توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Trend of maximum discharge for effective parameters of outflow hydrograph due to piping
اطلاعات انتشار: دومین کنفرانس بین المللی علوم و مهندسی، سال
تعداد صفحات: ۱۰
Dams provide society with essential benefits such as water supply, flood control, recreation, hydropower, and irrigation. When dam failure happens, the impounded water runs through the breach, and it leads to death of people and destruction of structures in the downstream valley. According to reports by International Commission on Large Dams (ICOLD, 1973), about 38 percent of all dam failures are caused by overtopping of the dam due to inadequate spillway capacity, about 33 percent of dam failures are caused by seepage through the dam, about 23 percent of the failures are related to foundation problems, and the remaining failures are caused by slope embankment slides, damage, or liquefaction from earthquakes. Due to loss of life, environmental damage and economic reflection, prediction of dam breach and outflow hydrograph should be considered. The breach is an opening in embankment dam which is created by piping or overtopping. Piping occurs where the body of dam is permeable. This phenomenon starts from downstream and expands to upstream in the body of the dam. When the top point of breach reaches water level, great amount of water enters into the breach, and causes dam failure. The purpose of this study is investigation of effective parameters on dam breach outflow hydrograph due to piping. BREACH GUI is used for modeling of dam breach failure. The results describe parameters which are effective on dam breach outflow hydrographs. These parameters are average grain size diameter (D50) of outer material, porosity of inner and outer material, upstream slope, and downstream slope of the surface and core.<\div>

۲Prediction of Water Quality of Ajichay River using developed Artificial Neural Network and Supporting Vector Machine Models
اطلاعات انتشار: سومین کنفرانس بین المللی علوم و مهندسی، سال
تعداد صفحات: ۱۱
International efforts have been launched to save the endangered Urmia Lake as one of the largest natural lake worldwide. Ajichay River located in East Azarbaijan province, Iran, is one of the main rivers discharging into this lake and, thus, its water quality can directly affect the Urmia Lake ecosystem and life. In this research, we develop and propose two new numerical packages on the basis of Artificial Neural Network (ANN) and Supporting Vector Machine (SVM) models to estimate the monthly Total Dissolved Solid (TDS) of Ajichay’s water. For the ANN calibration, the feed forward back prop (FFB) model is used to obtain a set of coefficients for a linear model, and the radial basic function (RBF) kernel was used for the SVM model. The input data sets of both ANN and SVM models consist of six water quality parameters: TDS, Mg, Na, Ca, Cl, and SO4 collected monthly over a period of 30 years at Vanyar station situated on the banks of Ajichay River. Both models can successfully predict the variability of water’s TDS, but the ANN model with R2=0.958 and RMSE=0.0043 has a more efficient and accurate estimation compared to the SVM model with R2= 0.84 and RMSE = 0.009.<\div>
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