مجله هیدرولیک
سال دوم شماره 1 (بهار 1386)

The simulation and application of models is supposed to be a suitable technique in proper recognition of channel hydraulic characteristics which may lead to increasing accuracy in prediction and saving investments. The present study was therefore conducted to study the relationship of important channel hydraulic characteristics with morphometric properties of bed sediment in Vaz River to find out the most important hydraulic factors controlling the morphometric characteristics of bed sediment. In this study, 12 sections were selected along the river and the bed sediments were sampled using mixing method. The channel hydraulic characteristics and bed sediment morphometric parameters were then regressed. The results of the study verified the significant relationship between hydraulic characteristics and morphometric parameters. Besides, the flow discharge and channel slope were also determined as the most and least effective factors controlling the morphometric characteristics of bed sediment.

The effect of a submerged normal flat plate on the trap efficiency and sedimentation length of a settling basin was experimentally investigated in this study and compared with the results of a numerical model. The implemented numerical model is an Eulerian-Lagrangian model that solves The Reynolds-Averaged Navier-Stokes equations with k¾e turbulence model for the continuous phase and sediment particles are tracked with a lagrangian method. The results indicate that, when the linear transition transmits the flow with high momentum from the upstream canal into the basin with no extra turbulence and a parallel 2D flow is established in the basin, the baffle has no positive effect on the trap efficiency and the sedimentation length.However, in 3D conditions in which the incoming jet travels a considerable distance and causes large variations of transverse velocity in the basin, installing the baffle in a relative submergence of 15% can increase the trap efficiency of the settling basin by up to 8.5%. This may be attributed to the role of the baffle in decaying the kinetic energy of the impinging jet and spreading the sediment particles in the width of the settling basin.

Real time updating is inevitable in flood forecasting systems due to uncertainty in hydrologic models and input data. In these systems, hydrological parameters are usually updated based on online recorded discharge in a telemetry system. Conventional methods-such as state space models have widely been used in real time updating of hydrological parameters in the context of flood forecasting systems. In this paper, however, we proposed a Monte Carlo (MC) based model in updating of flood forecasts. Generalized likelihood uncertainty estimation which is combination of MC and Bayesian theory, is applied to update rainfall runoff (RR) model parameters based on real time data. In this methodology, a large set of hydrological parameters is produced by random generation and then probability distribution of forecast is computed based on the results of RR simulation for the set of parameters. In real time updating of RR parameters, prior and posterior likelihoods are computed using forecast errors that are obtained from the results of behavioral models and real time recorded discharges. Then, prior and posterior likelihoods are applied to modify forecast confidence limits in each time step. In the updating process, probability distribution of peak discharge becomes stable prior to the time to peak and lead time of forecast is determined based on the stable time and real time to peak. The applied approach shows more flexibility in varying the parameters and modifying forecast limits in comparison with other conventional updating methods.

Hydrodynamic forces generated from waves and currents on slender cylinders are of great concern in designing offshore structures. Numerous analytical and experimental methods such as the Morison equation have been suggested to estimate the wave forces on slender structures. However, such methods have shown some inaccuracy in their estimations. In recent years, artificial neural networks have received a great deal of attention and have been used effectively in many of engineering subjects. In this paper, artificial neural networks have been used to predict waves and current forces on slender cylinders. The data generated from laboratory experiments were used to train and evaluate the prediction performance of the artificial neural networks used in this paper. A number of neural networks were designed, trained and evaluated. Results indicated the success of application of neural networks approach which can efficiently predict the waves and current forces on slender cylinders after conducting appropriate training. Furthermore, the results are quite acceptable in comparison with test results and better than the results obtained from other methods such as the Morison equation.

Sharp-Crested weirs as measuring devices are widely used in hydraulic laboratories. They are also useful as water surface or flow controlling structures at many irrigation networks. In this paper, an attempt was made to simulate flow over rectangular and triangular sharp-crested weirs with flow under slide gates. Based on the continuity equation, an empirical equation for the coefficient of contraction, and also discharge coefficient of the rectangular slide gates, flow discharge over rectangular and triangular sharp-crested weirs are proposed. A comparison was made between the proposed theory and few experiments conducted at Isfahan University of Technology. The proposed empirical equation was also compared with those of other researchers. The results showed that the proposed method could predict flow discharge over the weirs with high accuracy.