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標題: 上游渠坡對自由跌水沖擊特性之影響與類神經網路模式驗證(I)
Effect on Impact Characteristics of Upstream Slope Bed by Free Overfall and Model Verification Using ANNs (I)
作者: 陳正炎
關鍵字: 應用研究;Free Overfall Flow;土木水利工程類;自由跌水流;壓力分佈;上游渠床坡度;類神經網路;Pressure Distribution;Upstream Bed Slope;Artificial NeuralNetwork
近年來為了河道治理或取水等目標,經常於河道中設置跌水工、攔河堰或防砂壩等工程設施,雖可穩定上游河道,但因構造物上下游高度相差過大,使高速水流瞬間衝擊下游面,或稱自由跌流現象,造成下游面河床承受大量壓力,並導致水工結結構物之破壞。依據台灣965座的防砂壩資料統計,防砂壩上游淤砂坡度S小於6%,共796座占全部965座之82%。為探究當上游渠床坡度S改變,其沖擊效應為若何。本計畫由不同的上游渠床坡度(S=0~6 %) 、不同跌水高度(H=0.15~0.30 m)及不同流量(q=0.007~0.041 cms/m)進行渠槽試驗,於底床埋設壓力量測系統,以不干擾流場下量測自由跌水下游之壓力分佈,且應用類神經網路模式,預測試驗所得水流特性參數,並藉渠槽試驗資料點作驗證,以評估其精確性。

In recent years, the civil structures crossing the river have been widely used in bothnatural and artificial channels to process the water resource management. Thesestructures usually lead to a sudden vertical change of channel slope and induce a freeover-fall flow, and the large impact force of a free over-fall flow usually damages the civilstructure. According to a local statistical result in Taiwan, 796 out of 965 sabo dam (about82%) possess an upstream bed slope due to sand deposit less than 6%. In this research,the pressure transducers, which did not disturb the flow field, were set up to measure thepressure distributions along the streamwise direction downstream of the free overfall. Inthe study, the extent of flow characteristics is explored by varying the bed slope (S=0 to 6%), the drop height (H=0.15 to 0.30 m) and the discharge per unit width (q=0.007 to 0.041cms/m) using channel tests. Besides, the experimental data will be train and validate theartificial neural network (ANN).
其他識別: NSC99-2221-E005-044
Appears in Collections:土木工程學系所

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