RESUMO
Resistance spot welding (RSW) is a common joining technique in the production of car bodies in white for example, because of its high degree of automation, its short process time, and its reliability. While different steel grades and even dissimilar metals can be joined with this method, the current paper focuses on similar joints of galvanized advanced high strength steel (AHSS), namely dual phase steel with a yield strength of 1200 MPa and high ductility (DP1200HD). This material offers potential for light-weight design. The current work presents a multi-physical finite element (FE) model of the RSW process which gives insights into the local loading and material state, and which forms the basis for future investigations of the local risk of liquid metal assisted cracking and the effect of different process parameters on this risk. The model covers the evolution of the electrical, thermal, mechanical, and metallurgical fields during the complete spot welding process. Phase transformations like base material to austenite and further to steel melt during heating and all relevant transformations while cooling are considered. The model was fully parametrized based on lab scale material testing, accompanying model-based parameter determination, and literature data, and was validated against a large variety of optically inspected burst opened spot welds and micrographs of the welds.
RESUMO
In the automotive industry, corrosion protected galvanized advanced high strength steels with high ductility (AHSS-HD) gain importance due to their good formability and their lightweight potential. Unfortunately, under specific thermomechanical loading conditions such as during resistance spot welding galvanized, AHSS-HD sheets tend to show liquid metal embrittlement (LME). LME is an intergranular decohesion phenomenon leading to a drastic loss of ductility of up to 95%. The occurrence of LME for a given galvanized material mainly depends on thermal and mechanical loading. These influences are investigated for a dual phase steel with an ultimate tensile strength of 1200 MPa, a fracture strain of 14% and high ductility (DP1200HD) by means of systematic isothermal hot tensile testing on a Gleeble® 3800 thermomechanical simulator. Based on the experimental findings, a machine learning procedure using symbolic regression is applied to calibrate an LME damage model that accounts for the governing quantities of temperature, plastic strain and strain rate. The finite element (FE) implementation of the damage model is validated based on the local damage distribution in the hot tensile tested samples and in an exemplary 2-sheet resistance spot weld. The developed LME damage model predicts the local position and the local intensity of liquid metal induced cracking in both cases very well.
