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With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

Appropriate spray modeling in multidimensional simulations of diesel engines is well known to affect the overall accuracy of the results. More and more accurate models are being developed to deal with drop dynamics, breakup, collisions, and vaporization/multiphase processes; the latter ones being the most computationally demanding. In fact, in parallel calculations, the droplets occupy a physical region of the in-cylinder domain, which is generally very different than the topology-driven finite-volume mesh decomposition. This makes the CPU decomposition of the spray cloud severely uneven when many CPUs are employed, yielding poor parallel performance of the spray computation. Furthermore, mesh-independent models such as collision calculations require checking of each possible droplet pair, which leads to a practically intractable O(np2/2) computational cost, np being the total number of droplets in the spray cloud, and additional overhead for parallel communications.

In the present study, various risk curves for moderate-to-fatal head injury (AIS2+) were theoretically assessed by comparing model-based injury rates with field-based injury rates. This was accomplished by applying the risk curves in corresponding field models. The resulting injury rates were considered from two perspectives: aggregate (0-56 kph events) and point-estimate (higher-speed, barrier-like events). Four risk curves were studied: a HIC15-based curve from Mertz et al. (1997), a BRIC-based curve from Takhounts et al. (2011), a BrIC-based curve from Takhounts et al. (2013) and a Concussion-Correlate-based curve from Rowson et al. (2013). The field modeling pertained to adult drivers in 11-1 o'clock, towaway, full-engagement frontal crashes in the National Automotive Sampling System (NASS, calendar years = 1993-2012), and the model-year range of the passenger vehicles was 1985-2010.

Injury distributions of belted drivers in 1998-2013 model-year light passenger cars/trucks in various types of real-world frontal crashes were studied. The basis of the analysis was field data from the National Automotive Sampling System (NASS). The studied variables were injury severity (n=2), occupant body region (n=8), and crash type (n=8). The two levels of injury were moderate-to-fatal (AIS2+) and serious-to-fatal (AIS3+). The eight body regions ranged from head/face to foot/ankle. The eight crash types were based on a previously-published Frontal Impact Taxonomy (FIT). The results of the study provided insights into the field data. For example, for the AIS2+ upper-body-injured drivers, (a) head and chest injury yield similar contributions, and (b) about 60% of all the upper-body injured drivers were from the combination of the Full-Engagement and Offset crashes.

The objective of this paper focused on the modeling of an adaptive energy absorbing steering column which is the first phase of a study to develop a modeling methodology for an advanced steering wheel and column assembly. Early steering column designs often consisted of a simple long steel rod connecting the steering wheel to the steering gear box. In frontal collisions, a single-piece design steering column would often be displaced toward the driver as a result of front-end crush. Over time, engineers recognized the need to reduce the chance that a steering column would be displaced toward the driver in a frontal crash. As a result, collapsible, detachable, and other energy absorbing steering columns emerged as safer steering column designs. The safety-enhanced construction of the steering columns, whether collapsible, detachable, or other types, absorb rather than transfer frontal impact energy.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

The objective of this study was to further validate three previously-developed, age-dependent finite element models representing 35, 55, and 75 year old mid-sized males. The validation was based on comparisons with the following published tests involving post mortem human subjects: oblique thoracic and abdominal pendulum impact (4-10 m/s), oblique and lateral thoracic pendulum impact (2.5 m/s), and lateral thoracic pendulum impact (4.3 and 6.7 m/s). The responses of the models were compared to cadaveric response corridors and responses from specific cadavers similar in size and age. When compared to the cadaveric response corridors, the model responses were generally within those corridors. When compared to the responses of specific cadavers, the results were mixed. In some of the cases the model responses predicted the age-dependency of the cadaveric responses. In other cases, the model responses had the opposite trend of those of the cadavers.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash 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 impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

While seat belts are the most effective safety technology in vehicles today, there are continual efforts in the industry to improve their ability to reduce the risk of injury. In this paper, seat belt pretensioners and current trends towards more powerful systems were reviewed and analyzed. These more powerful systems may be, among other things, systems that develop higher belt forces, systems that remove slack from belt webbing at higher retraction speeds, or both. The analysis started with validation of the Ford Human Body Finite Element Model for use in evaluation of abdominal belt loading by pretensioners. The model was then used to show that those studies, done with lap-only belts, can be used to establish injury metrics for tests done with lap-shoulder belts. Then, previously performed PMHS studies were used to develop AIS 2+ and AIS 3+ injury risk curves for abdominal interaction with seat belts via logistic regression and reliability analysis with interval censoring.

FMVSS 201U, interior head impact performance is required for each new vehicle program. In the laboratory, testing to this requirement includes laying out the target locations, defining additional robustness target points based on targeting variation, positioning the Free Motion Headform (FMH), impacting each location with the headform and measuring HIC values. The tests may involve some conservative strategies and robustness studies to protect for the worst-case scenarios, where an impact might produce the highest HIC(d) within variations of impact conditions. In order to automate the best practices and procedures for both laboratory and CAE, a process automation environment was used to develop the Interior Head Impact Toolkit (IHIT, pronounced as i-hit). The IHIT software addresses several key testing processes and is grouped into four modules.

Nowadays is a common sense the importance of the CAE usage in the modern automotive industry. The ability to predict the design behavior of a project represents a competitive advantage. However, some CAE models have become so complex and detailed that, in some cases, one just can not build up the model without a considerable amount of information. In that case simplified models play an important role in the design phase, especially in pre-program stages. This work intends to build an archetypal vehicle dynamics model able to predict the rollover resistance of a vehicle design. Through the study of a more complex model, carried out in Adams environment, it was possible to identify the key degrees of freedom to be considered in the simplified model along with important elements of the suspension which are also important design factors.

Two rigid rollover test devices were constructed to have the approximate dimensions, mass and inertial properties of a mid-sized Car and Sport Utility Vehicle (SUV). The rigid devices were used to generate vehicle and occupant responses from a series of laboratory rollover tests. For each rigid rollover test, a deceleration sled was used to subject each rigid vehicle to nearly identical lateral speeds and decelerations. The rigid vehicles were limited to a single roll by tethering the vehicles to the deceleration cart. The vehicle's roll rate, roll angle, lateral acceleration and Anthropomorphic Test Devices (ATD) neck responses generated from the rigid SUV were compared to the responses of a full vehicle production SUV under similar test conditions. The rigid SUV and Car devices were then used to examine the effects of activating safety belt pre-tensioning systems and roof mounted side curtain airbags at various times on ATD neck forces and moments.

Injury to the thorax is the predominant cause of fatalities in crash-involved automobile occupants over the age of 65, and many elderly-occupant automobile fatalities occur in crashes below compliance or consumer information test speeds. As the average age of the automotive population increases, thoracic injury prevention in lower severity crashes will play an increasingly important role in automobile safety. This study presents the results of a series of sled tests to investigate the thoracic deformation, kinematic, and injury responses of belted post-mortem human surrogates (PMHS, average age 44 years) and frontal anthropomorphic test devices (ATDs) in low-speed frontal crashes. Nine 29 km/h (three PMHS, three Hybrid III 50th% male ATD, three THOR-NT ATD) and three 38 km/h (one PMHS, two Hybrid III) frontal sled tests were performed to simulate an occupant seated in the right front passenger seat of a mid-sized sedan restrained with a standard (not force-limited) 3-point seatbelt.

A theoretical math model was created to assess the net effect of aging populations versus evolving system designs from the standpoint of thoracic injury potential. The model was used to project the next twenty-five years of thoracic injuries in Canada. The choice of Canada was topical because rulemaking for CMVSS 208 has been proposed recently. The study was limited to properly-belted, front-outboard, adult occupants in 11-1 o'clock frontal crashes. Moreover, only AIS3+thoracic injury potential was considered. The research consisted of four steps. First, sub-models were developed and integrated. The sub-models were made for numerous real-world effects including population growth, crash involvement, fleet penetration of various systems (via system introduction, vehicle production, and vehicle attrition), and attendant injury risk estimation. Second, existing NASS data were used to estimate the number of AIS3+ chest-injured drivers in Canada in 2001.

Farm workers experience a very high incidence of injuries leading to physical and cognitive (strokes, TBI) disabilities. Since 1991, the AgrAbility Project 2 and its staff have provided direct assistance and education to many U.S. farmers and farm workers. If farmers, ranchers or farm workers who become disabled continue to be employed in agriculture, often their agricultural operation must be modified and/or agricultural machinery must be modified or adaptive equipment purchased to meet their new needs. Some common tractor modifications include operator lifts, hand controls, added/modified steps and handrails, automated hitches, and custom seating. Some modifications are commercially available but others are done on an individual need basis. AgrAbility staff would welcome the opportunity to work closer with farm equipment manufacturers to create modifications that would make farming and ranching easier and safer for all.

This book draws upon a variety of the author's experiences during more than 25 years in automotive safety. It gives an introduction to plain film radiographs (x-rays), computed tomograms (CTs), and magnetic resonance images (MRIs) such that vehicle safety professionals can use these techniques to help piece together the puzzle and provide a better understanding of the relationship between vehicle crash scenarios and occupant injury. For those with a primarily vehicle background, Neck Injury provides an overview of how x-rays, CTs, and MRIs may be used as a source of information to help analyze vehicle crashes and the associated injuries. For those with a clinical background, the book provides insight into how injuries relate to the vehicle crash. Chapters cover: Anatomy Imaging Injuries and Injury Mechanisms