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Fracture Modeling of AHSS in Component Crush Tests

Journal Article
2011-01-0001
ISSN: 1946-3979, e-ISSN: 1946-3987
Published April 12, 2011 by SAE International in United States
Fracture Modeling of AHSS in Component Crush Tests
Sector:
Citation: Chen, G., Shi, M., and Tyan, T., "Fracture Modeling of AHSS in Component Crush Tests," SAE Int. J. Mater. Manuf. 4(1):1-9, 2011, https://doi.org/10.4271/2011-01-0001.
Language: English

Abstract:

Advanced High Strength Steels (AHSS) have been implemented in the automotive industry to balance the requirements for vehicle crash safety, emissions, and fuel economy. With lower ductility compared to conventional steels, the fracture behavior of AHSS components has to be considered in vehicle crash simulations to achieve a reliable crashworthiness prediction. Without considering the fracture behavior, component fracture cannot be predicted and subsequently the crash energy absorbed by the fractured component can be over-estimated. In full vehicle simulations, failure to predict component fracture sometimes leads to less predicted intrusion. In this paper, the feasibility of using computer simulations in predicting fracture during crash deformation is studied. Three material fracture models, MAT_24, MAT_123, and MMC fracture model, available in LS-Dyna® finite element analysis code are adopted to simulate the fracture behavior of two dual-phase (DP) grades, i.e., DP590 and DP780 steels. To provide test data for the model validations, components made of DP590 and DP780 were fabricated and tested with axial crush and three-point bending loading conditions. During the simulation, forming simulation results such as plastic strains, thinning and damage parameters were mapped to the crash models as initial conditions in crash simulations so that the sensitivity of the forming effect on fracture modeling could be studied. The predicted crush force and crush mode were then compared to those from the component crush tests. The capability of the three material fracture models for fracture prediction was assessed and the results are discussed.