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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.

An evaluation of the four injury risk curves proposed in the NHTSA NCAP for estimating the risk of AIS≻=3 injuries to the head, neck, chest and AIS≻=2 injury to the Knee-Thigh-Hip (KTH) complex has been conducted. The predicted injury risk to the four body regions based on driver dummy responses in over 300 frontal NCAP tests were compared against those to drivers involved in real-world crashes of similar severity as represented in the NASS. The results of the study show that the predicted injury risks to the head and chest were slightly below those in NASS, and the predicted risk for the knee-thigh-hip complex was substantially below that observed in the NASS. The predicted risk for the neck by the Nij curve was greater than the observed risk in NASS by an order of magnitude due to the Nij risk curve predicting a non-zero risk when Nij = 0. An alternative and published Nte risk curve produced a risk estimate consistent with the NASS estimate of neck injury.

The URGENCY algorithm uses data from on-board crash recorders to assist in identifying crashes that are most likely to have time critical (compelling) injuries. The injury risks projected by using the NASS/CDS data are the basis for the URGENCY algorithm. This study applied the algorithm retrospectively to a population of injured occupants in the database from the University of Miami School of Medicine, William Lehman Injury Research Center (WLIRC). The population selected was adult occupants in frontal crashes that were protected by three-point belts plus an air bag. For the cases with greater than 50% predicted MAIS 3+ injury probability, 96% of the occupants in the study had MAIS 3+ injuries. For the cases with less than 10% predicted MAIS 3+ injury probability, 63% did not have MAIS 3+ injuries. Most of the of MAIS 3+ injuries not predicted involved injuries in multiple impact crashes, pole crashes or close-in occupants injured by air bag deployment.

The objective of the present study is to develop a better understanding of the reasons for airbag non-deployment in frontal crashes that produce serious injuries. The FARS data shows an increasing trend of fatal crashes involving airbag non-deployment with a higher fatality risk in recent model year vehicles. The reported number of fatalities in such crashes has increased by about 50 percent (from 500 per year to 780 per year) in the last five years. The percentage of fatalities with non-deployments has doubled in vehicles model year 1998 and later compared to earlier model years. Multiple impacts contribute to about 90 percent of the FARS frontal crashes with non-deployments. Crashes with a curb hit or guardrail impact as the first harmful event and a narrow impact crash with a tree or pole as a subsequent harmful event is the most frequent crash scenario in non-deployment related fatal crashes.

In a side impact, the occupants on both the struck, or near side, of the vehicle and the occupants on the opposite, or far side, of the vehicle are at risk of injury. Since model year 1997, all passenger cars in the U.S. have been required to comply with FMVSS No. 214, a safety standard that mandates a minimum level of side crash protection for near side occupants. No such federal safety standard exists for far side occupants. The mechanism of far side injury is believed to be quite different than the injury mechanism for near side injury. Far side impact protection may require the development of different countermeasures than those which are effective for near side impact protection. This paper evaluates the risk of side crash injury for far side occupants as a basis for developing far side impact injury countermeasures. Based on the analysis of NASS/CDS 1993–2002, this study examines the injury outcome of over 4500 car, light truck, and van occupants subjected to far side impact.

Currently, three-dimensional finite element models of the human body have been developed for frequently injured anatomical regions such as the brain, chest, extremities and pelvis. While a few models of the human body include the abdomen, these models have tended to oversimplify the complexity of the abdominal region. As the first step in understanding abdominal injuries via numerical methods, a 3D finite element model of a 50th percentile male human abdomen (WSUHAM) has been developed and validated against experimental data obtained from two sets of side impact tests and a series of frontal impact tests. The model includes a detailed representation of the liver, spleen, kidneys, spine, skin and major blood vessels.

Previous studies have hypothesized that the shoulder may be used to absorb some impact energy and reduce chest injury due to side impacts. Before this hypothesis can be tested, a good understanding of the injury mechanisms and the kinematics of the shoulder is critical for occupant protection in side impact. However, existing crash dummies and numerical models are not designed to reproduce the kinematics and kinetics of the human shoulder. The purpose of this study was to develop a finite element model of the human shoulder in order to achieve a deeper understanding of the injury mechanisms and the kinematics of the shoulder in side impact. Basic anthropometric data of the human shoulder used to develop the skeletal and muscular portions of this model were taken from commercial data packages. The shoulder model included three bones (the humerus, scapula and clavicle) and major ligaments and muscles around the shoulder.

The principal focus of this study was the measurement of relative brain motion with respect to the skull using a high-speed, biplanar x-ray system and neutral density targets (NDTs). A suspension fixture was used for testing of inverted, perfused, human cadaver heads. Each specimen was subjected to multiple tests, either struck at rest using a 152-mm-diameter padded impactor face, or stopped against an angled surface from steady-state motion. The impacts were to the frontal and occipital regions. An array of multiple NDTs was implanted in a double-column scheme of 5 and 6 targets, with 10 mm between targets in each column and 80 mm between columns. These columns were implanted in the temporoparietal and occipitoparietal regions. The impacts produced peak resultant accelerations of 10 to 150 g, and peak angular accelerations between 1000 and 8000 rad/s2. For all but one test, the peak angular speeds ranged from 17 to 22 rad/s.

Most studies of pedestrian injuries focus on reducing traumatic injuries due to the primary impact between the vehicle and the pedestrian. However, based on the Pedestrian Crash Data Study (PCDS), some researchers concluded that one of the leading causes of head injury for pedestrian crashes can be attributed to the secondary impact, defined as the impact of the pedestrian with the ground after the primary impact of the pedestrian with the vehicle. The purpose of this study is to understand if different vehicle front-end profiles can affect the risk of pedestrian secondary head impact with the ground and thus help in reducing the risk of head injury during secondary head impact with ground. Pedestrian responses were studied using several front-end profiles based off a mid-size vehicle and a SUV that have been validated previously along with several MADYMO pedestrian models.

Relative motion between the brain and skull may explain many types of brain injury such as intracerebral hematomas due to bridging veins rupture [1] and cerebral contusions. However, no experimental methods have been developed to measure the magnitude of this motion. Consequently, relative motion between the brain and skull predicted by analytical tools has never been validated. In this study, radio opaque markers were placed in the skull and neutral density markers were placed in the brain in two vertical columns in the occipitoparietal and temporoparietal regions. A bi-planar, high-speed x-ray system was used to track the motion of these markers. Due to limitations in current technology to record the x-ray image on high-speed video cameras, only low- speed (﹤ 4m/s) impact data were available.

In a previous study by Demetropoules et al., (1998), it was shown that both cadaveric and Hybrid III lumbar spines exhibit loading rate dependency when loaded in a quasi-static mode up to a velocity of 100 mm/s. In these tests, the Hybrid III lumbar spines were generally found to have higher stiffnesses than the human lumbar spines, except in compression. This is probably due to the fact that muscle loading was not simulated when testing the human spines. Additionally, the speed previously used to test the spines was less than that typically seen in automotive crash environment. The purpose of this study was to use a high-rate testing machine to establish the flexion and extension stiffnesses of the human lumbar spine with simulated extensor muscle tone. Two Hybrid III lumbar spines were used to develop the test methodology and to obtain the response of the Hybrid III lumbar spines.

Although not life threatening in most cases, victims of lower extremity injuries frequently end up living with a poor quality of life. The implementations of airbag supplement restraint systems significantly reduce the incidence of head and chest injuries. However, the frequency of leg injuries remains high. Several finite element models of the foot and ankle have been developed to further the understanding of this injury mechanism. None of those models employed accurate geometry among various bony segments. The objective of this study is to develop a foot and ankle finite element model based on CT scan data so that joint geometry can be accurately represented. The model was validated against experimental data for several different configurations including typical car crash situations.

Knee injuries represent about 10% of all injuries suffered during car crashes. Efforts to assess the injury risk to the posterior cruciate ligament (PCL) have been based on a study available in the literature (Viano et al., 1978), in which only two of the five knees tested had PCL ruptures. The aims of the current study were to repeat the study with a higher number of samples, study the effects of other soft tissues on knee response, and assess the adequacy of the experimental setup for the identification of a PCL tolerance. A total of 14 knees were tested using a high-speed materials testing machine. Eight were intact knees (with the patella and all the muscular and ligamentous structures), three were PCL-only knees (patella and all the muscular and ligamentous structures other than the PCL removed), and the last three were PCL-only knees with the tibia protected from bending fracture.

There has been much debate over “whiplash”-induced temporomandibular joint (TMJ) dysfunction following low-speed, rear-end automobile collisions. While several authors have reported TMJ injury based on case studies post collision, there has been little biomechanical evidence showing that rear-end impact was the primary cause of such injury. The purpose of this study was to measure the relative translation between the upper and lower incisors in cadavers subjected to low-speed, rear-end impacts. High-speed x-ray images used for this analysis were reported previously for the analysis of cadaveric cervical spine kinematics during low-speed, rear-end impacts. The cadavers were positioned at various seatback angles and body postures, producing an overall picture of various seating scenarios.

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.

This study characterizes the response of the human cadaver abdomen to high-speed seatbelt loading using pyrotechnic pretensioners. A test apparatus was developed to deliver symmetric loading to the abdomen using a seatbelt equipped with two low-mass load cells. Eight subjects were tested under worst-case scenario, out-of-position (OOP) conditions. A seatbelt was placed at the level of mid-umbilicus and drawn back along the sides of the specimens, which were seated upright using a fixed-back configuration. Penetration was measured by a laser, which tracked the anterior aspect of the abdomen, and by high-speed video. Additionally, aortic pressure was monitored. Three different pretensioner designs were used, referred to as system A, system B and system C. The B and C systems employed single pretensioners. The A system consisted of two B system pretensioners. The vascular systems of the subjects were perfused.

High-speed biplane x-ray and neutral density targets were used to examine brain displacement and deformation during impact. Relative motion, maximum principal strain, maximum shear strain, and intracranial pressure were measured in thirty-five impacts using eight human cadaver head and neck specimens. The effect of a helmet was evaluated. During impact, local brain tissue tends to keep its position and shape with respect to the inertial frame, resulting in relative motion between the brain and skull and deformation of the brain. The local brain motions tend to follow looping patterns. Similar patterns are observed for impact in different planes, with some degree of posterior-anterior and right-left symmetry. Peak coup pressure and pressure rate increase with increasing linear acceleration, but coup pressure pulse duration decreases. Peak average maximum principal strain and maximum shear are on the order of 0.09 for CFC 60 Hz data for these tests.

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. However, the mechanical properties of the pia-arachnoid complex and its influence on the overall response of the brain have not been well characterized. Consequently, finite element (FE) brain models have tended to oversimplify the response of the pia-arachnoid complex, possibly resulting in a loss of accuracy in the model predictions. The aim of this study was to determine, experimentally, the material properties of the pia-arachnoid complex under quasi-static and dynamic loading conditions. Specimens of the pia-arachnoid complex were obtained from the parietal and temporal regions of freshly slaughtered bovine subjects with the specimen orientation recorded. Single-stroke, uniaxial quasi-static and dynamic tensile experiments were performed at strain-rates of 0.05, 0.5, 5 and 100 s-1 (n = 10 for each strain rate group).

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.