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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.

Three computational gas and fluid dynamic methods, CV/UP (Control Volume/Uniform Pressure), CPM (Corpuscular Particle Method), and ALE (Arbitrary Lagrangian and Eulerian), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side crash applications.

Explicit method is commonly used in crashworthiness analysis due to its capability to solve highly non-linear problems without numerous iterations and convergence problems. However, the time step for explicit methods is limited by the time that the physical wave crosses the element. Therefore, to avoid large amount of CPU time, the explicit method is usually used for non-linear dynamic problems with a short period of simulation duration. For problems under quasi-static loading conditions at pre-crash and post-crash, implicit method could be more efficient than explicit methods because the required computation time is much shorter. Due to the recent advance of crash codes, which allows both implicit and explicit computations to be performed in the same code, crash engineers are able to use explicit computation for crash simulation as well as implicit computation for some of the pre-crash quasi-static loading or post-crash spring back simulations.

Because of their excellent crash energy absorption capacity, dual phase (DP) steels are gradually replacing conventional High Strength Low Alloy (HSLA) steels for critical crash components in order to meet the more stringent vehicle crash safety regulations. To achieve optimal axial and bending crush performance using DP steels for crash components designed for crash energy absorption and/or intrusion resistance applications, the cross sections need to be optimized. Correlated crush simulation models were employed for the cross-section study. The models were developed using non-linear finite element code LS-DYNA and correlated to dynamic and quasi-static axial and bending crush tests on hexagonal and octagonal cross-sections made of DP590 steel. Several design concepts were proposed, the axial and bending crush performance in DP780 and DP980 were compared, and the potential mass savings were discussed.

The frame rail has an impact on the crash performance of body-on-frame (BOF) and uni-body vehicles. Recent developments in materials and forming technology have prompted research into improving the energy absorption and deformation mode of the frame rail design. It is worthwhile from a timing and cost standpoint to predict the behavior of the front rail in a crash situation through finite element techniques. This study focuses on improving the correlation of the frame component Finite Element model to physical test data through sensitivity analysis. The first part of the study concentrated on predicting and improving the performance of the front rail in a frontal crash [1]. However, frame rails in an offset crash or side crash undergo a large amount of bending. This paper discusses appropriate modeling and testing procedures for front rails in a bending situation.

The optimization method and CAE analysis have been widely used in structure design for crash safety. Combining the CAE analysis and optimization approach, vehicle structure design for crash can be implemented more efficiently. One of the recent safety desirables in structure design is to reduce vehicle pitch and drop. At frontal impact tests with unbelted occupants, the interaction between occupant's head and interior header/sun visor, which is caused by excessive vehicle pitch and drop, is not desired in vehicle crash development. In order to comply with the federal frontal crash requirements for unbelted occupant, it is necessary to manage the vehicle pitch and drop by improving structure design. In this paper, a systematic process of CAE analysis with optimization approach is applied for discovering the major structural components affecting vehicle pitch and drop.

The front rail plays a very important role in vehicle crash. Trigger holes are commonly used to control frame crush mode due to their simple manufacturing process and flexibility for late changes in the product development phase. Therefore, a study, including CAE and testing, was conducted on a production front rail to understand the effects of trigger hole shape, size and orientation. The trigger hole location in the front rail also affects crash performance. Therefore, the effect of trigger hole location on front rail crash behavior was studied, and understanding these effects is the main objective of this study. A tapered front rail produced from 1.7 mm thick DP600 steel was used for the trigger hole location investigation. Front rails with different trigger spacing and sizes were tested using VIA sled test facility and the crash progress was simulated using a commercial code RADIOSS. The strain rate, welding and forming effects were incorporated in the front rail modeling.

This paper describes (1) the findings from the implementation of a component test methodology for body, engine and transmission mounts [1, 2 and 3], and (2) the associated CAE model development and mount design robustness enhancement. A series of component tests on light truck body, engine and transmission mounts have been conducted to not only obtain their characteristics as inputs for crashworthiness analysis, but also drive mount design direction for frontal impacts.

The front rail plays an important role in the performance of body-on-frame (BOF) vehicles in frontal crashes. New developments in materials and forming technology have led to the exploration of different configurations to improve crash performance. This paper presents the initial stages of an ongoing study to investigate the effects of the cross section of steel columns on crash performance in automotive applications. Because accurate prediction of the performance of these rails can help reduce the amount of physical crash testing necessary, the focus of this paper is on appropriate testing and modeling procedures for different rail configurations. In the first part of this paper, the Finite Element Analysis (FEA) methodology is presented with respect to correlation with real world tests. The effects of various parameters are described, along with the optimum configuration for model correlation.

Strain rate effects have been identified as one of the most critical factors for the modeling of vehicle components in many previous investigations. The strain rate data available to the authors have been processed to obtain the input decks of a required material law in prior investigations. With the application of strain rate modeling, the strain rate database needs to be expanded. In order to continuously improve the safety CAE quality and efficiency, especially the prediction of a vehicle's pulse in a crash event, the effort has been made to include more strain rate data and extend the material database for safety CAE applications. In this study, strain rate data provided by Ispat Inland Inc. for AISI/DOE Technology Roadmap Program are processed. The material processed in this study include HSS590-CR, 440W-GA, BH300-GI, HSLA350-GI, DP600-HR, TRIP590-EG, TRIP600-CR, TRIP780-CR.

The frontal rail is one of the most important components of a vehicle in determining crash performance, especially for a body on frame vehicle. Prior research [1] has shown that the frontal rail absorbs a significant amount of impact energy in a crash condition. In order to optimize crash performance, a component level sensitivity study was conducted to determine the effect different types of triggers would have on the performance of the frontal rail. The objective of this study is to determine the sensitivity of trigger size, trigger shape, and trigger orientation as well as to improve corresponding trigger modeling methodology by comparing crushed components to crushed CAE models. In this sensitivity study, the location of the triggers was held fixed, while the size, shape, and orientation were varied. The metric that will be used to compare the performance of these different trigger shapes is the overall stiffness of the frontal rail.

Vehicle pitch and drop play an important role for occupant neck and head injury at frontal impact. The excessive vehicle header drop, due to vehicle pitch and drop during crash, induces aggressive interaction between occupant head and sun visor/header that causes serious head and neck injuries. For most of body-on-frame vehicles, vehicle pitch and drop have commonly been observed at frontal impact tests. It is because the vehicle body is pulled downward by frame rails, which bend down during crash. Hence, the challenges of frame design are not only to absorb crash energy but also to manage frame deformation for minimizing vehicle pitch and drop. In this paper, the finite element method is used to analyze frame deformation at full frontal impact. To ensure the quality of CAE model, a full vehicle FEA model is correlated to barrier tests. In addition, a study of CAE modeling affecting vehicle header drop is performed.

This study focuses on the modeling of a frame in a body-on-frame (BOF) vehicle to improve the prediction of vehicle response in crashes. The study is divided into three phases - component (frame material modeling), subsystem (frame sled test) and full system (full vehicle test). In the component level, we investigate the available strain rate data, the performance of various material models in crash codes and the effect of the strain rate in crash simulation. In the subsystem phase, we incorporate the strain rate modeling and expand the scope to include both the forming and the welding effects in the subsystem CAE model to improve the correlation between CAE and test. Finally the improved frame modeling methodology with strain rate, forming and welding effects is adopted in full vehicle model. It is found that the proposed frame modeling methodology is crucial to improve the pulse prediction of a full vehicle in crashes.