In order to maintain the structural consistency during the welding of precipitation hardened copperchromium-zirconium(PH-CuCrZr)alloy components,electron beam welding(EBW)process was employed.Experimental study and nu...In order to maintain the structural consistency during the welding of precipitation hardened copperchromium-zirconium(PH-CuCrZr)alloy components,electron beam welding(EBW)process was employed.Experimental study and numerical modeling of EBW process during welding of PH-CuCrZr alloy components were carried out.A 3D finite element model was developed to predict the output responses(bead penetration and bead width)as a function of EBW input parameters(beam current,acceleration voltage and weld speed).A combined circular and conical source with Gaussian heat distribution was used to model the deep penetration characteristic of the EBW process.Numerical modeling was carried out by developing user defined function in Ansys software.Numerical predictions were compared with the experimental results which had a good agreement with each other.The developed model can be used for parametric study in wide range of problems involving complex geometries which are to be welded using EBW process.The present work illustrates that the input current with a contribution of 44.56%and 81.13%is the most significant input parameter for the bead penetration and bead width,respectively.展开更多
This paper is to represent new algorithms to predict process parameters on top-bead width in robotic gas metal arc（GMA） welding process.The models have been developed：linear, curvilinear and intelligent model based...This paper is to represent new algorithms to predict process parameters on top-bead width in robotic gas metal arc（GMA） welding process.The models have been developed：linear, curvilinear and intelligent model based on full factorial design with two replications.Regression analysis was employed for optimization of the coefficients of linear and curvilinear models, while genetic algorithm（GA） was utilized to estimate the coefficients of an intelligent model.Not only the fitting of these models were checked and compared by using a variance test（ANOVA）, but also the prediction on top-bead width using the developed models were carried out based on the additional experiments.The developed models were employed to investigate the characteristic between process parameters and top-bead width.Resulting solutions and graphical representation showed that the intelligent model developed can be employed for prediction of bead geometry in GMA welding process.展开更多
文摘In order to maintain the structural consistency during the welding of precipitation hardened copperchromium-zirconium(PH-CuCrZr)alloy components,electron beam welding(EBW)process was employed.Experimental study and numerical modeling of EBW process during welding of PH-CuCrZr alloy components were carried out.A 3D finite element model was developed to predict the output responses(bead penetration and bead width)as a function of EBW input parameters(beam current,acceleration voltage and weld speed).A combined circular and conical source with Gaussian heat distribution was used to model the deep penetration characteristic of the EBW process.Numerical modeling was carried out by developing user defined function in Ansys software.Numerical predictions were compared with the experimental results which had a good agreement with each other.The developed model can be used for parametric study in wide range of problems involving complex geometries which are to be welded using EBW process.The present work illustrates that the input current with a contribution of 44.56%and 81.13%is the most significant input parameter for the bead penetration and bead width,respectively.
基金supported by the 2006 research funds from Mokpo National University
文摘This paper is to represent new algorithms to predict process parameters on top-bead width in robotic gas metal arc（GMA） welding process.The models have been developed：linear, curvilinear and intelligent model based on full factorial design with two replications.Regression analysis was employed for optimization of the coefficients of linear and curvilinear models, while genetic algorithm（GA） was utilized to estimate the coefficients of an intelligent model.Not only the fitting of these models were checked and compared by using a variance test（ANOVA）, but also the prediction on top-bead width using the developed models were carried out based on the additional experiments.The developed models were employed to investigate the characteristic between process parameters and top-bead width.Resulting solutions and graphical representation showed that the intelligent model developed can be employed for prediction of bead geometry in GMA welding process.
