Thermomechanical simulation of the heat-affected zones in welded ultra-high strength steels: Microstructure and mechanical properties

Ultra-high strength steels (UHSS) have a determining role in construction and industry. Furthermore, welding as the primary joining process for steel has a similar role in promoting its applications. Therefore, welded UHSS have a vital role in related applications. However, due to their complex microstructures, these steels are more prone to harmful effects of welding heat input on the mechanical properties compared to mild steels. Thus, identifying the correlations between the microstructural transformations triggered by the heat input and the mechanical properties can lead to new insights and hindering the drawbacks. This study investigates the microstructures and mechanical properties of S960 (with a severe softening after welding) and S1100 (with a negligible decrease of the mechanical properties after welding) to understand the mechanisms behind the softening of welded UHSS. Microstructural analysis showed the formation of soft phases, e.g., ferrite and granular bainite, as the primary reason for the softening. Furthermore, tempered forms of martensite and bainite resulted in the simultaneous decrease of hardness and notch toughness. Finally, the applicabilities of two experimental approaches to predict hardness from microstructural constituents were evaluated for welded S960 and S1100 and proved to have relatively good reliability to detect their HAZ softened spots.</p

Possibilities of Artificial Intelligence-Enabled Feedback Control System in Robotized Gas Metal Arc Welding

In recent years, welding feedback control systems and weld quality estimation systems have been developed with the use of artificial intelligence to increase the quality consistency of robotic welding solutions. This paper introduces the utilization of an intelligent welding system (IWS) for feedback controlling the welding process. In this study, the GMAW process is controlled by a backpropagation neural network (NN). The feedback control of the welding process is controlled by the input parameters; root face and root gap, measured by a laser triangulation sensor. The NN is trained to adapt NN output parameters; wire feed and arc voltage override of the weld power source, in order to achieve consistent weld quality. The NN is trained offline with the specific parameter window in varying weld conditions, and the testing of the system is performed on separate specimens to evaluate the performance of the system. The butt-weld case is explained starting from the experimental setup to the training process of the IWS, optimization and operating principle. Furthermore, the method to create IWS for the welding process is explained. The results show that the developed IWS can adapt to the welding conditions of the seam and feedback control the welding process to achieve consistent weld quality outcomes. The method of using NN as a welding process parameter optimization tool was successful. The results of this paper indicate that an increased number of sensors could be applied to measure and control the welding process with the developed IWS

Thermomechanical simulation of the heat-affected zones in welded ultra-high strength steels:microstructure and mechanical properties

Abstract Ultra-high strength steels (UHSS) have a determining role in construction and industry. Furthermore, welding as the primary joining process for steel has a similar role in promoting its applications. Therefore, welded UHSS have a vital role in related applications. However, due to their complex microstructures, these steels are more prone to harmful effects of welding heat input on the mechanical properties compared to mild steels. Thus, identifying the correlations between the microstructural transformations triggered by the heat input and the mechanical properties can lead to new insights and hindering the drawbacks. This study investigates the microstructures and mechanical properties of S960 (with a severe softening after welding) and S1100 (with a negligible decrease of the mechanical properties after welding) to understand the mechanisms behind the softening of welded UHSS. Microstructural analysis showed the formation of soft phases, e.g., ferrite and granular bainite, as the primary reason for the softening. Furthermore, tempered forms of martensite and bainite resulted in the simultaneous decrease of hardness and notch toughness. Finally, the applicabilities of two experimental approaches to predict hardness from microstructural constituents were evaluated for welded S960 and S1100 and proved to have relatively good reliability to detect their HAZ softened spots