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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.

The National Highway Traffic Safety Administration (NHTSA) published a Request for Comments (RFC) on proposed changes to the New Car Assessment Program (NCAP) in 2015 and 2017. One potential change was the introduction of a frontal Oblique Impact (OI) crash test. The Test device for Human Occupant Restraint (THOR) in the front left seat was used in the proposed OI test. The motivations behind the current study were a) determine if OI sled tests can be simplified, b) study the sensitivity of the THOR chest deflection to the shoulder belt layout in OI and c) assess the NHTSA-proposed THOR thoracic injury risk curves. In the current study, eleven oblique sled impact tests were conducted. The environment was representative of a generic mid-sized sedan. The buck was mounted on a rigid plate that allowed the pre-test rotation of the buck relative to the sled axis. A generic mid-sized OI pulse was used. The pulse was applied in the longitudinal direction of the sled.

An eight-group taxonomy was created to classify real-world frontal crashes from the Crashworthiness Data System (CDS) component of the National Automotive Sampling System (NASS). Three steps were taken to develop the taxonomy: (1) frontal-impact towaway crashes were identified by examining 1985-2005 model year light passenger vehicles with Collision Deformation Classification (CDC) data from the 1995-2005 calendar years of NASS; (2) case reviews, engineering judgments, and categorization assessments were conducted on these data to produce the eight-group taxonomy; and (3) two subsets of the NASS dataset were analyzed to assess the consistency of the resulting taxonomic-group frequencies. “Full-engagement” and “Offset” crashes were the most frequent crash types, each contributing approximately 33% to the total. The group identified as “D, Y, Z No-Rail” was the most over-represented crash type for vehicles with at least one seriously-injured occupant.

This study demonstrates the use of pressure sensing technology to predict the crash severity of frontal impacts. It presents an investigation of the pressure change in the front structural elements (bumper, crush cans, rails) during crash events. A series of subsystem tests were conducted in the laboratory that represent a typical frontal crash development series and provided empirical data to support the analysis of the concept. The pressure signal energy at different sensor mounting locations was studied and design concepts were developed for amplifying the pressure signal. In addition, a pressure signal processing methodology was developed that relies on the analysis of the air flow behavior by normalizing and integrating the pressure changes. The processed signal from the pressure sensor is combined with the restraint control module (RCM) signals to define the crash severity, discriminate between the frontal crash modes and deploy the required restraint devices.

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.

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.

This study deals with passenger side restraint system design for frontal impact and four impact modes are considered in optimization. The objective is to minimize the Relative Risk Score (RRS), defined by the National Highway Traffic Safety Administration (NTHSA)'s New Car Assessment Program (NCAP). At the same time, the design should satisfy various injury criteria including HIC, chest deflection/acceleration, neck tension/compression, etc., which ensures the vehicle meeting or exceeding all Federal Motor Vehicle Safety Standard (FMVSS) No. 208 requirements. The design variables include airbag firing time, airbag vent size, inflator power level, retractor force level. Some of the restraint feature options (e.g., some specific features on/off) are also considered as discrete design variables. Considering the local variability of input variables such as manufacturing tolerances, the robustness and reliability of nominal designs were also taken into account in optimization process.

Optimization of heavy materials like steel, in order to create a lighter vehicle, it is a major goal among most automakers, since heavy vehicles simply cannot compete with a lightweight model's fuel economy. Thinking this way, this paper shows a case study where the Size Optimization technique is applied to a front floor reinforcement. The reinforcement is used by two different vehicles, a subcompact and a crossover Sport Utility Vehicle (SUV), increasing the problem complexity. The Size Optimization technique is supported by Finite Element Method (FEM) tools. FEM in Computer Aided Engineering (CAE) is a numerical method for solving engineering problems, and its use can help to optimize prototype utilization and physical testing.

This study examines the biofidelity, repeatability, and reproducibility of various anthropomorphic devices in rear impacts. The Hybrid III, the Hybrid III with the RID neck, and the TAD-50 were tested in a rigid bench condition in rear impacts with ΔVs of 16 and 24 kph. The results of the tests were then compared to the data of Mertz and Patrick[1]. At a AV of 16 kph, all three anthropomorphic devices showed general agreement with Mertz and Patrick's data [1]. At a AV of 24 kph, the RID neck tended to exhibit larger discrepancies than the other two anthropomorphic devices. Also, two different RID necks produced significantly different moments at the occipital condyles under similar test conditions. The Hybrid III and the Hybrid III with the RID neck were also tested on standard production seats in rear impacts for a AV of 8 kph. Both the kinematics and the occupant responses of the Hybrid III and the Hybrid III with the RID neck differed from each other.

Head restraint has become an important element in seat design due to the severity of neck injuries in rear-end collisions. The objective of this paper is to present an analytical and efficient approach to assist engineers in analyzing the design parameters of the seat and head restraint system. The CAE simulation models with Bio-RID dummy were assembled to correlate to 10 mph rear impact sled tests. The correlated models were then adopted in Design of Experiment (DOE) studies to explore all the significant design parameters influencing occupant neck injuries. Based on the results from the DOE studies, we are able to improve the seat and head restraint designs for reducing the risk of neck injuries in rear-end impacts.

This paper examines the neck tension force (Fz) of the BioRid II dummy in the IIHS (Insurance Institute of Highway Safety) rear impact mode. The kinematics of the event is carefully reviewed, followed by a detailed theoretical analysis, paying particular attention to the upper neck tension force. The study reveals that the neck tension should be approximately 450N due to the head inertia force alone. However, some of the tests conducted by IIHS had neck tension forces as high as 1400N. The theory of head hooking and torso downward pulling is postulated in the paper, and various publicly available IIHS rear impact tests are examined against the theory. It is found in the analysis that in many of those tests with high neck tension forces, the locus of the head restraint reaction force travels on the dummy's skull cap, and eventually moves down underneath the skull cap, which causes “hooking” of the head on the stacked-up head restraint foam.

In this study, the occupant containment characteristics of automotive laminated safety glass in side window applications was evaluated through two full-scale, full-vehicle dolly rollover crash tests. The dolly rollover crash tests were performed on sport utility vehicles equipped with heat-strengthened laminated safety glass in the side windows in order to: (1) evaluate the capacity of laminated side window safety glass to contain unrestrained occupants during rollover, (2) analyze the kinematics associated with unrestrained occupants during glazing interaction and ejection, and (3) to identify laminated side window safety glass failure modes. Dolly rollovers were performed on a 1998 Ford Expedition and a 2004 Volvo XC90 at a nominal speed of 43 mph, with unbelted Hybrid II Anthropomorphic Test Devices (ATDs) positioned in the outboard seating positions.

With the increasing demand for safety, energy saving and emission reduction, Advanced High Strength Steels (AHSS) have become very attractive materials for automobile makers. Welding of AHSS remains one of the technical challenges in the successful application of AHSS in automobile structures, especially when durability of the welded structures is required. In this study, 2.0 mm uncoated DP780 was investigated. GMAW welding parameters for lap joints of this steel were developed in order to obtain different weld geometries defined by weld toe angle, weld leg sizes, and weld penetration. Metallurgical properties of the joints were evaluated using optical microscopy and scanning electron microscopy (SEM). Static and fatigue tests were conducted on the welded joints. Effect of weld geometry and HAZ softening on fatigue performance including fatigue life, crack initiation site and propagation path of the joints will be analyzed.

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.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

A comparison of the 50th percentile male THOR-LX and Hybrid III 50th percentile male dummy lower leg was conducted via component and full scale barrier testing. In the component tests, isolated THOR-LX and Hybrid III lower legs were impacted in two different test set-ups where the tibia was impacted at three different impact points. The foot without a shoe was impacted in two different test set-ups at six different impact points. A shoe impact study was also conducted to determine the effect of a shoe on the results and to determine how many impacts a shoe can withstand at each point before properties of the shoe begin to change. For these tests, the THOR-LX and Hybrid III lower legs were repeatedly impacted at four different points on the foot with a shoe. For the full scale barrier testing, the THOR-LX or Hybrid III lower legs were attached to a belted Hybrid III 50th percentile male dummy. The dummy was positioned in a compact car for each test.

This study applies a detailed finite element model of the human body to simulate occupant knee impacts experienced in vehicular frontal crashes. The human body model includes detailed anatomical features of the head, neck, chest, thoracic and lumbar spine, abdomen, and lower and upper extremities. The material properties used in the model for each anatomic part of the human body were obtained from test data reported in the literature. The total human body model used in the current study has been previously validated in frontal and side impacts. Several cadaver knee impact tests representing occupants in a frontal impact condition were simulated using the previously validated human body model. Model impact responses in terms of force-time and acceleration-time histories were compared with test results. In addition, stress distributions of the patella, femur, and pelvis were reported for the simulated test conditions.

Automotive manufacturing presents unique challenges for ergonomic analysis. The variety of tasks and frequencies are typically not seen in other industries. Moving these challenges into the realm of digital human modeling poses new challenges and offers the opportunity to create and enhance tools brought over from the traditional reactive approach. Chiang et al. (2006) documented an enhancement to the Siemen's Jack Static Strength Prediction tool. This paper will document further enhancements to the ErgoSolver (formerly known as the Ford Static Strength Prediction Solver).

Assembly operators are rarely observed performing one-handed tasks where the unutilized hand is entirely inactive. Therefore, this study was designed to determine the forces applied to supporting hands, by automotive assembly operators, during common one-handed tasks such as hose installations or electrical connections. The data were computed as a percentage of body weight and a repeated measures analysis of variance (ANOVA) (p<0.05) was conducted. Supporting hand forces were observed to range from 5.5% to 12.1% of body mass across a variety of tasks. The results of this study can be used to account for these supporting hand forces when performing a biomechanical/ergonomic analysis.