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Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.

Periprosthetic fractures refer to the fractures that occur in the vicinity of the implants of joint replacement arthroplasty. Most of the fractures during an automotive frontal collision involve the long bones of the lower limbs (femur and tibia). Since the prevalence of persons living with lower limb joint prostheses is increasing, periprosthetic fractures that occur during vehicular accidents are likely to become a considerable burden on health care systems. It is estimated that approximately 4.0 million adults in the U.S. currently live with Total Knee Replacement (TKR) implants. Therefore, it is essential to study the injury patterns that occur in the long bone of a lower limb containing a total knee prosthesis. The aim of the present study is to develop an advanced finite element model that simulates the possible fracture patterns that are likely during vehicular accidents involving occupants who have knee joint prostheses in situ.

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements.

Model characteristics of a finite element deformable featureless headform with one to four layers of solid elements for the headform skin are studied using both the LS-DYNA3D and FCRASH codes. The models use a viscoelastic material law whose constitutive parameters are established through comparisons of drop test simulations at various impact velocities with the test data. Results indicate that the one-layer model has a significant distinct characteristic from the other (2-to-4-layer) models, thus requiring different parametric values. Similar observation is also noticed in simulating drop tests with one and two layers of solid elements for the headform skin using PAM-CRASH. When using the same parametric values for the viscoelastic material, both the LS-DYNA3D and FCRASH simulations yield the same results under identical impact conditions and, thereby, exhibit a “functional equivalency” between these two codes.

This paper examines the theoretical worst case of normal headform impact on an infinitely rigid surface with the help of a dynamic spring-mass model. It is pointed out that the current approach is not an actual representation of any vehicle upper interior but is useful in gaining insight into the headform impact phenomenon and determining how to further enhance design. After considering force-deflection characteristics of a variety of commonly used headform impact protection countermeasures, a mathematical model is set up with spring properties that approximate those of physical countermeasures. Closed-form solutions are derived for various dynamic elasto-plastic phases including elastic unloading and contact. A parametric study is then carried out with HIC(d) as the dependent variable, and spring stiffness, yield force and spring length (representing countermeasure crush space) as the design variables.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

An attractive strategy for joining metallic as well as non-metallic substrates through adhesive bonding. This technique of joining also offers the functionality for joining dissimilar materials. However, doubts are often expressed on the ability of such joints to perform on par with other mechanical fastening methodologies such as welding, riveting, etc. In the current study, adhesively-bonded single lap shear (SLS), double lap shear (DLS) and T-peel joints are studied initially under quasi-static loading using substrates made of a grade of mild steel and an epoxy-based adhesive of a renowned make (Huntsman). Additionally, single lap shear joints comprised of a single spot weld are tested under quasi-static loading. The shear strengths of adhesively-bonded SLS joints and spot-welded SLS joints are found to be similar. An important consideration in the deployment of adhesively bonded joints in automotive body structures would be the performance of such joints under impact loading.

Recent experimental studies on the behavior of adhesively-bonded steel double-hat section components under axial impact loading have produced encouraging results in terms of load-displacement response and energy absorption when compared to traditional spot-welded hat- sections. However, it appears that extremely limited study has been carried out on the behavior of such components under transverse impact loading keeping in mind applications such as automotive body structures subject to lateral/side impact. In the present work, lateral impact studies have been carried out in a drop-weight test set-up on adhesively-bonded steel double-hat section components and the performance of such components has been compared against their conventional spot-welded and hybrid counterparts. It is clarified that hybrid components in the present context refer to adhesively-bonded hat-sections with a few spot welds only aimed at preventing catastrophic flange separations.

This paper presents the design of a crash detection system based on the principles of continuous-mode Hidden Markov Models (HMM) with real-valued emission parameters. Our design utilizes log-likelihood for optimizing HMM parameters including the number of states in the model and the accelerometer crash-pulse buffer size resulting in lower costs and complexity of the crash detection system. Cross validation technique based on Jackknifing is utilized to estimate the crash pulse detection rate for a variety of crash events involving rigid as well as offset deformable barriers with head-on and oblique angle impacts. The system is simulated using Matlab and Simulink, and the proposed model is able to accurately classify crash-events within 10 ms from the time of the impact.

Development of frontal impact airbag sensor algorithms/calibrations requires crash signals, which can be obtained from vehicle crash testing and/or CAE simulations. This paper presents the development of finite element sensor models to generate CAE simulated crash pulses/signals at the sensing location during frontal impacts. These signals will be evaluated for potential used in the airbag sensor algorithm/calibration.

The present work is concerned with the objective of developing a process for practical multi-disciplinary design optimization (MDO). The main goal adopted here is to minimize the weight of a vehicle body structure meeting NVH (Noise, Vibration and Harshness), durability, and crash safety targets. Initially, for simplicity a square tube is taken for the study. The design variables considered in the study are width, thickness and yield strength of the tube. Using the Response Surface Method (RSM) and the Design Of Experiments (DOE) technique, second order polynomial response surfaces are generated for prediction of the structural performance parameters such as lowest modal frequency, fatigue life, and peak deceleration value. The optimum solution is then obtained by using traditional gradient-based search algorithm functionality “fmincon” in commercial Matlab package.

State of the art electronic restraint systems rely on the acceleration measured during a vehicle crash for deployment decisions. The acceleration signal is analyzed with different criteria, among which the velocity change is a dominant criterion in almost any existing crash detection algorithm. Sensors in the front crush zone have recently been added to help develop restraint systems that comply with the new FMVSS208 and EuroNCAP regulations. Front crash sensors are usually evaluated for their velocity change during a crash and typically play a key role in the deployment decision. CAE based FEA analysis has recently been used to generate signals at the sensor module locations in crash simulations to provide supplemental information for crash sensing algorithm development and calibration. This paper presents an initial effort in developing a velocity-based crash detection algorithm, that allows broad use of CAE generated velocity time histories for system calibration.

Numerical analyses frequently accompany experimental investigations that study injury biomechanics and improvements in automotive safety. Limited by computational speed, earlier mathematical models tended to simplify the system under study so that a set of differential equations could be written and solved. Advances in computing technology and analysis software have enabled the development of many sophisticated models that have the potential to provide a more comprehensive understanding of human impact response, injury mechanisms, and tolerance. In this article, 50 years of publications on numerical modeling published in the Stapp Car Crash Conference Proceedings and Journal were reviewed. These models were based on: (a) author-developed equations and software, (b) public and commercially available programs to solve rigid body dynamic models (such as MVMA2D, CAL3D or ATB, and MADYMO), and (c) finite element models.

As early as the 1950's, Gurdjian and colleagues (Gurdjian et al., 1955) observed that brain injuries could occur by direct pressure loading without any global head accelerations. This pressure-induced injury mechanism was "forgotten" for some time and is being rekindled due to the many mild traumatic brain injuries attributed to blast overpressure. The aim of the current study was to develop a finite element (FE) model to predict the biomechanical response of rat brain under a shock tube environment. The rat head model, including more than 530,000 hexahedral elements with a typical element size of 100 to 300 microns was developed based on a previous rat brain model for simulating a blunt controlled cortical impact. An FE model, which represents gas flow in a 0.305-m diameter shock tube, was formulated to provide input (incident) blast overpressures to the rat model. It used an Eulerian approach and the predicted pressures were verified with experimental data.

A number of studies, using data from NASS-CDS, have shown a large percentage of rollover crashes can be classified as tripped events. In many cases, the requirements for a tripped rollover detection algorithm are driven by the timely activation of an occupant containment device. To meet these requirements rollover detection algorithms have been developed by utilizing vehicle roll rate, lateral and vertical accelerations data collected primarily from laboratory tests. This study identifies and examines several challenges associated with developing a rollover detection algorithm with enhanced capabilities. Enhancement of the detection algorithm is explored by considering additional vehicle responses: forward velocity and sideslip angle. With the additional signals, discrimination of rollover crashes from other crash modes is discussed. Potential field/laboratory test modes are proposed to generate the additional vehicle signals.

The current paper presents improvements of a previous single-degree-of-freedom lumped parameter model with a nonlinear spring that could be used for preliminary design of headform impact safety countermeasures for normal impact with negligible headform rotation. The unloading taking place along the elastic path has been dispensed with and a parabolic unloading path may yield more realistic force-deformation and deceleration-time behaviors when compared with test results. The effects of the modified unloading behavior on HIC(d) are illustrated with examples. Additionally, a new velocity-dependent yield force criterion is adopted for the spring element to represent strain rate sensitive countermeasures. It is observed that inclusion of strain rate effect can either increase or decrease predicted HIC(d) when compared with using only quasi-static yield force.

The seatbelt system, originally designed for protecting occupants in frontal crashes, has been reported to be inadequate for preventing occupant head-to-roof contact during rollover crashes. To improve the effectiveness of seatbelt systems in rollovers, in this study, we reviewed previous literature and proposed vertical head excursion corridors during static inversion and dynamic rolling tests for human and Hybrid III dummy. Finite element models of a human and a dummy were integrated with restraint system models and validated against the proposed test corridors. Simulations were then conducted to investigate the effects of varying design factors for a three-point seatbelt on vertical head excursions of the occupant during rollovers. It was found that there were two contributing parts of vertical head excursions during dynamic rolling conditions.

A mathematical model of an airbag restraint system for automobile drivers, including the simulation of the simultaneous collapse of the steering column, has been developed. The model is designed to work in conjunction with a three-dimensional occupant model. It is capable of assessing the relative effects of airbag size, pressure, deployment rate, venting area, contact force, steering column collapse force, and column collapse distance. The results of the model are compared with experimental runs in which anthropometric dummies were used as test subjects. Good correlation was obtained for torso kinematics. The model can be conveniently used for a parametric study to aid the design of airbag restraint systems.

This paper represents the development of a new design methodology based on data mining theory for decision making in vehicle crashworthy components (or parts) development. The new methodology allows exploring the big crash simulation dataset to discover the underlying complicated relationships between vehicle crash responses and design variables at multi-levels, and deriving design rules based on the whole vehicle safety requirements to make decisions towards the component and sub-component level design. The method to be developed will resolve the issue of existing design approaches for vehicle crashworthiness, i.e. limited information exploring capability from big datasets, which may hamper the decision making and lead to a nonoptimal design. A preliminary design case study is presented to demonstrate the performance of the new method. This method will have direct impacts on improving vehicle safety design and can readily be applied to other complex systems.

This paper presents a method to obtain improved foam/pillar structural designs to help enhance occupant interior impact protection. Energy absorbing foams are used in this study with their thickness and crush strength being selected as primary design variables for optimization. The response surface techniques in the design of experiment are used in the optimization process. Head impact analyses are conducted by a CAE model with explicit, nonlinear, dynamic finite element code LS-DYNA3D. A baseline model is developed and verified by comparing the simulation results with the experimental data. Based on this model, the anticipated effects of stiffness of the pillar structure and the trim on the Head Injury Criterion (HIC) results are also assessed. The optimization approach in this study provides a comprehensive consideration of the factors which affect the HIC value.