Hydrogen diffusion coefficients of different regions in the welded joint of X80 pipeline steel were measured using the electro-chemical permeation technique. Using ABAQUS software, hydrogen diffusion in X80 pipeline s...Hydrogen diffusion coefficients of different regions in the welded joint of X80 pipeline steel were measured using the electro-chemical permeation technique. Using ABAQUS software, hydrogen diffusion in X80 pipeline steel welded joint was studied in consideration of the inhomogeneity of the welding zone, and temperature-dependent thermo-physical and mechanical properties of the metals. A three dimensional finite element model was developed and a coupled thermo-mechanical-diffusion analysis was performed. Hydrogen concentration distribution across the welded joint was obtained. It is found that the postweld residual hydrogen exhibits a non-uniform distribution across the welded joint. A maximum equivalent stress occurs in the immediate vicinity of the weld metal. The heat affected zone has the highest hydrogen concentration level, followed by the weld zone and the base metal.Simulation results are well consistent with theoretical analysis.展开更多
The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The ...The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.展开更多
基金Project(BK2011258)supported by the Natural Science Foundation of Jiangsu Province,China
文摘Hydrogen diffusion coefficients of different regions in the welded joint of X80 pipeline steel were measured using the electro-chemical permeation technique. Using ABAQUS software, hydrogen diffusion in X80 pipeline steel welded joint was studied in consideration of the inhomogeneity of the welding zone, and temperature-dependent thermo-physical and mechanical properties of the metals. A three dimensional finite element model was developed and a coupled thermo-mechanical-diffusion analysis was performed. Hydrogen concentration distribution across the welded joint was obtained. It is found that the postweld residual hydrogen exhibits a non-uniform distribution across the welded joint. A maximum equivalent stress occurs in the immediate vicinity of the weld metal. The heat affected zone has the highest hydrogen concentration level, followed by the weld zone and the base metal.Simulation results are well consistent with theoretical analysis.
基金The Natural Science Foundation of Jiangsu Province,China(No.BK20200470)China Postdoctoral Science Foundation(No.2021M691595)Innovation and Entrepreneurship Plan Talent Program of Jiangsu Province(No.AD99002).
文摘The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.