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The objective of this study was to optimize the occupant restraint systems for a light tactical vehicle in frontal crashes. A combination of sled testing and computational modeling were performed to find the optimal seatbelt and airbag designs for protecting occupants represented by three size of ATDs and two military gear configurations. This study started with 20 sled frontal crash tests to setup the baseline performance of existing seatbelts, which have been presented previously; followed by parametric computational simulations to find the best combinations of seatbelt and airbag designs for different sizes of ATDs and military gear configurations involving both driver and passengers. Then 12 sled tests were conducted with the simulation-recommended restraint designs. The test results were further used to validate the models. Another series of computational simulations and 4 sled tests were performed to fine-tune the optimal restraint design solutions.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Among all the vehicle rollover test procedures, the SAE J2114 dolly rollover test is the most widely used. However, it requires the test vehicle to be seated on a dolly with a 23° initial angle, which makes it difficult to test a vehicle over 5,000 kg without a dolly design change, and repeatability is often a concern. In the current study, we developed and implemented a new dynamic rollover test methodology that can be used for evaluating crashworthiness and occupant protection without requiring an initial vehicle angle. To do that, a custom cart was designed to carry the test vehicle laterally down a track. The cart incorporates two ramps under the testing vehicle’s trailing-side tires. In a test, the cart with the vehicle travels at the desired test speed and is stopped by a track-mounted curb.

Occupant stature and body shape may have significant effects on injury risks in motor vehicle crashes, but the current finite element (FE) human body models (HBMs) only represent occupants with a few sizes and shapes. Our recent studies have demonstrated that, by using a mesh morphing method, parametric FE HBMs can be rapidly developed for representing a diverse population. However, the biofidelity of those models across a wide range of human attributes has not been established. Therefore, the objectives of this study are 1) to evaluate the accuracy of HBMs considering subject-specific geometry information, and 2) to apply the parametric HBMs in a sensitivity analysis for identifying the specific parameters affecting body responses in side impact conditions. Four side-impact tests with two male post-mortem human subjects (PMHSs) were selected to evaluate the accuracy of the geometry and impact responses of the morphed HBMs.

We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers’ head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset.

Seat comfort is driven in part by the fit between the sitter and seat. Traditional anthropometric data provide little information about the size and shape of the torso that can be used for backrest design. This study introduces a methodology for using three-dimensional computer models of the human torso based on a statistical analysis of body shapes for conducting automated fit assessments. Surface scan data from 296 men and 417 women in a seated posture were analyzed to create a body shape model that can be adjusted to a range of statures, body shape, and postures spanning those typical of vehicle occupants. Finite-element models of two auto seat surface were created, along with custom software that generates body models and postures them in the seat. A simple simulation technique was developed to rapidly assess the fit of the torso relative to the seat back.

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.

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.

Complete validation of any finite element (FE) model of the human brain is very difficult due to the lack of adequate experimental data. However, more animal brain injury data, especially rat data, obtained under well-defined mechanical loading conditions, are available to advance the understanding of the mechanisms of traumatic brain injury. Unfortunately, internal response of the brain in these experimental studies could not be measured. The aim of this study was to develop a detailed FE model of the rat brain for the prediction of intracranial responses due to different impact scenarios. Model results were used to elucidate possible brain injury mechanisms. An FE model, consisting of more than 250,000 hexahedral elements with a typical element size of 100 to 300 microns, was developed to represent the brain of a rat. The model was first validated locally against peak brain deformation data obtained from nine unique dynamic cortical deformation (vacuum) tests.

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.

Although biomechanical studies on the knee-thigh-hip (KTH) complex have been extensive, interactions between the KTH and various vehicular interior design parameters in frontal automotive crashes for newer models have not been reported in the open literature to the best of our knowledge. A 3D finite element (FE) model of a 50th percentile male KTH complex, which includes explicit representations of the iliac wing, acetabulum, pubic rami, sacrum, articular cartilage, femoral head, femoral neck, femoral condyles, patella, and patella tendon, has been developed to simulate injuries such as fracture of the patella, femoral neck, acetabulum, and pubic rami of the KTH complex. Model results compared favorably against regional component test data including a three-point bending test of the femur, axial loading of the isolated knee-patella, axial loading of the KTH complex, axial loading of the femoral head, and lateral loading of the isolated pelvis.

Several three-dimensional (3D) finite element (FE) models of the human body have been developed to elucidate injury mechanisms due to automotive crashes. However, these models are mainly focused on 50th percentile male. As a first step towards a better understanding of injury biomechanics in the small female, a 3D FE model of a 5th percentile female human chest (FEM-5F) has been developed and validated against experimental data obtained from two sets of frontal impact, one set of lateral impact, two sets of oblique impact and a series of ballistic impacts. Two previous FE models, a small female Total HUman Model for Safety (THUMS-AF05) occupant version 1.0ϐ (Kimpara et al., 2002) and the Wayne State University Human Thoracic Model (WSUHTM, Wang 1995 and Shah et al., 2001) were integrated and modified for this model development.

Cerebral blood vessels are an integral part of the brain and may play a role in the response of the brain to impact. The purpose of this study was to quantify the effects of surrogate vessels on the deformation patterns of a physical model of the brain under various impact conditions. Silicone gel and tubing were used as surrogates for brain tissue and blood vessels, respectively. Two aluminum cylinders representing a coronal section of the brain were constructed. One cylinder was filled with silicone gel only, and the other was filled with silicone gel and silicone tubing arranged in the radial direction in the peripheral region. An array of markers was embedded in the gel in both cylinders to facilitate strain calculation via high-speed video analysis. Both cylinders were simultaneously subjected to a combination of linear and angular acceleration using a two-segment pendulum.

Typical automotive related abdominal injuries occur due to contact with the rim of the steering wheel, seatbelt and armrest, however, the rate is less than in other body regions. When solid abdominal organs, such as the liver, kidneys and spleen are involved, the injury severity tends to be higher. Although sled and pendulum impact tests have been conducted using cadavers and animals, the mechanical properties and the tissue level injury tolerance of abdominal solid organs are not well characterized. These data are needed in the development of computer models, the improvement of current anthropometric test devices and the enhancement of our understanding of abdominal injury mechanisms. In this study, a series of experimental tests on solid abdominal organs was conducted using porcine liver, kidney and spleen specimens. Additionally, the injury tolerance of the solid organs was deduced from the experimental data.

Brain tissue architecture consists of a complex network of neurons and vasculature interspersed within a matrix of supporting cells. The role of the relatively suffer blood vessels on the more compliant brain tissues during rapid loading has not been properly investigated. Two 2-D finite element models of the human head were developed. The basic model (Model I) consisted of the skull, dura matter, cerebral spinal fluid (CSF), tentorium, brain tissue and the parasagittal bridging veins. The pia mater was also included but in a simplified form which does not correspond to the convolutions of the brain. In Model II, major branches of the cerebral arteries were added to Model I. Material properties for the brain tissues and vasculature were taken from those reported in the literature. The model was first validated against intracranial pressure and brain/skull relative motion data from cadaveric tests.

Aortic injuries during blunt thoracic impacts can lead to life threatening hemorrhagic shock and potential exsanguination. Experimental approaches designed to study the mechanism of aortic rupture such as the testing of cadavers is not only expensive and time consuming, but has also been relatively unsuccessful. The objective of this study was to develop a computer model and to use it to predict modes of loading that are most likely to produce aortic ruptures. Previously, a 3D finite element model of the human thorax was developed and validated against data obtained from lateral pendulum tests. The model included a detailed description of the heart, lungs, rib cage, sternum, spine, diaphragm, major blood vessels and intercostal muscles. However, the aorta was modeled as a hollow tube using shell elements with no fluid within, and its material properties were assumed to be linear and isotropic.

The Lower Limb Model for Safety (LLMS) is a finite element model of the lower limb developed mainly for safety applications. It is based on a detailed description of the lower limb anatomy derived from CT and MRI scans collected on a subject close to a 50th percentile male. The main anatomical structures from ankle to hip (excluding the hip) were all modeled with deformable elements. The modeling of the foot and ankle region was based on a previous model Beillas et al. (1999) that has been modified. The global validation of the LLMS focused on the response of the isolated lower leg to axial loading, the response of the isolated knee to frontal and lateral impact, and the interaction of the whole model with a Hybrid III model in a sled environment, for a total of nine different set-ups. In order to better characterize the axial behavior of the lower leg, experiments conducted on cadaveric tibia and foot were reanalyzed and experimental corridors were proposed.

Finite element models of human body segments have been developed in recent years. Numerical simulation could be helpful when understanding injury mechanisms and to make injury assessments. In the lower leg injury research in NISSAN, a finite element model of the human ankle/foot is under development. The mesh for the bony part was taken from the original model developed by Beaugonin et al., but was revised by adding soft tissue to reproduce realistic responses. Damping effect in a high speed contact was taken into account by modeling skin and fat in the sole of the foot. The plantar aponeurosis tendon was modeled by nonlinear bar elements connecting the phalanges to the calcaneus. The rigid body connection, which was defined at the toe in the original model for simplicity, was removed and the transverse ligaments were added instead in order to bind the metatarsals and the phalanges. These tendons and ligaments were expected to reproduce a realistic response in compression.