River water quality is a significant concern in many countries, considering agricultural and drinking consumptions. Therefore, prediction of salinity index, as the main water quality condition is a necessary tool for water resources planning and management. This paper describes the application of artificial neural networks (ANNs) models for computing the total dissolved solids (TDS) level in Jajrood River (Iran). Two ANN networks, multi-layer perceptron (MLP) and radial basis function (RBF), were identified, validated and tested for the computation of TDS concentrations. Both networks employed five input water quality variables measured in river water over a period of 40 years. The performance of the ANN models was checked through the coefficient of determination (R 2 ) and root mean square error (RMSE). Jajrood River is one of the most important rivers which is located adjacent to Tehran city and supplies drinking water for people who live in this mega-city and recreational uses. Tehran is the most populous city and largest industrial pole in Iran, which caused the river, to be exposed to various pollutants. Matlab 2007 was selected for modeling goals in this research. Results show that MLP and RBF modeling as two methods of ANN are able to simulate water quality variables of Jajrood River with more than 90% accuracy. After modeling in MLP and RBF formatting and comparing simulation results (output) show that, the RBF result (R 2 of validation is 0.9362) are more closely to reality than the MLP (R 2 of validation is 0.8968). In other words, because of large number of input data, the RBF modeling performance has a better prediction than MLP modeling.
The piano key weir (PKW) is a developed type of labyrinth spillway with the ability to transfer large amounts of discharge by keeping executive costs constant. In this study, the parameters affecting the discharge coefficient of nine models were evaluated using physical models and simulations by Flow-3D software. The PKW models included: PK1.0, PK1.1, PK1.2, PK1.3, PK1.4, PK1.5, and PK1.6 representing the width ratios of the inlet (Wi) to outlet (Wo) keys of 1.0, 1.1, 1.2, 1.3, 1.4, 1.5 and 1.6 respectively and the other two models were PKT (PK1.1 with a thicker wall) and PKTP (PK1.1 with a thicker wall and an enhanced crown). According to the results of experimental and simulation evaluations, the model of PK1.4 was selected as the optimal model, which increased the discharge rate by 30% compared to the control weir. Moreover, increasing wall thickness (PKT model) led to an increase in the discharge and installing a parapet wall (PKTP model) resulted in an increase in discharge and a uniform distribution of flow lines on the weir. Considering the superiority of models PK1.4, PKT, and PKTP, the geometric properties of these models can be used to optimize the design of PKWs.
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