Search Results

This paper focuses on the role and significance of linear momentum and kinetic energy in controlling air bags aboard vehicles. Among the results of the study are analytic and geometric models that characterize crash behavior and control algorithms that quantify crash severity and identify crash configurations. These results constitute an effective basis for crash-data design and air-bag control.

This paper describes the development of a new component test methodology concept for simulating NHTSA side impact, to evaluate the performance of door subsystems, trim panels and possible safety countermeasures (foam padding, side airbags, etc.). The concept was developed using MADYMO software and the model was validated with a DOT-SID dummy. Moreover, this method is not restricted to NHTSA side impact, but can be also be used for simulating the European procedure, with some modifications. This method uses a combination of HYGE and VIA decelerator to achieve the desired door velocity profile from onset of crash event until door-dummy separation, and also takes into account the various other factors such as the door/B pillar-dummy contact velocity, door compliance, shape of intruding side structure, seat-to-door interaction and initial door-dummy distance.

In vehicle crash tests, an unbelted occupant's kinetic energy is absorbed by the restraints such as an air bag and/or knee bolster and by the vehicle structure during occupant ride-down with the deforming structure. Both the restraint energy absorbed by the restraints and the ride-down energy absorbed by the structure through restraint coupling were studied in time and displacement domains using crash test data and a simple vehicle-occupant model. Using the vehicle and occupant accelerometers and/or load cell data from the 31 mph barrier crash tests, the restraint and ride-down energy components were computed for the lower extremity, such as the femur, for the light truck and passenger car respectively.

This paper discusses a method to reduce the reliance on testing by using CAE to arrive at a stable instrument panel support structure which is capable of resisting the deployment of the passenger airbag. This technique has been used on various instrument panels, and has proven to be useful to the instrument panel design team. Tests have shown that deployment of the airbag results in large forces which act on an instrument panel. This paper describes a method to evaluate those forces and their impact on the surrounding instrument panel structure. The method uses loads from simple bench test data. Loads at the airbag mounting locations during an airbag deployment were measured. Those loads were used in the analysis to simulate the behavior of the airbag deployment on the instrument panel substrate. The analysis enabled the design engineering team to achieve an understanding of the event and to revise the surrounding instrument panel structure design in order to improve its performance.

Frontal airbag interaction with the head and neck of the Hybrid III family of dummies may involve a nonbiofidelic interaction. Researchers have found that the deploying airbag may become entrapped in the hollow cavity behind the dummy chin. This study evaluated a prototype neck shield design, the Flap Neck Shield, for biofidelic response and the ability to prevent airbag entrapment in the chin/jaw cavity. Neck pendulum calibration tests were conducted for biofidelity evaluation. Static and dynamic airbag deployments were conducted to evaluate neck shield performance. Tests showed that the Flap Neck Shield behaved in a biofidelic manner with neck loads and head motion within established biofidelic limits. The Flap Neck Shield did not alter the neck loads during static or dynamic airbag interactions, but it did consistently prevent the airbag from penetrating the chin/jaw cavity.

The potential effects of passenger air bag deployment on an out-of-position three-year-old child dummy and on a three-year-old child dummy in a child restraint system are two of the items considered in the development of an automotive passenger air bag restraint system. In order to increase our understanding of the passenger air bag and three-year-old dummy interaction, we have developed a three dimensional computer model of a three-year-old child dummy. The dummy model has a compressible sternum and a multi-segment representation of the neck which helps improve the predictive capabilities of the neck criteria. The dummy properties needed as inputs to the occupant model were all experimentally determined. An energy technique was used for separating the elastic, damping and friction components for each joint. Three HYGE sled test cases were simulated to validate the model.

The development of combined finite element and spring / rigid mass crash simulation dummy models for automotive applications is described. In order to better understand the crash phenomena and occupant kinematics during vehicle crashes, recent developments have been focused on the use of finite element techniques in the simulation of both structure and structure / dummy interactions. The combination of spring /rigid mass modeling and finite element technique is used to develop models of fiftieth percentile Hybrid III and Side impact Dummies in a finite element program (RADIOSS). In general, the dummies are modeled with rigid masses and joints with techniques similar to those used in Crash Victim Simulation programs like MADYMO and CAL3D. Only selected components, like the Hybrid III dummy thorax and the SID pelvis and jacket, are modeled with finite element shell and brick elements to improve dummy / restraint system and dummy / structure interaction responses.

This paper describes the development of a Dynamic Door Component Test Methodology (DDCTM) for side impact simulation. A feasibility study of the methodology was conducted using a MADYMO computer model by taking parameters such as door pre-crush, door-to-SID (Side Impact Dummy) contact velocity and the deceleration profile into consideration. The prove-out tests of this methodology was carried out on a dynamic sled test facility. The DDCTM has been validated for various carlines. In addition, various existing dynamic component test methods are reviewed. In our approach, a pre-crushed door, mounted on a sled, strikes a stationary SID at a pre-determined velocity. A programmable hydraulic decelerator is used to decelerate the sled to simulate the barrier/door deceleration pulse during door-to-SID contact period. This test procedure provides excellent correlation of the SID responses between the component test and the full-scale vehicle test.

Transfer or response equations are important as they provide relationships between the responses of different surrogates under matched, or nearly identical loading conditions. In the present study, transfer equations for different body regions were developed via mathematical modeling. Specifically, validated finite element models of the age-dependent Ford human body models (FHBM) and the mid-sized male Hybrid III (HIII50) were used to generate a set of matched cases (i.e., 192 frontal sled impact cases involving different restraints, impact speeds, severities, and FHBM age). For each impact, two restraint systems were evaluated: a standard three-point belt with and without a single-stage inflator airbag. Regression analyses were subsequently performed on the resulting FHBM- and HIII50-based responses. This approach was used to develop transfer equations for seven body regions: the head, neck, chest, pelvis, femur, tibia, and foot.

The potential of head injury in frontal barrier impact tests was investigated by a mathematical model which consisted of a finite element human head model, a four segments rigid dynamic neck model, a rigid body occupant model, and a lumped-mass vehicle structure model. The finite element human head model represents anatomically an average adult head. The rigid body occupant model simulates an average adult male. The structure model simulates the interior space and the dynamic characteristics of a vehicle. The neck model integrates the finite element human head to the occupant body to give a more realistic kinematic head motion in a barrier crash test. Model responses were compared with experimental cadaveric data and vehicle crash data for the purpose of model validation to ensure model accuracy. Model results show a good agreement with those of the tests.

This paper describes further developments of the MVMA-2D model including program modifications of the air bag and the energy absorbing steering assembly submodels. The air bag submodel and the steering assembly submodel in the MVMA-2D crash victim simulation are independently formulated. No coupling exists between these two submodels to permit simulation of the kinematics of an anthropomorphic dummy restrained by a driver air bag restraint system mounted on a collapsible steering column. The development effort of integrating both submodels to provide the MVMA-2D model with such a capability is presented. The integrated model has been successfully utilized in simulating dynamic responses, in frontal impact situations, of a dummy restrained by a driver air bag restraint system mounted on a collapsible steering column. Validations of the model were made by comparing simulation results with experimental test data.

Vehicle side impact performance is potentially affected by a large number of parameters which may be related to body stiffness and energy absorption characteristics, and packaging dimensions. An understanding of the principal variables controlling TTI (Thoracic Trauma Index) is fundamental to the achievement of high LINCAP (Lateral Impact New Car Assessment Program) rating especially for sedans. In the present study, the effects on TTI of the following are considered: response-related parameters such as velocity and intrusion (which are in turn related to body structure), countermeasures such as side airbag, and dummy to structure clearance dimensions. With the help of test data gathered from side impact tests carried out on cars and trucks at Ford, a new “best subset” regression model is developed and is shown to be able to predict TTI for a number of LINCAP tests which were not part of the suite used in the derivation of the model.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash 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 impact applications.

In the 1999 Supplemental Notice for Proposed Rulemaking (SNPRM) for Advanced Airbags, the National Highway Traffic Safety Administration (NHTSA) sought comments on the maximum speed at which the high-speed, unbelted occupant test suite will be conducted, i.e., 48 kph vs. 40 kph. To help address this question, an analysis of constraints was performed via extensive mathematical modeling of a theoretical restraint system. First, math models (correlated with several existing physical tests) were used to predict the occupant responses associated with 336 different theoretical dual-stage driver airbag designs subjected to six specific Regulated and non-Regulated tests.

The increased focus on occupant protection by automobile manufacturers combined with incessant consumer demand for safety features such as dual airbags has posed design engineers with major challenges in the field of Instrument Panel (IP) design. Typically, airbags are designed to deploy when the speed of the automobile is above 13 mph in a frontal impact. The airbag door should meet head impact requirements for unbelted occupants involved in low speed impacts (<15mph) when airbags are not deployed. This paper describes how computer aided engineering (CAE) simulation techniques were used in improving the design of the passenger airbag door of a full size van for head impact performance. Fewer tests were conducted primarily for validation, which resulted in significantly less prototypes, costs and time.