فصلنامه مدل سازی در مهندسی
پیاپی 35 (زمستان 1392)

Friction stir welding (FSW) is a process in the solid state in which heat is generated due to friction between welding tool and work piece. FSW has extensive effect on the microstructure، weld quality، and mechanical properties. The purpose of this investigation is to study and to predict the heat generated in Aluminum alloy plates welded by FSW method. A three dimensional model was developed by LS-Dyna software، using finite element method. An appropriate heating cycle has been proposed for aluminum 6061 alloy. The investigated parameters in this study were linear velocity and rotational velocity. Finally، results from numerical and experimental data was compared and verified.

In this article، has been studied implementation of fractional fuzzy PID controller on a DC motor. A fractional fuzzy PID controller is a conventional PID controller that includes two non-integer derivative and integral parameters (λ،µ) in addition to kp،ki،kd could be perform against uncertainties as fuzzy logic. Design strategy contains five parameters. This research uses from artificial bee colony and particle swarm optimization for designing of controller parameters. Artificial bee colony in designing proposed FFPID has improved system robustness considerably comparison with designed controller based on PSO and conventional PID.

A new model is proposed for production of fine particles of Nabutemon by rapid expansion of supercritical solutions (RESS). A mathematical model is used for prediction of particle size and particle size distribution of RESS produced particles. In this model the effect of various operating parameters such as pressure and temperature of extraction and temperature and pressure of expansion on the characteristics of products were studied. The calculation results showed good agreement between the calculation results and the experimental data for Nabutemon particles.

The continuous Petri net is a model in which the number of marks in the places are real numbers instead of integers. This kind of Petri Nets is useful for modeling of systems that have one flux variable. Thus، changes in variables such as electrical current، water flow، electrical power flow، etc can be modeled by continuous Petri nets. Petri nets with the elements in it are not responsive to modeling of systems that are based on two or more variables (Such as electronic circuit). In this paper a new method based on continuous Petri nets for modeling and analysis of electrical circuits is introduced. In this approach، the new types of arcs، called control arcs، which control the speed of Petri nets transition، are presented. By adding these arcs، the possibility of linear systems modeling is provided.

The general goal of this paper is to determine natural frequency of a plate by artificial neural network with various supporting conditions. One of the most famous training of neural network is back propagation algorithm. This algorithm is a systematic method for training multi-layer artificial neural network. Back propagation algorithm is based on gradient descant which means that it moves downward on the error declination and regulates the weights for the minimum error. In this research، the real frequency is calculated using ANSYS program and is defined as a goal function for neural network so that all outputs of the network can be compared to this function and the error can be calculated. Then using a set of inputs including dimensions or specifications of plate، a neural network is made. After the determination of algorithm and quantities of the network، the phases of training and testing of the results are carried out and the output of the network is created. It is concluded that the results show the performance of the neural network and that the time of frequency calculation is considerably reduced.

In this paper، a novel hybrid model based on neural network and Game Theory is proposed to support the analyzers in oil market. In this model، first the neural network is utilized to learn the oil prices associated with OPEC production level and USA imports level. Then the learned neural network is applied by a game model. Finally the Nash equilibrium points of the game present the optimum decision which can be decided by OPEC. In experimental studies، the proposed model is applied to determine the best decision at March 2012. According to the results، the model can be used for OPEC decision-making and oil prices prediction.

In this article the effects of gravity on the mixed convection of a microflow is studied numerically by using lattice Boltzmann method (LBM). To do this، the hydrodynamic boundary condition equations should also be modified. The cold fluid enters to the microchannel and leaves it after cooling its hot walls. Calculations are provided for a wide range of Knudsen number (Kn). The results are presented as the isotherms and streamlines، the values of slip velocity and temperature jump and the local and global profiles of velocity، temperature and Nusselt number. It is observed that LBM is able to simulate the mixed convection in a microchannel appropriately. It is claimed that the effects of buoyancy forces are important for Kn<0. 05 and should be considered and for Kn>0. 05 they can be ignored. Moreover، the buoyancy forces make a rotational cell in the microchannel flow which generates the negative slip velocity at Kn=0. 005.