Performance Prediction of Resistance Spot Welding Joints Using a Modified GTN Model

Abstract

Nowadays Al-steel joints are increasingly used in the lightweight automobile structure to meet the requirement of energy saving and CO2 emission reduction. Among various joining technologies proposed to join dissimilar material, resistance spot welding (RSW) stands out since the operation speed is fast, no extra material is needed and it is easy to be automated in mass production. Determining the joint load bearing capacity is one important task in the further application of this technology. Traditionally, it is obtained by performing some fractured tests, such as lap-shear test, coach peel test, cross tension test, by extracting and then analyzing the mechanical performance parameters including maximum load and failure energy from the force-and-displacement (F-D) curves. However, this method is time consuming and finite element simulation provides a much more efficient solution. Therefore, this work aimed at developing an experimentally validated performance model of Al-steel RSW joint. An aluminum alloy (AA6022) and a hot-dip galvanized high strength low alloy steel (HDG HSLA340), both of which are widely used in automotive industry, were joined by a unique RSW process proposed by General Motors in lap-shear configuration. To predict the joint fracture, a modified Gurson-Tvergaard-Needleman (GTN) model was applied. Finally, this performance model was validated experimentally and proved to be capable of predicting the maximum load and failure energy accurately.