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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81038完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李百祺(Pai-Chi Li) | |
| dc.contributor.author | Tzu-Ning Liao | en |
| dc.contributor.author | 廖梓甯 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:27:27Z | - |
| dc.date.available | 2022-02-21 | |
| dc.date.available | 2022-11-24T03:27:27Z | - |
| dc.date.copyright | 2022-02-21 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-09 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81038 | - |
| dc.description.abstract | 聲穿孔作用是指利用超音波與超音波對比劑的相互作用使細胞膜產生穿孔現象，已被廣泛研究於輸送藥物、蛋白質和基因。目前已知可引發聲穿孔作用的主要機制之一為慣性穴蝕效應，但慣性穴蝕效應引發時造成的微氣泡破裂，可能會帶來非必要性的細胞死亡，因此期望找到其他方法來引發聲穿孔作用。在我們過去以聲學激發液滴汽化同步光學激發液滴汽化為基礎的聲穿孔研究中，我們已展示液滴反覆汽化凝結的機制，可產生一定劑量的聲穿孔效應，此顯示重複性汽化可引發聲穿孔作用的潛在性。為了近一步瞭解重複性汽化的機制，適當的數值分析方法是必要的。本篇研究將結合流體力學及超音波原理，以數值分析方法建立液滴重複性汽化模型，並在模型中發現可重複性汽化較容易發生於聲壓小週期長的參數條件。此外，為改善傅立葉分析在判斷可重複性汽化發生率的限制，本研究亦採用有限基函式之小波轉換進行具有不同波形之訊號分析，發現當其在高頻區間的能量超過設定之閥值時，能有大於 90 %之正確率找出液滴相變之發生，並可加入每微秒之相變次數提高可重複性汽化之判別。此外，我們也發現小波轉換於低頻高頻間的能量比值可為另一個判定汽化及穴蝕效應的方法。最後，以機器學習進行自動化分析時，發現傅立葉轉換在汽化及慣性穴蝕效應的分析上仍為較佳的指標，而小波轉換則可協助分析重複性汽化之發生機率及次數，因此未來可結合小波與傅立葉轉換用於汽化、重複性汽化與穴蝕效應之分析，協助臨床上更有效率的制定治療策略。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:27:27Z (GMT). No. of bitstreams: 1 U0001-0202202200351500.pdf: 17544955 bytes, checksum: 9bafbd3a0e2ded94a9e50faef96929c0 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 口試委員會審定書 i 誌謝 i 中文摘要 ii ABSTRACT iii 目錄 iv 圖目錄 viii 表目錄 xiv Chapter 1 緒論 1 1.1 聲穿孔作用與癌症腫瘤治療 1 1.2 微米氣泡與奈米液滴 2 1.2.1 微米氣泡 2 1.2.2 奈米液滴 4 1.3 液滴汽化 6 1.4 穴蝕效應 9 1.5 可重複性汽化效應 11 1.6 研究動機 13 Chapter 2 研究方法 14 2.1 模型架構 14 2.2 液滴汽化模型 14 2.2.1 聲學激發液滴汽化模型 16 2.2.2 光聲激發液滴汽化模型 19 2.2.3 光學激發液滴汽化模型 21 2.2.4 模擬中的液滴汽化及凝結定義 22 2.3 氣泡震盪模型 24 2.3.1 氣泡震盪模型簡介 24 2.3.2 模擬中的氣泡穴蝕效應定義 26 2.4 粒徑變化與分散壓力 27 2.4.1 粒徑變化轉換為壓力公式 27 2.4.2 壓力所代表的訊號含義 28 2.4.3 加入背景訊號 28 2.5 訊號分析 29 2.5.1 傅立葉轉換 29 2.5.2 小波分析—汽化與凝結效應 30 2.5.3 小波分析—汽化與慣性穴蝕效應 33 2.6 機器學習分類模型 36 2.6.1 分類器 36 2.6.2 訊號特徵模型 37 2.6.3 訊號模型 — 兩種訊號定義 39 Chapter 3 實驗結果 40 3.1 聲學激發液滴汽化模型 40 3.1.1 聲壓 40 3.1.2 液滴外徑 43 3.1.3 彈性模數 44 3.1.4 超音波週期數目 47 3.1.5 液滴氣態內徑 50 3.1.6 頻率 51 3.2 光聲激發液滴汽化模型 52 3.2.1 聲壓 52 3.2.2 液滴外徑 53 3.2.3 彈性模數 54 3.2.4 超音波週期數目 55 3.2.5 液滴氣態內徑 56 3.2.6 頻率 57 3.3 光學激發液滴汽化模型 58 3.4 液滴可重複性汽化效應與慣性穴蝕效應分析 59 3.4.1 傅立葉分析 59 3.4.2 小波分析－汽化與凝結效應 61 3.4.3 慣性穴蝕效應分析 65 3.5 機器學習之分類器結果 71 3.5.1 訊號特徵分類結果 71 3.5.2 傅立葉定義及小波定義分類結果 74 Chapter 4 討論 76 4.1 模擬總結 76 4.1.1 模擬中改變聲壓、頻率、激發週期對汽化與慣性穴蝕效應之影響 76 4.1.2 模擬中液滴外徑內徑及彈性模數對汽化與慣性穴蝕效應之影響 78 4.1.3 光學激發液滴汽化對於聲學激發液滴汽化之影響 79 4.2 實際實驗數據與模擬結果在分析後的誤差討論 81 4.2.1 實驗與模擬中的交互作用及形變 82 4.2.2 液滴氣態內核的起始位置及大小 84 4.3 模擬中的訊號分析 85 4.3.1 汽化效應分析 85 4.3.2 慣性穴蝕效應分析 86 4.4 分類器結果 88 4.4.1 訊號特徵分類結果於模擬與實驗的差異 88 4.4.2 傅立葉與小波轉換分類適用性 89 4.5 模型實用性討論 89 Chapter 5 結論 91 Chapter 6未來工作 93 6.1 液滴形變 93 6.2 液滴交互作用 93 6.3 以微流道系統製作粒徑大小一致的液滴 95 6.4 長短期記憶神經網絡學習模型 98 參考文獻 99 | |
| dc.language.iso | zh-TW | |
| dc.subject | 聲穿孔效應 | zh_TW |
| dc.subject | 氣泡震盪模型 | zh_TW |
| dc.subject | 液滴汽化模型 | zh_TW |
| dc.subject | 小波轉換 | zh_TW |
| dc.subject | 傅立葉轉換 | zh_TW |
| dc.subject | 汽化效應 | zh_TW |
| dc.subject | 穴蝕效應 | zh_TW |
| dc.subject | Bubble Oscillation Model | en |
| dc.subject | Fourier Transform | en |
| dc.subject | Wavelet Transform | en |
| dc.subject | Droplet Vaporization Model | en |
| dc.subject | Sonoporation | en |
| dc.subject | Cavitation | en |
| dc.subject | Vaporization | en |
| dc.title | 奈米液滴汽化與後續穴蝕效應之數值模擬 | zh_TW |
| dc.title | Numerical modeling of nanodroplet vaporization and concomitant cavitation | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 謝寶育(Chi-Lin Chen),廖愛禾(Li-Sheng Chen),沈哲州(Ming-Fang Yen),(Shin-Liang Pan) | |
| dc.subject.keyword | 聲穿孔效應,穴蝕效應,汽化效應,傅立葉轉換,小波轉換,液滴汽化模型,氣泡震盪模型, | zh_TW |
| dc.subject.keyword | Sonoporation,Cavitation,Vaporization,Fourier Transform,Wavelet Transform,Droplet Vaporization Model,Bubble Oscillation Model, | en |
| dc.relation.page | 109 | |
| dc.identifier.doi | 10.6342/NTU202200264 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-02-10 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| 顯示於系所單位： | 生醫電子與資訊學研究所 | |
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