In the presented study, the laser butt-welding of Ti 6Al 4V is investigated using 2.2 kw CO2 laser. Ti 6Al 4V alloy has widespread application in various fields of industries including the medical, nuclear and aerospa...In the presented study, the laser butt-welding of Ti 6Al 4V is investigated using 2.2 kw CO2 laser. Ti 6Al 4V alloy has widespread application in various fields of industries including the medical, nuclear and aerospace. In this study, Response Surface Methodology (RSM) is employed to establish the design of experiments and to optimize the bead geometry. The relationships between the input laser-welding parameters (i.e. laser power, welding speed and focal point position) and the process responses (i.e. welded zone width, heat affected zone width, welded zone area, heat affected zone area and penetration depth) are investigated. The multi-response optimizations are used to optimize the welding process. The optimum welding conditions are identified in order to increase the productivity and minimize the total operating cost. The validation results demonstrate that the developed models are accurate with low percentages of error (less than 12.5%).展开更多
The aim of this study is to develop processing maps based on two models and compare them with conventional processing maps.The hyperbolic sinus constitutive equation and artificial neural network(ANN)approaches were u...The aim of this study is to develop processing maps based on two models and compare them with conventional processing maps.The hyperbolic sinus constitutive equation and artificial neural network(ANN)approaches were used in this investigation to predict flow stress and to develop processing maps in various conditions.The hot compression tests of InX-750 superalloy were carried out above the gamma prime phase temperature and within the temperature range of 1000-1150℃and strain rate of 0.001-1.000 s^(-1).The processing maps were conducted based upon dynamic material model(DMM)for data by experimental,constitutive equation and ANN approaches.The processing maps drawn by either of the prediction methods show that the method developed by ANN data does not significantly differ from the experimental processing map.The ANN approach is thus a suitable way to predict the flow stress as well as hot working processing map of engineering metals and materials.展开更多
文摘In the presented study, the laser butt-welding of Ti 6Al 4V is investigated using 2.2 kw CO2 laser. Ti 6Al 4V alloy has widespread application in various fields of industries including the medical, nuclear and aerospace. In this study, Response Surface Methodology (RSM) is employed to establish the design of experiments and to optimize the bead geometry. The relationships between the input laser-welding parameters (i.e. laser power, welding speed and focal point position) and the process responses (i.e. welded zone width, heat affected zone width, welded zone area, heat affected zone area and penetration depth) are investigated. The multi-response optimizations are used to optimize the welding process. The optimum welding conditions are identified in order to increase the productivity and minimize the total operating cost. The validation results demonstrate that the developed models are accurate with low percentages of error (less than 12.5%).
基金the support by the Faculty of Engineering,Hakim Sabzevari University,Sabzevar,Iran。
文摘The aim of this study is to develop processing maps based on two models and compare them with conventional processing maps.The hyperbolic sinus constitutive equation and artificial neural network(ANN)approaches were used in this investigation to predict flow stress and to develop processing maps in various conditions.The hot compression tests of InX-750 superalloy were carried out above the gamma prime phase temperature and within the temperature range of 1000-1150℃and strain rate of 0.001-1.000 s^(-1).The processing maps were conducted based upon dynamic material model(DMM)for data by experimental,constitutive equation and ANN approaches.The processing maps drawn by either of the prediction methods show that the method developed by ANN data does not significantly differ from the experimental processing map.The ANN approach is thus a suitable way to predict the flow stress as well as hot working processing map of engineering metals and materials.
