Resumen
Advanced high-strength steels (AHHS) are widely used in many production lines of car components. For efficient design of the forming processes, numerical methods are frequently applied in the automotive industry. To model the forming processes realistically, exact material data and analytical models are required. With respect to failure modelling, the accurate determination of failure onset continues to be a challenge. In this article, the complex phase (CP) steel CP800 is characterised for its failure characteristics using tensile tests with butterfly specimens. The material failure was determined by three evaluation methods: mechanically by a sudden drop in the forming force, optically by a crack appearing on the specimen surface, and acoustically by burst signals. As to be expected, the mechanical evaluation method determined material failure the latest, while the optical and acoustical methods showed similar values. Numerical models of the butterfly tests were created using boundary conditions determined by each evaluation method. A comparison of the experiments, regarding the forming force and the distribution of the equivalent plastic strain, showed sufficient agreement. Based on the numerical models, the characteristic stress states of each test were evaluated, which showed similar values for the mechanical and optical evaluation method. The characteristic stress states derived from the acoustical evaluation method were shifted to higher triaxialities, compared to the other methods. Matching the point in time of material failure, the equivalent plastic strain at failure was highest for the mechanical evaluation method, with lower values for the other two methods. Furter, three Johnson?Cook (JC) failure models were parametrised and subsequently compared. The major difference was in the slope of the failure models, of which the optical evaluation method showed the lowest slope. The reasons for the differences are the different stress states and the different equivalent plastic strains due to different evaluation areas.