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Y J Chao - One of the best experts on this subject based on the ideXlab platform.
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Determination of global mechanical response of friction stir Welded Plates using local constitutive properties
Modelling and Simulation in Materials Science and Engineering, 2004Co-Authors: S Liu, Y J ChaoAbstract:Global mechanical behaviour, i.e. the true stress–strain curves, yield strength σs, hardening exponents n, and strength coefficients K, of friction stir Welded Plates, in which the weld line lies either perpendicular or parallel to the axis of the applied tensile force, is determined by using the local constitutive properties of the base metal, heat affected zone and weld nugget. The principle of 'rule of mixtures' is adopted to develop the analytical models. Experimental data from Lockwood (2000 PhD Dissertation Department of Mechanical Engineering, University of South Carolina) for Al 2024-T351 specimens under tension in the transverse direction are compared with the analytical results. The effect of the size of different welding zones on the global mechanical response of the Welded Plate is also assessed. The 'rule of mixtures' method is shown to be reasonably accurate in determining the global mechanical response of the Welded Plate.
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numerical simulation of transient temperature and residual stresses in friction stir welding of 304l stainless steel
Journal of Materials Processing Technology, 2004Co-Authors: X K Zhu, Y J ChaoAbstract:Abstract Three-dimensional nonlinear thermal and thermo-mechanical numerical simulations are conducted for the friction stir welding (FSW) of 304L stainless steel. The finite element analysis code—WELDSIM, developed by the authors specifically for welding simulation, was used. Two welding cases with tool rotational speeds of 300 and 500 rpm are analyzed. The objective is to study the variation of transient temperature and residual stress in a friction stir Welded Plate of 304L stainless steel. Based on the experimental records of transient temperature at several specific locations during the friction stir welding process for the 304L stainless steel, an inverse analysis method for thermal numerical simulation is developed. After the transient temperature field is determined, the residual stresses in the Welded Plate are then calculated using a three-dimensional elastic–plastic thermo-mechanical simulation. The effect of fixture release after the welding on the residual stresses is also studied. Comparison with the residual stress fields measured by the neutron diffraction technique shows that the results from the present numerical simulation have good agreement with the test data.
Arun Kumar Samantaray - One of the best experts on this subject based on the ideXlab platform.
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Determination of Optimal Pulse Metal Inert Gas Welding Parameters with a Neuro-GA Technique
Materials and Manufacturing Processes, 2010Co-Authors: Sukhomay Pal, Surjya K. Pal, Arun Kumar SamantarayAbstract:Optimization of a manufacturing process is a rigorous task because it has to take into account all the factors that influence the product quality and productivity. Welding is a multi-variable process, which is influenced by a lot of process uncertainties. Therefore, the optimization of welding process parameters is considerably complex. Advancement in computational methods, evolutionary algorithms, and multiobjective optimization methods create ever-more effective solutions to this problem. This work concerns the selection of optimal parameters setting of pulsed metal inert gas welding (PMIGW) process for any desired output parameters setting. Six process parameters, namely pulse voltage, background voltage, pulse frequency, pulse duty factor, wire feed rate and table feed rate were used as input variables, and the strength of the Welded Plate, weld bead geometry, transverse shrinkage, angular distortion and deposition efficiency were considered as the output variables. Artificial neural network (ANN) mod...
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artificial neural network modeling of weld joint strength prediction of a pulsed metal inert gas welding process using arc signals
Journal of Materials Processing Technology, 2008Co-Authors: Sukhomay Pal, Surjya K. Pal, Arun Kumar SamantarayAbstract:This paper addresses the weld joint strength monitoring in pulsed metal inert gas welding (PMIGW) process. Response surface methodology is applied to perform welding experiments. A multilayer neural network model has been developed to predict the ultimate tensile stress (UTS) of Welded Plates. Six process parameters, namely pulse voltage, back-ground voltage, pulse duration, pulse frequency, wire feed rate and the welding speed, and the two measurements, namely root mean square (RMS) values of welding current and voltage, are used as input variables of the model and the UTS of the Welded Plate is considered as the output variable. Furthermore, output obtained through multiple regression analysis is used to compare with the developed artificial neural network (ANN) model output. It was found that the welding strength predicted by the developed ANN model is better than that based on multiple regression analysis.
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Sensor based weld bead geometry prediction in pulsed metal inert gas welding process through artificial neural networks
International Journal of Knowledge-based and Intelligent Engineering Systems, 2008Co-Authors: Sukhomay Pal, Surjya K. Pal, Arun Kumar SamantarayAbstract:Weld quality is primarily determined from the weld bead geometry. This work concerns the weld bead geometry prediction in pulsed metal inert gas welding (PMIGW) process. A back propagation neural network (BPNN) model, a radial basis function network (RBFN) model and regression model have been developed to predict the weld bead geometry of Welded Plates. Six process parameters, namely pulse voltage, back-ground voltage, pulse duty factor, pulse frequency, wire feed rate and the welding speed along with root mean square (RMS) values of two sensor signals, namely the welding current and the voltage signals, are used as input variables of the two models. The weld bead width, height and reinforcement of the Welded Plate are considered as the output variables. Having same process parameters does not always result in the same output quality. This is why, inclusion of sensor signals in the models, as developed in this work, results in better output prediction.
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Radial basis function neural network model based prediction of weld Plate distortion due to pulsed metal inert gas welding
Science and Technology of Welding and Joining, 2007Co-Authors: Surjya K. Pal, Sukhomay Pal, Arun Kumar SamantarayAbstract:AbstractWelding shrinkage and distortion affect the shape, dimensional accuracy and strength of the finished product. This work concerns the prediction of welding distortion in a pulsed metal inert gas welding (PMIGW) process. Six different types of radial basis function network (RBFN) models have been developed to predict the distortion of Welded Plates. Six process parameters, namely, pulse voltage, background voltage, pulse duty factor, pulse frequency, wire feed rate and the welding speed, along with the root mean square (RMS) values of two sensor signals, namely, the welding current and the voltage signals, are used as input variables of these models. The angular distortion and the transverse shrinkage of the Welded Plate are considered as the output variables. Inclusion of sensor signals in the models, as developed in this work, results in better output prediction.
Zhang Kai - One of the best experts on this subject based on the ideXlab platform.
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Study on superplastic bulging capabilities of Ti-6Al-4V plasma arc welding butt Welded Plate
Materials Science and Technology, 2003Co-Authors: Zhang KaiAbstract:The Superplastic bulging capabilities of a plasma arc welding (PAW) butt-Welded Plate was studied using simple bulging tests. The experimental results indicate that the PAW butt-Welded Plate possesses good superplastic bulging capability that the maximum bulge height can exceed the radius of the female die. During bulging the acicular martensite microstructure of weld metal transformed into spherical α+streak α microstructure. The bulging gas pressure has an optimum value under the same conditions.An actual superplastic bulge example was given for the application of PAW butt-Welded Plate.
Sukhomay Pal - One of the best experts on this subject based on the ideXlab platform.
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Determination of Optimal Pulse Metal Inert Gas Welding Parameters with a Neuro-GA Technique
Materials and Manufacturing Processes, 2010Co-Authors: Sukhomay Pal, Surjya K. Pal, Arun Kumar SamantarayAbstract:Optimization of a manufacturing process is a rigorous task because it has to take into account all the factors that influence the product quality and productivity. Welding is a multi-variable process, which is influenced by a lot of process uncertainties. Therefore, the optimization of welding process parameters is considerably complex. Advancement in computational methods, evolutionary algorithms, and multiobjective optimization methods create ever-more effective solutions to this problem. This work concerns the selection of optimal parameters setting of pulsed metal inert gas welding (PMIGW) process for any desired output parameters setting. Six process parameters, namely pulse voltage, background voltage, pulse frequency, pulse duty factor, wire feed rate and table feed rate were used as input variables, and the strength of the Welded Plate, weld bead geometry, transverse shrinkage, angular distortion and deposition efficiency were considered as the output variables. Artificial neural network (ANN) mod...
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artificial neural network modeling of weld joint strength prediction of a pulsed metal inert gas welding process using arc signals
Journal of Materials Processing Technology, 2008Co-Authors: Sukhomay Pal, Surjya K. Pal, Arun Kumar SamantarayAbstract:This paper addresses the weld joint strength monitoring in pulsed metal inert gas welding (PMIGW) process. Response surface methodology is applied to perform welding experiments. A multilayer neural network model has been developed to predict the ultimate tensile stress (UTS) of Welded Plates. Six process parameters, namely pulse voltage, back-ground voltage, pulse duration, pulse frequency, wire feed rate and the welding speed, and the two measurements, namely root mean square (RMS) values of welding current and voltage, are used as input variables of the model and the UTS of the Welded Plate is considered as the output variable. Furthermore, output obtained through multiple regression analysis is used to compare with the developed artificial neural network (ANN) model output. It was found that the welding strength predicted by the developed ANN model is better than that based on multiple regression analysis.
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Sensor based weld bead geometry prediction in pulsed metal inert gas welding process through artificial neural networks
International Journal of Knowledge-based and Intelligent Engineering Systems, 2008Co-Authors: Sukhomay Pal, Surjya K. Pal, Arun Kumar SamantarayAbstract:Weld quality is primarily determined from the weld bead geometry. This work concerns the weld bead geometry prediction in pulsed metal inert gas welding (PMIGW) process. A back propagation neural network (BPNN) model, a radial basis function network (RBFN) model and regression model have been developed to predict the weld bead geometry of Welded Plates. Six process parameters, namely pulse voltage, back-ground voltage, pulse duty factor, pulse frequency, wire feed rate and the welding speed along with root mean square (RMS) values of two sensor signals, namely the welding current and the voltage signals, are used as input variables of the two models. The weld bead width, height and reinforcement of the Welded Plate are considered as the output variables. Having same process parameters does not always result in the same output quality. This is why, inclusion of sensor signals in the models, as developed in this work, results in better output prediction.
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Radial basis function neural network model based prediction of weld Plate distortion due to pulsed metal inert gas welding
Science and Technology of Welding and Joining, 2007Co-Authors: Surjya K. Pal, Sukhomay Pal, Arun Kumar SamantarayAbstract:AbstractWelding shrinkage and distortion affect the shape, dimensional accuracy and strength of the finished product. This work concerns the prediction of welding distortion in a pulsed metal inert gas welding (PMIGW) process. Six different types of radial basis function network (RBFN) models have been developed to predict the distortion of Welded Plates. Six process parameters, namely, pulse voltage, background voltage, pulse duty factor, pulse frequency, wire feed rate and the welding speed, along with the root mean square (RMS) values of two sensor signals, namely, the welding current and the voltage signals, are used as input variables of these models. The angular distortion and the transverse shrinkage of the Welded Plate are considered as the output variables. Inclusion of sensor signals in the models, as developed in this work, results in better output prediction.
Jung Min Sohn - One of the best experts on this subject based on the ideXlab platform.
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Effects of Welding Residual Stresses on High Tensile Steel Plate Ultimate Strength: Nonlinear Finite Element Method Investigations
Journal of Offshore Mechanics and Arctic Engineering-transactions of The Asme, 2011Co-Authors: Jeom Kee Paik, Jung Min SohnAbstract:The primary objective of the present paper is to examine the effects of welding residual stresses on ultimate strength of high tensile steel Plates under axial compression in terms of their magnitude and pattern. The ANSYS nonlinear finite element method is employed for the purpose. The secondary objective of the present paper is to study a nonlinear finite element method modeling technique for Welded Plate structures with residual stresses. Three levels of residual stresses, namely slight, average, and severe, are considered. As another important parameter of influence on the Plate ultimate strength, the Plate thickness is also varied in the numerical computations to examine their role and trend. Important insights and conclusions developed from the present study are documented.
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Effects of Welding Residual Stresses on High Tensile Steel Plate Ultimate Strength: Nonlinear Finite Element Method Investigations
Volume 2: Structures Safety and Reliability, 2009Co-Authors: Jeom Kee Paik, Jung Min SohnAbstract:The primary objective of the present paper is to examine the effects of welding residual stresses on ultimate strength of high tensile steel Plates under axial compression in terms of their magnitude and pattern. The ANSYS nonlinear finite element method is employed for the purpose. The secondary objective of the present paper is to study a nonlinear finite element method modeling technique for Welded Plate structures with residual stresses. Three levels of residual stresses, namely slight, average and severe levels are considered. As another important parameter of influence on the Plate ultimate strength, the Plate thickness is also varied in the numerical computations to examine their role and trend. Important insights and conclusions developed from the present study are documented.Copyright © 2009 by ASME
