This research suggests a simplified equation to predict the shear strength of reinforced concrete beams without web reinforcements. The focus of study has been made to study of…
Abstract
This research suggests a simplified equation to predict the shear strength of reinforced concrete beams without web reinforcements. The focus of study has been made to study of the high strength concrete (HSC) beams (45MPa) with different shear span to depth ratios (a/d = 1, 2, 3 & 4) without web reinforcements and then, the results were compared with three shear models namely, ACI 318, Canadian standards, and Zsutty equation. The results obtained from data base revealed that the most suitable fit equation for modeling shear capacity in HSC beams without shear reinforcements was Zsutty formulae and finally, a simplified mathematical equation to predict the shear capacity was proposed.
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This study presented the model of predicting the water table fluctuation in flood plain of Sepidroud watershed (North of Iran-Gilan). The model for prediction of water table depth…
Abstract
This study presented the model of predicting the water table fluctuation in flood plain of Sepidroud watershed (North of Iran-Gilan). The model for prediction of water table depth was developed leaning on artificial neural network. The neural network with different numbers of hidden layer neurons was developed by using 4 years (2004-2007) monthly rainfall, potential evapotranspiration and influencing wells as input and water table depth as output. The best model was selected based on mean square error. The results showed that artificial neural network could be used to predict water table depth in aquifer with good convergence and maximum error was 5% approximately.