فهرست مطالب hassan khademi zadeh

In this day and age, the ultra-fine materials due to their unique properties have found a special place in various industries. By reducing the grain size, the share of atoms at the grain boundaries has been increased and the increase of grain boundaries prevents the movement of dislocations and increases the strength. One method of producing ultra-fine materials is imposing severe plastic deformation. In order to apply Plastic deformation, disparate methods can be used that parallel angled channels are used in this study. ABAQUS finite element software is used to analyze the process numerically and to optimize the results, neural network and genetic algorithm methods have been used. In this study, the effects of die parameters including channel angle, tube length, increase of diameter difference and the friction coefficient are checked out. The results depicted that the coefficient of friction and pipe length which are tested, played a pivotal role in the homogenization of strain distribution separately; that by increasing the supposed friction coefficient and reducing the length of the tube, the strain distribution will be homogeneous. The difference between the increase in the diameter of pipe and the angle of die’s channel will have little impact on the improved uniformity of strain distribution. On the other hand, increasing the coefficient of friction, pipe length and diameter of pipe ends with an increase in the force of process while increasing the angle of die’s channel culminated in reducing the formation force. Additionally, considering the results obtained from optimization of parameters,

One of reasons that researchers in recent years have tried to produce ultrafine grained materials is producing lightweight components with high strength and reliability. There are disparate methods for production of ultra-fine grain materials,one of which is severe plastic deformation method. Severe plastic deformation method comprises different processes, one of which is Parallel tubular channel angular pressing. The aim of this study is optimizing parameters of the noticed process die just by utilizing neural network and genetic algorithm methods that at first for this purpose, by using ABAQUS finite element software, the numerical analysis of the die parameters is performed and the impact of each die parameter on the force of the process and the equivalent strain is examined. Finally, for gaining optimal parameters, MATLAB and neural network optimization methods and genetic algorithm are used. The use of neural network and genetic algorithm illustrated that to achieve the ideal possible situation in order to achieve a flawless super-fine tube, it is imperative to use the friction coefficient of 0.05, tube length of 40 mm, channel angle of 140 degrees and diameter increase difference of 1.5 mm. With such values, strain fluctuations reach 0.23, lowest value, and also the force reaches 0.49 KN and the amount of applied strain reaches its highest value to 2.37.