾何以及流率參數進行最佳化,選定的7個參數如下,流體A入口流道寬度 、深度 、後段主流道長度 及A、B流體匯流處與主流道圓弧形流道壁端點距離 、入口總流率 、B流體1號入口和B流體流率的流率比 及A流體流率和總流率的流率比 ,先以田口法評估各項參數對分光器分光角和傳輸效率的影響程度,在經過程式模擬後,發現流率參數對表現的影響較大,並且各項參數對於分光角和傳輸效率的影響為相反,因此接著以基因演算法進行多目標最佳化,尋求最佳的參數組合,在以模擬驗證基因演算法的結果後,確認基因演算法能夠取得優於田口法的最佳化結果。
英文摘要 In this work, we investigate a micro optofluidics beam splitter, which forms gradient refractive index (GRIN) inside main channel to split the incident beam into two beams. The beam splitter consists of inlet channel, main channel with curved wall and outlet channel. Calcium chloride solution ( ) and deionized water( ) are used as the core and the cladding liquid, respectively. They are pumped into the channel through inlet channels with unequal height, so the cladding liquid would wrap around the core liquid to form GRIN in the main channel, which will split and focus the incident beams into two beams. ANSYS Fluent is used to simulate the concentration field inside the channel and Self-developed ray tracing code is employed to simulate light propagation. Different geometry and flow parameters will affect the transmission efficiency and the split angle. Genetic algorithm and the Taguchi method are used to optimize these parameters to achieve big split angle with good transmission. Response surface method (RSM) and radial basis function (RBF) are used to create surrogate model for genetic algorithm optimization. We find the following trends from simulation results. (i) The inlet channel depth ratio has great influence on both split angle and transmission efficiency of the beam splitter. (ii) Flow rate parameters have greater influence on the performance of the beam splitter than geometry parameter. (iii) The RBF method combined with genetic algorithm generates better optimization result than taguchi method does.
論文目次 摘要 I
Extended Abstract II
目錄 VIII
表目錄 XI
圖目錄 XII
符號說明 XIV
第一章 緒論 1
1-1 研究背景 1
1-2 文獻回顧 1
1.3 研究動機 5
1.4 本文架構 6
第二章 微光流體分光器設計、數值模擬與最佳化 7
2.1 微光流體分光器設計 7
2.2 測試用光學系統簡介 10
2.3 流體力學模型及流場數值模擬 11
2.3.1 流場假設與統御方程式 12
2.3.2 邊界條件 14
2.3.3 流場混合模擬 14
2.4 微分光器聚焦和分光效能評估 16
2.4.1 光束傳輸效率 16
2.4.2 微分光器分光角 17
2.5 微光流體分光器之參數最佳化 18
2.5.1 田口法 19
2.5.2 目標函數模型重建 23
2.5.3 基因演算法 25
第三章 結果與討論 28
3.1 簡介 28
3.2 流場與濃度場計算之參數測試 28
3.2.1 網格大小測試 29
3.2.2 殘餘值測試 30
3.3 光追跡測試 31
3.3.1 入射光包數測試 31
3.3.2 MLS內差資料點數測試 33
3.3.3 MLS基底矩陣元素數目測試 34
3.4 流道幾何與流率參數之田口法最佳化 35
3.5 多目標最佳化 41
3.5.1 目標函數模型重建 41
3.5.2 基因演算法結果 43
3.5.3 RBF法模擬結果呈現 49
3.5.4 RBF方法之再驗證 58
第四章 結論與未來展望 60
4.1 結論 60
4.2 未來展望 61
參考文獻 62
附錄 68
A.1 光追跡模擬 68
A.1.1 統御方程式 68
A.1.2 光線初始位置與入射方向 70
A.1.3 入射光線帶有知能量值 72
A.1.4 光線與流道壁的接觸處理 72
A.2 折射率函數重建 75
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