THERMAL FIELD MODEL FOR LASER+GMAW-PHYBRID WELDING OF TCS STAINLESS STEEL BASED ON THE PREDICTED KEYHOLE SHAPE
ZHANG Zhuanzhuan, XU Guoxiang, WU Chuansong
1) Key Lab for Liquid--Solid Structure Evolution and Materials Processing (Ministry of Education), Shandong University, Jinan 250061
2) School of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003
Cite this article:
ZHANG Zhuanzhuan XU Guoxiang WU Chuansong . THERMAL FIELD MODEL FOR LASER+GMAW-PHYBRID WELDING OF TCS STAINLESS STEEL BASED ON THE PREDICTED KEYHOLE SHAPE. Acta Metall Sin, 2011, 47(11): 1450-1458.
Abstract In order to describe the distribution characteristics of laser energy inside the keyhole reasonably, the ray tracing method is used to deal with the multiple reflections of laser beam in the keyhole and Fresnel absorption on the keyhole wall. The line-source based keyhole model is modified. The predicted shape and size of the keyhole are employed to determine the distribution parameters of the volumetric heat source for laser beam welding, which are applied to the combined heat source model for hybrid laser+ pulsed gas metal arc welding (laser+GMAW-P) process. Based on such an adaptive heat source model, the numerical analysis of quasi-steady state temperature field in hybrid welding of TCS stainless steel is conducted. The hybrid welding experiments of TCS stainless steel are carried out, and the predicted weld shape and size are compared with the measured results to validate the established thermal model for hybrid welding. It is found that the thermal model for hybrid welding of TCS stainless steel based on the predicted keyhole shape can well simulate the temperature profiles and weld formation. Besides, the thermal model is used to calculate the shape and dimension of heat-affected zone (HAZ) and thermal cycles at different positions in HAZ under different process conditions, and the characteristics of thermal cycles of TCS stainless steel in hybrid welding are analyzed, which lay the foundation for the prediction of microstructure and properties of TCS stainless steel weld joints.
