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研究生:黃建榮
研究生(外文):Huang Chien-Jung
論文名稱:基於改良型基因演算法之高壓氫氣鋼瓶結構最佳化設計與使用者介面之開發
論文名稱(外文):Optrmal design of high pressure hydrogen cylinder structure and user interface development Based on an improved genetic algorithm
指導教授:郭俊賢郭俊賢引用關係
指導教授(外文):CHUN-Hsien Kuo
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:應用工程科學研究所
學門:工程學門
學類:綜合工程學類
論文種類:學術論文
論文出版年:101
畢業學年度:100
語文別:中文
論文頁數:72
中文關鍵詞: 套裝軟體 求解器 危險性 關鍵字 演算法 套裝軟體 求解器 危險性 關鍵字 演算法
外文關鍵詞: computer AND
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摘要
由於氫氣密度的很低,一但氫氣外洩,很快的氫氣將會往上擴散被大量的空氣稀釋,雖然不會累積濃度,但還是具備一定之危險性,例如未來若是運用在汽車上等等之密閉空間,更是具有一定之危安性。所以本研究之主要目的為建立一套最佳化軟體以設計應用於氫氣燃料電池之氫氣高壓鋼瓶。然而當高壓鋼瓶長期處於一個內壓並且反覆的加載及卸載就會提升發生破裂意外事件之機率,而該破裂意外通常都是在壁面之應力集中(Stress concentration)處所引起突然之破裂,這是由於應力集中對於高壓鋼瓶的長期使用上,將會造成材料的疲勞破裂。而應力集中處都是位於容器殼體中的不連續接面之區域,所以該區域乃為高壓鋼瓶之外形設計中最需要重視的地方。
本研究所提出之最佳化軟體採用有限元素法(Finite element method)並結合吾人自行開發之改良型基因演算法(Non-tradition Genetic Algorithms, NGA)作為最佳化搜尋氫氣高壓鋼瓶外型的方法,而在介面方面則是運用MATLAB程式語言進行撰寫。其中之有限元素法是運用商業套裝軟體ANSYS作為正向解之計算處理求解器。在氫氣高壓鋼瓶分析方面,主要針對典型連結噴嘴之氫氣高壓鋼瓶。研究中分別針對其處於一穩定內壓下之壁面應力分佈進行探討;以決定最適合之幾何形狀參數。而最佳化之目標函數為整體模型之最小Von Mises應力值,以達到降低應力之峰值,並均勻整體壁面之應力。
研究中將藉由吾人所撰寫之最佳化軟體去改善氫氣高壓鋼瓶之整體壁面的應力分佈,藉此提高容器之使用壽命年限。本最佳化軟體將建立一個有效的自動化電腦輔助設計過程的方法,這將有助於未來之工業發展。

關鍵字: 氫氣燃料電池、氫氣高壓鋼瓶、使用者介面、最佳化設計、基因演算法
Abstract
Since the hydrogen density is very low, Once the hydrogen releases outside, the hydrogen will proliferate upward by the massive air dilution quickly. It will not accumulate the density, but it still exists certain risk. For example, Being utilized in the automobile or other airtight spaces, might cause somewhat danger . Therefore the main purpose of this research is to establish a set of optimization software to design high pressure steel cylinder of hydrogen in the hydrogen fuel cell.
High pressure steel cylinder’s long time use causing stress concentration, will make the material fracture. For example, when the high pressure steel repeated load in an intrinsic pressure, it will promote to burst accident’s probability. However, stress concentration is all in the region of non-continual composition. Therefore this region will be the most important of the design in the high pressure steel cylinder.
This research proposed the best software by Finite element method and also combined with Non-tradition Genetic Algorithms, NGA to be the best way to search the outlook of high pressure steel cylinder. For instance, with MATLAB to composition in the interface and Finite element method use ANSYS to be the computing solver of the direct solution. In the hydrogen of high pressure steel cylinder, the most part is to be aimed at the hydrogen of high pressure steel cylinder of combined nozzle and is also probed into stress to decide the most suitable parameter for geometric figure of. The best objective function is the least Von Mises stress to reach reducing high stress and also balance all stress of shell surface.
This research is to improve stress distribution of hydrogen high pressure steel cylinder by the present proposed best software and to raise the working valid period of container. The study builds up a valid automatical method of the computer design processing to help develop industry in the future.
Keywords: Hydrogen fuel cells、Hydrogen bomb、The user interface、Optimization design、Genetic algorithms
目錄

摘要 I
ABSTRACT II
致謝 IV
目錄 V
圖目錄 VII
表目錄 VIII
符號索引 IX
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.2.1. 燃料電池 2
1.2.2. 燃料電池之優點 3
1.2.3. 氫氣燃料電池之危安性 4
1.3 研究目的與方法 5
1.4 文獻探討 7
1.5 論文架構 10
第二章 數值分析與驗證 11
2.1 有限元素法 11
2.2 驗證數值模擬之基本模型建立 12
2.3 驗證數值模擬之比較結果 13
第三章 最佳化方法與架構 25
3.1 最佳化設計過程 26
3.2 傳統型基因演算法 28
3.2.1. 基因演算法之組織架構 28
3.2.2. 初始值設定 29
3.2.3. 運算因子 31
3.2.4. 收斂準則 33
3.3 改良型基因演算法 34
3.3.1. 非傳統之選擇複製 34
3.3.2. 非傳統之收斂準則 35
3.3.3. 可更新之族群大小 35
3.3.4. 基因資料庫 35
3.4 傳統型與改良型基因演算法的差異與優點 36
3.4.1. 基因演算法之優點 36
3.4.2. 基因基因演算法之缺點 37
3.4.3. 改良型基因基因演算法之改善 37
3.5 最佳化搜尋器之架構 38
3.5.1. 最佳化搜尋器之使用者介面 38
3.6 最佳化模型描述 39
第四章 結果與討論 53
4.1 模擬分析 53
4.2 收斂結果 54
4.3 高壓鋼瓶之最佳化設計結果 55
第五章 結論與建議 64
5.1 結論 64
5.2 未來研究方向 65
參考文獻 67
作者簡歷 72

圖目錄
圖1 試驗壓力容器之配置 16
圖2 試驗壓力容器之尺寸示意圖 17
圖3 試驗壓力容器之材料非線性應力-應變曲線 18
圖4 簡化之材料應力-應變曲線 19
圖5 SOLID186幾何描述 20
圖6 壓力容器模型之有限元素網格 21
圖7 內壓2.25MPA之VON MISES應力分佈 22
圖8 內壓2.25MPA之VON MISES應力分佈(A)文獻[14]結果(B)本研究結果 23
圖9 試驗壓力容器之內壓為極限爆破壓力7.4MPA 24
圖10 二階函數的極值關係 (A)全域極值(絕對極值) (B)區域極值(相對極值) 43
圖11三階函數的極值關係 (A)立體圖形 (B)圍線輪廓圖 44
圖12傳統型基因演算法之最佳化流程圖 45
圖13改良型基因演算法之最佳化流程圖 46
圖14最佳化搜尋器之流程架構 47
圖15最佳化搜尋器之使用者介 48
圖16 PLANE82幾何描述 49
圖17網格數量對於不連續接面的應力分佈之影響 50
圖18有限元素模型之網格分佈 51
圖19最佳化模型 52
圖20有限元素分析之模擬結果 56
圖21變數對應力分佈之影響 57
圖22初始演化族群於20之收斂趨勢 58
圖23初始演化族群於25之收斂趨勢 59
圖24初始演化族群於30之收斂趨勢 60
圖25初始演化族群於35之收斂趨勢 61
圖26最佳化過程後之模型 62

表目錄
表1 試驗壓力容器之尺寸配置 15

符號索引
= 應力 (MPa)
= 最大允許應力 (MPa)
= Von Mises等效應力 (MPa)
= 應變
= 縱向應力 (MPa)
= 切向應力 (MPa)
= 徑向應力 (MPa)
= 極限強度 (MPa)
γ = 蒲松比
= 焊接係數
= 密度
= 楊氏系數 (MPa)
= 工作壓力 (MPa)
= 桶身之內壁半徑 (mm)
= 球形穹頂封頭之內壁半徑 (mm)
= 容器之球形穹頂封頭的最小安全厚度 (mm)
= 桶身的壁面最小安全厚度 (mm)
= 安全係數
= 目標函數
下標
= 標號
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