Modeling and characterization of spot weld material configurations for crash analysis

Abstract

To achieve an effective design of automotive structures, a material's mechanical properties are crucial, especially in welded structures that are susceptible to impact loading, such as in vehicle collisions. The primary objective of this research is to characterize resistance spot welding (RSW) for steel material and to develop an equivalent simplified weld model using material characterization. A secondary objective is to investigate friction stir spot welding (FSSW) for a material flow study using a smooth particle hydrodynamics (SPH) formulation and to compare it with RSW. During the initial phase of this study, friction stir welding (FSW) is investigated for temperature evolution, plastic strain, and material flow using finite element (FE) simulations, which are carried out using an elasto-plastic model. A heat source FSW model is developed to predict the thermal effect. FSSW results are compared with the results from RSW, reaching the conclusion that RSW is still a better method for the automotive industry. The necessary conditions for all RSW modeling are virtual test data that exist for spot-welded specimens. After developing a simplified weld model, the parameters gained from the sample specimen are transferred to the simulation of components tests. Components of a test especially designed for the connection failure illustrate that neglecting a spot-weld failure leads to altered energy absorption. Vehicle-level test also considered in this evaluation. Finally, to address the overdesigning issue, an optimization procedure is carried out using the I-sight software design methodology for vehicle mass reduction. Thus, a suitable modeling approach is investigated numerically for mapping the spot weld in a crash simulation. Further development of the analytical methods and user-defined material would be extremely beneficial; however, the proof of concept successfully developed in this dissertation satisfies its objective.