Occurrence of laminar separation bubbles on solid walls of an elliptic cylinder has been simulated using a recently developed transitional model for boundary layer flows. Computational method is based on the solution of the Reynolds averaged Navier-Stokes (RANS) equations and the eddy-viscosity concept. Transitional model tries to simulate streamwise fluctuations, induced by freestream turbulen...

In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...

In this paper, a mathematical model is developed to calculate the conversion and the residence time reaction for plug flow and mixed flow in the reactors filled with cylin-drical particles using the shrinking core model. In this modeling, the size of the particles is un-chamged during the reaction. Also, the reaction rate is controlled by the gas layer resistance, the ash layer resistance, and ...

The adsorption ability of activated carbon, chitosan, and chitosan/activated carbon composite for cadmium separation from aqueous solution was analyzed via statistical physical modeling. The equilibrium data were analyzed by Langmuir, Hill, double layer model, and the multi-layer model with saturation isotherm models. Results showed that the multi-layer model with saturation could well describe...

In this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. In proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. In comparison with existing similar neural networks proposed model provides solutions with high accuracy. Numerica...

in this study, a three–layer artificial neural network (ann) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. a total of 455 data points were collected from 13 data sources to develop the ann model. superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of t...

evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...