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研究生:黃宏信
研究生(外文):Hung-Shin Huang
論文名稱:自由跌水作用下坡度渠流之水力特性研究
論文名稱(外文):Hydraulic Characteristics of Free Overfall-Impacted Channel Flow over Sloping Bed
指導教授:陳正炎陳正炎引用關係
指導教授(外文):Jen-Yan Chen
學位類別:博士
校院名稱:國立中興大學
系所名稱:土木工程學系所
學門:工程學門
學類:土木工程學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:150
中文關鍵詞:自由跌水渠床坡度沖擊特性視窗化類神經網路
外文關鍵詞:Free Overfall FlowBed SlopesImpact CharacteristicsWindows-BasedArtificial Neural Network
相關次數:
  • 被引用被引用:7
  • 點閱點閱:126
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近年來為了河道治理或取水,經常於河道中設置跌水工、攔河堰或防砂壩等水利工程設施構造物,且因工程設施上下游產生高差,而高速水流流動所產生之水舌沖擊力最具沖擊能量及沖刷潛勢,常導致水工結構物之毀損破壞。依據台灣60條較大河川資料統計,河道平均坡度小於7%共43條,占全部60條河川之72%。為探究當渠床坡度改變,其相關水力沖擊特性參數為何,本文由不同的渠床坡度(S=0%、3%、6%、9%)、改變跌水高度(H=0.15m、0.20m、0.25m、0.30m)及配合不同單寬流量(q=0.0076~0.0402cms/m)進行單階自由跌水渠槽試驗,且在自由跌水下游渠床埋設壓力量測系統,以不干擾流場下量測下游之縱向渠床壓力水頭分佈,進一步分析其水力沖擊特性參數。為使設計者更為便捷及設計後圖示之展示快速,將利用自由跌水渠槽試驗所獲得的經驗式,藉由VB(Visusal Basic)程式語言,建構自由跌水工設計之視窗化,且應用類神經網路(Artificial Neural Network, ANN)模式,推估模擬自由跌水渠槽試驗所得水力沖擊特性參數,並藉試驗資料點作驗證,以評估其精確性。
研究結果發現,在渠槽試驗方面,最大沖擊壓力水頭(Hpd)、沖擊位置(Ld)、單寬沖擊力(Fe)及能量損失(△E)與渠床坡度(S)呈正相關;而水墊區水深(Yp)、沖擊角度(θ)及尾水深(Y1)與渠床坡度(S)為負相關。視窗化設計方面,開發出可以呈現自由跌水之水力沖擊特性參數,設計結果示意圖及計算表單之視窗化模組。倒傳遞類神經網路模式方面,在推估自由跌水渠槽試驗所得水力沖擊特性參數,都有良好之成效。研究結果對於在自由跌水相關參數設計及推估模擬上,提供一便利且精確的方法。

In recent years, the hydraulic structures crossing the river have been widely used in both natural and artificial channels to process the water resource management. These structures usually lead to a sudden vertical change of channel slope and induce a free over-fall flow, and the large impact force of a free-falling nappe due to free over-fall flow usually damages the hydraulic structure. According to statistics of the sixty largest rivers in Taiwan, there are 43 rivers (72 percent of the 60 rivers) with average slope less than 7 percent. This study used the pressure transducers, which did not disturb the flow field, were set up to measure the pressure distributions along the streamwise direction downstream of the free over-fall. The experiment includes the different drops as 0.15 m, 0.20 m, 0.25 m and 0.30 m with the range of discharges 0.0076-0.0402 cms/m for different bed slopes as 0 %, 3 %, 6 % and 9 %. Furthermore, with application of window-based design of free over-fall, the instant design information can be acquired conveniently in a short time by computer. Besides, the experimental data will be trained and validated by the artificial neural network (ANN).
The experimental results indicate that the maximum impact pressure head (Hpd), the impact position (Ld), the unit width of the impact force (Fd) and the energy loss (△E) appear to be proportional to the bed drop of the downstream channel (S). The depth of pool (Yp), the nappe impact angle (θ) and the depth of tailwater (Y1) is inversely proportional to the bed drop of the downstream channel (S). Besides, this study developed a window-based design module of single step free over-fall through Visual Basic program and the figures of hydraulic impact parameters and a list table of computed result can be displayed. Moreover, the test results showed that the artificial neural network method provided accurate estimations for the hydraulic impact parameters of free overfall flow.

謝 誌 I
中 文 摘 要 II
Abstract III
目錄 V
圖目錄 VIII
表目錄 XI
附圖目錄 XIII
符號說明 XV
第一章 緒 論 1
1-1 研究動機 1
1-2 研究目的 2
1-3 本文組織 3
第二章 文獻回顧 5
2-1 自由跌水沖擊特性參數 5
2-1-1 壓力水頭分佈及沖擊位置 6
2-1-2 水墊區水深及尾水深 11
2-1-3 沖擊角度及沖擊力 14
2-1-4 能量變化 16
2-2 類神經網路 19
2-3 視窗化研究 22
第三章 理論分析 23
3-1 壓力水頭分佈模式 23
3-2 自由跌水沖擊特性參數 25
3-2-1 沖擊位置 25
3-2-2 沖擊力 27
3-2-3 沖擊角度 30
3-3 水流能量變化 30
第四章 渠槽試驗與結果 32
4-1 試驗設計 32
4-1-1 試驗設備與佈置 32
4-1-2 試驗步驟與條件 35
4-2 渠槽試驗結果分析 39
4-2-1 自由跌水下游渠床壓力分佈 39
4-2-2 自由跌水沖擊特性參數 47
4-3 力學觀點探討自由跌水 60
4-3-1 自由跌水沖擊力 60
4-3-2 水流能量變化 68
4-4 坡度效應 72
第五章 視窗化設計 74
5-1 視窗化建構 74
5-1-1 水力特性參數數值演算 74
5-1-2 視窗化架構 76
5-1-3 現地資料調查 79
5-2 模式操作與結果 81
5-2-1 視窗化操作 83
5-2-2 VB模式與試驗結果比較 85
5-3 實例演算 92
第六章 類神經網路模式與應用 99
6-1 類神經網路自由跌水沖擊特性模式 99
6-1-1 人工神經元模型 99
6-1-2 類神經網路學習過程 100
6-1-3 多層感知機 101
6-2 類神經網路應用 104
6-2-1 資料正規化 104
6-2-2 類神經網路訓練條件 105
6-2-3 類神經網路訓練與模擬 108
6-3 類神經網路結果與模式比較 110
第七章 結論與建議 117
7-1 結論 117
7-2 建議 123
參考文獻 124
附圖 128
簡歷及學術著作 147



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