Mathematical model of fast hydraulic actuator dynamics, based on Riemann's equations, is presented in the paper. Fast hydraulic actuator can be assumed as two serially connected compressible fluid flows controlled by supply and return variable flow restrictors enclosed in control servo-valve and separated by actuator piston. Exhibited dynamic model includes several physical effects, such as: fluid viscosity and compressibility, compression and expansion, wave propagation, actuator equivalent inertia, potential external load and arbitrary servo-valve control input. Solution of the presented mathematical model is evaluated by using the method of characteristics. Corresponding boundary conditions assume the actuator piston position as a movable boundary between the direct and the reverse part of the actuator chamber.

A mathematical model has been developed and simulated to describe contaminated soil bioremediation. The model equations consist of a system of three nonlinear partial differential equations. Dimensional analysis of the model equations has been performed, and solution of these equations has been conducted by an implicit finite difference method. A Computer program is runed for solving the model equations and by using this program, the influence of the principal parameters (porosity, soil aggregate radius, and partition coefficient of the substrate) on the fate of chemicals has been studied. The rates of substrate, oxygen diffusion and biodegradation rate have been found to be the controlling mechanisms for remediation in the aggregates.

Introduction: Hospital Emergency Departments (ED) face different problems affecting their performance. Deficiency of inpatient beds, inability to access suitable care, noisy and overcrowded places, etc. lead to prolonged waiting time, increased length of stay and low service quality.The main purpose of this study was to improve patient flow processes in emergency departments.Method: The population of this descriptive- applied study included unlimited number of patients who referred to the ED of the selected hospital. Colored Petri Net was used to model patient flow processes and CPN Tools software was employed to simulate and investigate different improvement scenarios. Input data for the simulation model were obtained through timing during data collection period. Patients’ waiting time, length of stay, and resource utilization were defined as performance measures. Four improving scenarios (B, C, D, and E) were defined and their effects were investigated to improve processes.Results: According to simulation outputs, scenario B led to 45% decrease in waiting time for the specialists while the other scenarios had no positive (decreasing) impact on waiting time. Scenario E was the most effective one in decreasing the length of stay for patients at different ESI levels.Scenarios E and D had positive effect on resource utilization.Conclusions: Selection of the best scenario depends on the mission of ED, i.e. to save patients’ life. Therefore, a scenario which is the most effective one in saving life must be chosen even if it is expensive. Although it is expensive, scenario E is preferred to scenario D due to its improved outcome. Scenario D is the second best scenario, compared to the other two scenarios, because it is less expensive.

Today, computational acoustics is one of major branch of underwater acoustics that play important role in the advanced laboratories in the world. It is important due to high financial cost of operational tests in the water. There exist many numerical methods in this field that among them only, ray tracing, normal modes, fast field programming and parabolic equation method have gained more attention. PE method is a suitable method in low frequencies and shallow water as well as valid for all environments. In this paper, Numerical implementation of PE method based on c++ and MATLAB routines is given over some of well known standard test problems. In the implementation, according to both mathematically and physically complexities of problem, we chose general manner for some of important parameters such as depth and frequency of source, range of receiver, and the whole depth of simulation. Some results show that we have surface and bottom reflections from 4500 meters in range. TL error has a value about 18.4 percent. As increasing source strength from 200 dB, we can eliminate noise effects. TL in stations 1 to 4 in Caspian sea is shown as well as ray simulation in graphs 2, 6, 8, 10.

In recent years, flexible manufacturing system as a response to market demands has been proposed to increase product diversity, optimum utilization of machines andperiods of short-term products. The development of Computer systems has provided the ability to build machines with high functionality and the necessary flexibility to perform various operations. However, due to the complexity and the random nature of these problems, deterministic algorithms are not highly accurate andefficient enough. In this paper, Computer simulation models are used to optimize flexible manufacturing system FMS). The objectives of this paper are included: the optimal time served in each unit, the optimal number of servers in each unit, and the optimum number of domestic transportation fleet based on type. At the first step, source-destination traffic matrix is presented for development, including: service time and traffic volume are used. The computational results show the accuracy and efficiency of using simulation tools in these problems.

In this study, a mathematical model based on principles of heat and mass transfer taking place during the drying process has been developed. Element material and energy balance equations are solved simultaneously using the modified Euler method with time step variation. In order to consider evaporation rate reduction after the critical moisture content, a î factor is defined which could be evaluated from drying curve. The developed model is then used as a base to build a simulation program. The program is eventually used to predict the performance of a dryer for baby food compared with real plant measurements. Relatively good compatibility is observed to exist between the predicted and measured data. Errors observed between the calculated results and real plant data are about 10.32% for drying time and 15.40 % for final moisture content. The simulator also used to study the behavior of a dryer for qualitative analysis and the influence of different parameters on drying time and product quality.