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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.

A series of rigid wall tests have been conducted at three impact velocities to quantify the dynamic response of the Side Impact Dummy (SID) developed by US DOT. This paper reports the chest, pelvis and head responses of the dummy at various filter frequencies and describes the development and verification of the three-dimensional mathematical model of the Side Impact Dummy utilizing the rigid wall test results. The mathematical model uses the mass distribution and the linkage system of the current Part 572, Hybrid II dummy which forms the basic platform of the SID. The unique chest of the dummy is modeled by two systems of linkages simulating the rib cage and the jacket. Also included in the model is the internal hardware of the chest, e.g. a damper, rib stopper and a clavicle simulator at the upper spine. The material and linkage models are based on static and dynamic tests of the dummy components.

This paper describes the development of a three-dimensional lumped-mass structure and dummy model to study barrier-to-car side impacts. The test procedures utilized to develop model input data are also described. The model results are compared to crash test results from a series of six barrier-to-car crash tests. Sensitivity analysis using the validated model show the necessity to account for dynamic structural rate effects when using quasi-statically measured vehicle crush data.

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension kinematics and compliance test. The correlated model was then used to simulate a J-turn vehicle dynamics test maneuver, a roll and non-roll ditch test, corkscrew ramp and a lateral trip test, the results of which are presented in this paper. The results indicate that MADYMO is able to reasonably predict the vehicle and occupant responses in these types of applications and is potentially suited as a tool to help setup a suite of vehicle configurations and test conditions for rollover sensor testing. A suspension system sensitivity study is presented for the laterally tripped non-roll event.

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.

Macroscopic constitutive behaviors of aluminum 5052-H38 honeycombs under dynamic inclined loads with respect to the out-of-plane direction are investigated by experiments. The results of the dynamic crush tests indicate that as the impact velocity increases, the normal crush strength increases and the shear strength remains nearly the same for a fixed ratio of the normal to shear displacement rate. The experimental results suggest that the macroscopic yield surface of the honeycomb specimens as a function of the impact velocity under the given dynamic inclined loads is not governed by the isotropic hardening rule of the classical plasticity theory. As the impact velocity increases, the shape of the macroscopic yield surface changes, or more specifically, the curvature of the yield surface increases near the pure compression state.

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.

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.

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.

CAE has played a key role in development of the rollover safety technology by reducing the required number of prototypes. CAE-led Design Of Experiments (DOE) studies have helped in developing the process to minimize the number of CAE runs and to optimize use of the prototypes. This paper demonstrates the use of CAE/DOE for the design and optimization of rollover vehicle prototypes and also investigates effects of various factors in the selection of vehicle configuration for rollover sensor calibration testing. The process described herein has been successfully applied to vehicle programs. Modeling and analysis guidelines are also presented for CAE engineers to help in optimizing vehicle prototypes at program level.

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.

This paper describes (1) the development of a component test methodology for testing a cooling module including radiator, condenser and trans. cooler, and (2) the associated CAE model development. A series of light truck/SUV cooling module component tests were conducted to obtain their characteristics as inputs for frontal impact and sensor modeling development. First, the cooling module component CAE sub-model was developed using soft springs along with fine-mesh sheet metal shell elements. Second, simulated sub-model results were correlated fairly well with the test data. Third, this component CAE sub-model was then incorporated into a full vehicle CAE model that was used for frontal impact (NCAP) and sensor development. Results indicated that the proposed test method for cooling module components provided consistent data and the results from cooling module sub-model can be incorporated into the full vehicle CAE model for improving the quality and accuracy of CAE models.

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.

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.

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.

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 first describes an experimental analytical approach and numerical procedures used to establish crushable foam material constants needed in finite element (FE) analysis. Dynamic compressive stress-strain data of a 2 pcf Dytherm foam, provided by ARCO Chemical, is used to determine the material parameters which appears in the foam constitutive equation. A finite element model simulating a 15 mph spherical headform impact with a foam sample 6 in. x 6 in. x 1 in. fixed against a rigid plate is developed. The predicted force-deflection characteristic is validated against test data to characterize the initial loading and final unloading stiffnesses of the foam during impact. Finite element modeling and analysis of 15 mph spherical headform impact with component sections of upper interior structures of a passenger compartment is presented.

Locations of key body segments of Hybrid III dummies used in FMVSS 208 compliance tests and NCAP tests were measured and subjected to statistical analysis. Mean clearance dimensions and their standard deviations for selected body segments of driver and passenger occupants with respect to selected vehicle surfaces were determined for several classes of vehicles. These occupant locations were then investigated for correlation with impact responses measured in crash tests and by using a three dimensional human-dummy mathematical model in comparable settings. Based on these data, the importance of some of the clearance dimensions between the dummy and the vehicle surfaces was determined. The study also compares observed Hybrid III dummy positions within selected vehicles with real world occupant positions reported in published literature.

This paper describes the steps and procedures involved in the development, calibration, and validation of a finite element model of a deformable featureless headform (Hybrid III head without nose). Development efforts included: a headform scan to verify geometric accuracy, quantification of general-purpose construction of the finite element model from the scanned data, viscoelastic parameters for the constitutive model definition of the headform skin, and models of drop tests with impact speeds of 9.775, 14.484, 19.312, and 24.140 km/h (6.074, 9, 12, and 15 mph). The predictions of all pertinent headform responses during the calibration were in excellent agreement with related experiments. The validity of the headform model and the headform impact methodology were verified in both component and full vehicle environments. This was accomplished through comparisons of finite element simulations with tests of the headform responses at 24.140 km/h (15 mph) impact.

Many foams exhibit significant strain rate dependency in their mechanical responses. To characterize these foams, a strain rate dependent constitutive model is formulated and implemented in an explicit dynamic finite element code developed at FORD. The constitutive model is developed in conjunction with a Lagrangian eight node solid element with twenty four degrees of freedom. The constitutive model has been used to model foams in a number crash analysis problems. Results obtained from the analyses are compared to the experimental data. Evidently, numerical results show excellent agreement with the experimental data.