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研究生: 蔡依璇
Tsai, Yi-Hsuan
論文名稱: 基於類神經網路及基因演算法之生質柴油純化分離微流元件最佳化設計
Application of Artificial Neural Network and Genetic Algorithm for Optimization of Biodiesel Purification and Separation by Microfluidic Device
指導教授: 葉思沂
Yeh, Szu-I
學位類別: 碩士
Master
系所名稱: 工學院 - 航空太空工程學系
Department of Aeronautics & Astronautics
論文出版年: 2023
畢業學年度: 111
語文別: 中文
論文頁數: 70
中文關鍵詞: 生質柴油純化微流體晶片類神經網路基因演算法
外文關鍵詞: Biodiesel Purification, Microfluidic Device, Artificial Neural Network, Genetic Algorithm
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  • 關於生質柴油的產製過程,需在轉酯化後進行純化的步驟,將先前反應中加入的過量甲醇萃取出,而本研究透過微流體具有高表面積與體積比的特性,增加萃取反應的接觸面積,即可加快反應速率,並結合類神經網路與基因演算法,使得在減少實驗量的同時獲得符合限制條件之最佳實驗參數配置。
    本研究藉由結合微萃取器與微分離器的設計,讓生質柴油得以在進行純化反應後與檸檬酸酸洗水溶液分離,透過兩種反應區域長度0.5 m與2 m、兩種檸檬酸濃度0.5 wt%與1 wt%以及不同的生質柴油與檸檬酸水溶液流率的搭配,探討各種參數對於生質柴油純化與分離的效率影響。在反應區長度加長時,會因整體反應時間增加,使得生質柴油的酸值提升,但對於甲醇萃取的部分,2m的反應區長度僅於油相流率較高時相較於0.5 m有較低的甲醇含量。在檸檬酸的濃度比較中,改變檸檬酸濃度僅會改變生質柴油的酸值高低,並不會對於甲醇的萃取效率有所影響。而關於兩相流率組合比較,發現在固定水相流率,且提高油相流率時,會導致生質柴油內部的甲醇重量百分比上升,而當改為固定油相流率,逐漸提升水相流率時,則會產生甲醇含量先降低後上升的情形,推估此原因為在增加水相流率時,會有較多的水相可供反應,但同時會造成毛細管分離器的分離效果降低,使得部分水溶液經由毛細管流至生質柴油的出口。並再透過實驗驗證由類神經網路與基因演算法所計算出的最佳參數配置,證明該方法能成功預測出合適的參數組合。

    In biodiesel manufacturing, a crucial purification step follows transesterification to remove excess methanol. This study utilizes microfluidics, known for its high surface area to volume ratio, to enhance the contact area and accelerate the reaction rate. Additionally, the neural network and genetic algorithm are applied in this research to reduce the number of experiments while simultaneously obtaining the optimal experimental parameter configuration that complies with the specified constraints. This research utilizes a combination of microextractor and microseparator designs to enable the separation of biodiesel from the citric acid washing solution after the purification reaction. By varying parameters such as two reaction region lengths (0.5 m and 2 m), two citric acid concentrations (0.5 wt% and 1 wt%), and different flow rates of biodiesel and citric acid solution, the efficiency of biodiesel purification and separation are investigated. When the reaction zone length is increased, the overall reaction time also increases, resulting in higher acid value of the biodiesel. However, regarding methanol extraction, the 2m reaction region length shows a lower methanol content only when the oil phase flow rate is higher compared to 0.5m. Changing the citric acid concentration solely affects the acid value of the biodiesel and has no impact on the efficiency of methanol extraction. In the comparison of flow rate combinations between the two phases, it is observed that increasing the oil phase flow rate while keeping the water phase flow rate fixed leads to a higher weight percentage of methanol. On the other hand, when fixing the oil phase flow rate and gradually increasing the water phase flow rate, the methanol content shows an initial decrease followed by an increase. This phenomenon is likely caused by raising the water phase flow rate, which offers additional water phase for the extraction. Nonetheless, it decreases the efficiency of microseparator, enabling some aqueous solution to flow through the capillary and reach the outlet of biodiesel.
    Furthermore, the study validates the optimal parameter configuration calculated by the neural network and genetic algorithm through experiments, confirming the successful prediction of suitable parameter combinations.

    摘要 I Abstract II 致謝 XV 目錄 XVI 表目錄 XIX 圖目錄 XX 符號索引 XXIV 第一章 緒論 1 1.1研究背景 1 1.2研究目的 2 第二章 文獻回顧 3 2.1 生質柴油純化方法 3 2.2微萃取器型式 4 2.3微型分離器 10 2.4生質柴油量化分析 13 2.4.1近紅外線圖譜分析法 13 2.4.2氣相層析法 14 2.4.3核磁共振分析法 16 2.5微流體系統最佳化 18 2.5.1響應曲面法 18 2.5.2類神經網路與基因演算法 20 2.6文獻回顧總結 21 第三章 研究方法 23 3.1純化分離晶片設計與參考 23 3.2微流體晶片製作 25 3.2.1微影製程 25 3.2.2流道翻製 31 3.3實驗流體製備 33 3.4實驗架設 34 3.5實驗方法 35 3.5.1兩項流體分離觀測 35 3.5.2酸值分析 36 3.5.3儀器分析方法 37 3.6實驗參數優化方法 39 3.6.1類神經網路建立 39 3.6.2基因演算法 42 3.7甲醇萃取效率最佳化驗證 43 第四章 實驗結果與討論 44 4.1液-液萃取之液珠生成 44 4.2毛細管兩相分離結果 45 4.2.1兩相流率對於分離效果之影響 46 4.2.2反應區域長度對於分離效果之影響 47 4.2.3毛細管分離結果小結 48 4.3萃取反應之結果分析 49 4.3.1 生質柴油之酸值比較 49 4.3.2生質柴油之甲醇含量比較 53 4.4萃取反應之實驗參數最佳化 60 4.4.1甲醇重量百分比0.2 wt% 60 4.4.2甲醇重量百分比0.15 wt% 62 第五章 結論與未來展望 64 5.1結論 64 5.2未來展望 65 參考文獻 66

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