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Technical Paper

Calibration and Validation of GISSMO Damage Model for A 780-MPa Third Generation Advanced High Strength Steel

2020-04-14
2020-01-0198
To evaluate vehicle crash performance in the early design stages, a reliable fracture model is needed in crash simulations to predict material fracture initiation and propagation. In this paper, a generalized incremental stress state dependent damage model (GISSMO) in LS-DYNA® was calibrated and validated for a 780-MPa third generation advanced high strength steels (AHSS), namely 780 XG3TM steel that combines high strength and ductility. The fracture locus of the 780 XG3TM steel was experimentally characterized under various stress states including uniaxial tension, shear, plane strain and equi-biaxial stretch conditions. A process to calibrate the parameters in the GISSMO model was developed and successfully applied to the 780 XG3TM steel using the fracture test data for these stress states.
Journal Article

Validation of GISSMO Model for Fracture Prediction of a Third-Generation Advanced High-Strength Steel

2018-04-03
2018-01-0107
Advanced high-strength steels (AHSS), due to their significantly higher strength than the conventional high-strength steels, are increasingly used in the automotive industry to meet future safety and fuel economy requirements. Unlike conventional steels, the properties of AHSS can vary significantly due to the different steelmaking processes and their fracture behaviors should be characterized. In crash analysis, a fracture model is often integrated in the simulations to predict fracture during crash events. In this article, crash simulations including a fracture criterion are conducted for a third-generation AHSS, that is, 980GEN3. A generalized incremental stress state dependent damage model (GISSMO) in LS-DYNA is employed to evaluate the fracture predictability in the crash simulations.
Technical Paper

Determination of the Forming Limit Curve Using Digital Image Correlation - Comparison of Different Approaches to Pinpoint the Onset of Localized Necking

2017-03-28
2017-01-0301
Digital image correlation (DIC) technique has been proved as a potent tool to determine the forming limit curve (FLC) of sheet metal. One of the major technical challenges using the DIC to generate FLC is to accurately pinpoint the onset of localized necking from the DIC data. In addition to the commonly applied ISO 12004-2 standard, a plethora of other DIC data analysis approaches have been developed and used by various users and researchers. In this study, different approaches, including spatial, temporal and hybrid approaches, have been practiced to determine the limit strains at the onset of localized necking. The formability of a 980GEN3 sheet steel was studied in this work using the Marciniak cup test coupled with a DIC system. The resulting forming limits determined by different approaches were compared. Strengths and limitations of each approach were discussed. In addition, the conventional finger-touch approach was excised using specimens with perceivable localized necks.
Technical Paper

Determination of Fracture Strain of Advanced High Strength Steels Using Digital Image Correlation in Combination with Thinning Measurement

2017-03-28
2017-01-0314
Fracture strain data provide essential information for material selection and serve as an important failure criterion in computer simulations of crash events. Traditionally, the fracture strain was measured by evaluating the thinning at fracture using tools such as a microscope or a point micrometer. In the recent decades, digital image correlation (DIC) has evolved as an advanced optical technique to record full-field strain history of materials during deformation. Using this technique, a complete set of the fracture strains (including major, minor, and thickness strains) can be approximated for the material. However, results directly obtained from the DIC can be dependent on the experiment setup and evaluation parameters, which potentially introduce errors to the reported values.
Technical Paper

Springback Prediction Improvement Using New Simulation Technologies

2009-04-20
2009-01-0981
Springback is a major concern in stamping of advanced high strength steels (AHSS). The existing computer simulation technology has difficulty predicting this phenomenon accurately even though it is well developed for formability simulations. Great efforts made in recent years to improve springback predictions have achieved noticeable progress in the computational capability and accuracy. In this work, springback simulation studies are conducted using FEA software LS-DYNA®. Various parametric sensitivity studies are carried out and key variables affecting the springback prediction accuracy are identified. Recently developed simulation technologies in LS-DYNA® are implemented including dynamic effect minimization, smooth tool contact and newly developed nonlinear isotropic/kinematic hardening material models. Case studies on lab-scale and full-scale industrial parts are provided and the predicted springback results are compared to the experimental data.
Technical Paper

Prediction of Stretch Flangeability Limits of Advanced High Strength Steels using the Hole Expansion Test

2007-04-16
2007-01-1693
More and more advanced high strength steels (AHSS) such as dual phase steels and TRIP steels are implemented in automotive components due to their superior crash performance and vehicle weight reduction capabilities. Recent trends show increased applications of higher strength grades such as 780/800 MPa and 980/1000 MPa tensile strength for crash sensitive components to meet more stringent safety regulations in front crash, side impact and roll-over situations. Several issues related to AHSS stamping have been raised during implementation such as springback, stretch bending fracture with a small radius to thickness ratio, edge cracking, etc. It has been shown that the failure strains in the stretch bending fracture and edge cracking can be significantly lower than the predicted forming limits, and no failure criteria are currently available to predict these failures.
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