In this research, experimental and numerical modelling of three-phase air, water, and sediment tr... more In this research, experimental and numerical modelling of three-phase air, water, and sediment transport flow, due to the opening of a sluice gate was conducted in two scenarios, i.e., with and without a triangular obstacle. Numerical simulation was conducted using the Navier-Stokes equations with the aid of the volume of fluid method (VOF) to track the free surface of the fluid. For the experimental model, a glass-enclosed flume with 150 × 30 × 50 cm dimensions was used. The experiment was performed for an initial height of the water column at 20 cm and 10 cm sediment column. To evaluate the numerical model’s performance, the simulation results were compared with the experimental observations using the average relative error %. The amount of relative error between experimental observations and numerical simulations, for the position and height of the wave flow for the three-phase air, water, and sediment flow, were obtained as 2.64% and 4.51% for the position and height of the wat...
IOP Conference Series: Earth and Environmental Science
This study evaluates the performance of an integrated version of artificial neural network namely... more This study evaluates the performance of an integrated version of artificial neural network namely HS-ANN (which is a combination of neural network and heuristic harmony search algorithm) as an alternative approach to predict the sediment transport in terms of sediment volumetric concentration (Cv) in sewer pipe systems. To overcome the complexities of choosing the optimum number of the input variables and to consider the effective parameters of the model, the factor analysis technique is utilized. In addition to the HS-ANN model, an empirical equation, as well as a multiple linear regression model, are also considered. The mean square error (RMSE), mean absolute percentage error (MAPE), and Pearson correlation coefficients (PCC) are used for evaluating the accuracy of the applied models. As the comparisons demonstrate, the HS-ANN model (PCC = 0.97) is more accurate than the existing empirical equation and MLR model and could be successfully employed in predicting sediment transport ...
The present study investigates the capability of two metaheuristic optimization approaches, namel... more The present study investigates the capability of two metaheuristic optimization approaches, namely the Butterfly Optimization Algorithm (BOA) and the Genetic Algorithm (GA), integrated with machine...
In this research, experimental and numerical modelling of three-phase air, water, and sediment tr... more In this research, experimental and numerical modelling of three-phase air, water, and sediment transport flow, due to the opening of a sluice gate was conducted in two scenarios, i.e., with and without a triangular obstacle. Numerical simulation was conducted using the Navier-Stokes equations with the aid of the volume of fluid method (VOF) to track the free surface of the fluid. For the experimental model, a glass-enclosed flume with 150 × 30 × 50 cm dimensions was used. The experiment was performed for an initial height of the water column at 20 cm and 10 cm sediment column. To evaluate the numerical model’s performance, the simulation results were compared with the experimental observations using the average relative error %. The amount of relative error between experimental observations and numerical simulations, for the position and height of the wave flow for the three-phase air, water, and sediment flow, were obtained as 2.64% and 4.51% for the position and height of the wat...
IOP Conference Series: Earth and Environmental Science
This study evaluates the performance of an integrated version of artificial neural network namely... more This study evaluates the performance of an integrated version of artificial neural network namely HS-ANN (which is a combination of neural network and heuristic harmony search algorithm) as an alternative approach to predict the sediment transport in terms of sediment volumetric concentration (Cv) in sewer pipe systems. To overcome the complexities of choosing the optimum number of the input variables and to consider the effective parameters of the model, the factor analysis technique is utilized. In addition to the HS-ANN model, an empirical equation, as well as a multiple linear regression model, are also considered. The mean square error (RMSE), mean absolute percentage error (MAPE), and Pearson correlation coefficients (PCC) are used for evaluating the accuracy of the applied models. As the comparisons demonstrate, the HS-ANN model (PCC = 0.97) is more accurate than the existing empirical equation and MLR model and could be successfully employed in predicting sediment transport ...
The present study investigates the capability of two metaheuristic optimization approaches, namel... more The present study investigates the capability of two metaheuristic optimization approaches, namely the Butterfly Optimization Algorithm (BOA) and the Genetic Algorithm (GA), integrated with machine...
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Papers by Marzieh Fadaee