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This study reanalyzes the data from a recent experimental report from the University of Utah investigating the effect on driving performance of auditory-vocal secondary tasks (such as cell phone and passenger conversations, speech-to-text, and a complex artificial cognitive task). The current objective is to estimate the relative risk of crashes associated with such auditory-vocal tasks. Contrary to the Utah study's assumption of an increase in crash risk from the attentional effects of cognitive load, a deeper analysis of the Utah data shows that driver self-regulation provides an effective countermeasure that offsets possible increases in crash risk. For example, drivers self-regulated their following distances to compensate for the slight increases in brake response time while performing auditory-vocal tasks. This new finding is supported by naturalistic driving data showing that cell phone conversation does not increase crash risk above that of normal baseline driving.

A key aim of research into cell phone tasks is to obtain an unbiased estimate of their relative risk (RR) for crashes. This paper re-examines five RR estimates of cell phone conversation in automobiles. The Toronto and Australian studies estimated an RR near 4, but used subjective estimates of driving and crash times. The OnStar, 100-Car, and a recent naturalistic study used objective measures of driving and crash times and estimated an RR near 1, not 4 - a major discrepancy. Analysis of data from GPS trip studies shows that people were in the car only 20% of the time on any given prior day at the same clock time they were in the car on a later day. Hence, the Toronto estimate of driving time during control windows must be reduced from 10 to 2 min.

The present investigation details an experimental procedure for frontal impact responses of a generic steel front bumper crush can (FBCC) assembly subjected to a rigid full and 40% offset impact. There is a paucity of studies focusing on component level tests with FBCCs, and of those, speeds carried out are of slower velocities. Predominant studies in literature pertain to full vehicle testing. Component level studies have importance as vehicles aim to decrease weight. As materials, such as carbon fiber or aluminum, are applied to vehicle structures, computer aided models are required to evaluate performance. A novel component level test procedure is valuable to aid in CAE correlation. All the tests were conducted using a sled-on-sled testing method. Several high-speed cameras, an IR (Infrared) thermal camera, and a number of accelerometers were utilized to study impact performance of the FBCC samples.

Previously, a 10-year-old (YO) pediatric thorax finite element model (FEM) was developed and verified against child chest stiffness data measured from clinical cardiopulmonary resuscitation (CPR). However, the CPR experiments were performed at relatively low speeds, with a maximum loading rate of 250 mm/s. Studies showed that the biomechanical responses of human thorax exhibited rate sensitive characteristics. As such, the studies of dynamic responses of the pediatric thorax FEM are needed. Experimental pediatric cadaver data in frontal pendulum impacts and diagonal belt dynamic loading tests were used for dynamic validation. Thoracic force-deflection curves between test and simulation were compared. Strains predicted by the FEM and the injuries observed in the cadaver tests were also compared for injury assessment and analysis. This study helped to further improve the 10 YO pediatric thorax FEM.

Auto racing has been in vogue from the time automobiles were first built. With the dawn of modern cars came higher engine capacities; the speeds involved in these races and crashes increased as well. However, the advent of passive restraint systems such as the helmet, HANS (Head and Neck Support device), multi-point harness system, roll cage, side and frontal crush zones, racing seats, fire retardant suits, and soft-wall technology, have greatly improved the survivability of the drivers in high-speed racing crashes. Three left lateral crashes from Begeman and Melvin (2002), Case #LAS12, #IND14 and #99TX were used as inputs to the Wayne State Human Body Model (WSHBM) in a simulated racing buck. Twelve simulations with delta-v, six-point harness and shoulder pad as design variables were analyzed for the average maximum principal strain (AMPS) in the aorta. The average AMPS for the high-speed crashes were 0.1551±0.0172 while the average maximum pressure was 110.50±4.25 kPa.

Typical automotive body structures use resistance spot welding for most joining purposes. New materials, such as Advanced High Strength Steels (AHSS) are increasingly used in the construction of automotive body structures to meet increasingly higher structural performance requirements while maintaining or reducing weight of the vehicle. One of the challenges for implementation of new AHSS materials is weldability assessment. Weld engineers and vehicle program teams spend significant efforts and resources in testing weldability of new sheet metal stack-ups. In this paper, we present a methodology to determine the weldability of sheet metal stack-ups using an Artificial Neural Network-based tool that learns from historical data. The paper concludes by reviewing weldability results predicted by using this tool and comparing with actual test results.

Commotio Cordis (CC) is the second leading cause of mortality in youth sports. Impacts occurring directly over the left ventricle (LV) during a vulnerable period of the cardiac cycle can cause ventricular fibrillation (VF), which results in CC. In order to better understand the pathophysiology of CC, and develop a mechanical model for CC, appropriate injury criteria need to be developed. This effort consisted of impacts to seventeen juvenile porcine specimens (mass 21-45 kg). Impacts were delivered over the cardiac silhouette during the venerable period of the cardiac cycle. Four impact speeds were used: 13.4, 17.9, 22.4, and 26.8 m/s. The impactor was a lacrosse ball on an aluminum shaft instrumented with an accelerometer (mass 188 g - 215 g). The impacts were recorded using high-speed video. LV pressure was measured with a catheter. Univariate binary logistic regression analyses were performed to evaluate the predictive ability of ten injury criteria.

A modified Marmarou impact acceleration injury model was developed to study the kinematics of the rat head to quantify traumatic axonal injury (TAI) in the corpus callosum (CC) and brainstem pyramidal tract (Py), to determine injury predictors and to establish injury thresholds for severe TAI. Thirty-one anesthetized male Sprague-Dawley rats (392 ± 13 grams) were impacted using a modified impact acceleration injury device from 2.25 m and 1.25 m heights. Beta-amyloid precursor protein (β-APP) immunocytochemistry was used to assess and quantify axonal changes in CC and Py. Over 600 injury maps in CC and Py were constructed in the 31 impacted rats. TAI distribution along the rostro-caudal direction in CC and Py was determined. Linear and angular responses of the rat head were monitored and measured in vivo with an attached accelerometer and angular rate sensor, and were correlated to TAI data.

It is well known that sound radiation from a rectangular panel can be significantly affected by its boundary condition. However, most of the existing investigations are primarily focused on sound radiation from plates with simply supported boundary conditions. The objective of this paper is to study the effect on sound radiation of the boundary supporting conditions generally specified in the form of discrete and/or distributed restraining springs. This will have practical implications. For example, in automotive NVH design, it is of interest to understand how the sound radiation from a body panel can be affected by the number and distribution of spot-welds. It is demonstrated through numerical examples that the distribution of spot-welds can be tuned or optimized, like other conventional design parameters, to achieve maximum sound reduction.

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.

Hat sections made of steel are frequently encountered in automotive body structural components such as front rails. These components can absorb significant amount of impact energy during collisions thereby protecting occupants of vehicles from severe injury. In the initial phase of vehicle design, it will be prudent to incorporate the sectional details of such a component based on an engineering target such as peak load, mean load, energy absorption, or total crush, or a combination of these parameters. Such a goal can be accomplished if efficient and reliable data-based models are available for predicting the performance of a section of given geometry as alternatives to time-consuming and detailed engineering analysis typically based on the explicit finite element method.

The objective of this research is to investigate the effect of the blast load on the vehicle and occupant and identify the sensitivity of the vehicle parameters to the blast load, therefore figure out the design solution to protect the vehicle and occupant. CAE explicit commercial code, LSDYNA, is applied in this research with adopting CONWEP method for the blast load. The LSDYNA 95th percentile Hybrid III dummy model is used for occupant simulation. Seat, seat belt, and underbody and underbody armor are interested areas in the design to meet the survivability and weight target. The results show the protection can be effectively achieved through employing the new design method in three areas mentioned above.

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).

Traumatic brain injury (TBI) continues to be a major health problem, with over 500,000 cases per year with a societal cost of approximately $85 billion in the US. Motor vehicle accidents are the leading cause of such injuries. In many cases of TBI widespread disruption of the axons occurs through a process known as diffuse axonal injury (DAI) or traumatic axonal injury (TAI). In the current study, an in vivo TAI model was developed using spinal nerve roots of adult rats. This model was used to determine functional and structural responses of axons to various strains and displacement rates. Fifty-six L5 dorsal nerve roots were each subjected to a predetermined strain range (<10%, 10-20% and >20%) at a specified displacement rate (0.01 mm/sec and 15 mm/sec) only once. Image analysis was used to determine actual strains on the roots during the pull.

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.

Propagation-based and phase-enhanced x-ray imaging was developed as a unique metrology technique to visualize the internal structure of high-pressure fuel injection nozzles. We have visualized the microstructures inside 200-μm fuel injection nozzles in a 3-mm-thick steel housing using this novel technique. Furthermore, this new x-ray-based metrology technique has been used to directly study the highly transient needle motion in the nozzles in situ and in real-time, which is virtually impossible by any other means. The needle motion has been shown to have the most direct effect on the fuel jet structure and spray formation immediately outside of the nozzle. In addition, the spray cone-angle has been perfectly correlated with the numerically simulated fuel flow inside the nozzle due to the transient nature of the needle during the injection.

A high carbon, high silicon and high manganese steel containing about 1% carbon, 3.0% silicon and 2.0% manganese has been developed. This steel has been synthesized using the concepts from Austempered Ductile Cast Iron (ADI) technology. The influence of austempering process on the microstructure and the room temperature mechanical properties of this steel was investigated. The influence of microstructure on the plain strain fracture toughness of this new steel was also examined. Four batches of compact tension and cylindrical tensile samples were prepared from this steel as per ASTM standards E-399 and E-8 respectively. Two batches of specimens were processed by traditional quenching and tempering process while other two batches were austempered. The microstructures were characterized by X-ray diffraction and optical metallography.

Lower extremity injuries in frontal automotive crashes usually occur with footwell intrusion where both the knee and foot are constrained. In order to identify factors associated with tibial shaft injury, a series of numerical simulations were conducted using a finite element model of the whole human body. These simulations demonstrated that tibial mid-shaft injuries in frontal crashes could be caused by an abrupt change in velocity and a high rate of footwell intrusion.

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.

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.