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Abstract Compared to other age groups, older adults are at more significant risk of hip fracture when they fall. In addition to the higher risk of falls for the elderly, fear of falls can reduce this population’s outdoor activity. Various preventive solutions have been proposed to reduce the risk of hip fractures ranging from wearable hip protectors to indoor flooring systems. A previously developed rubberized asphalt mixture demonstrated the potential to reduce the risk of head injury. In the current study, the capability of the rubberized asphalt sample was evaluated for the risk of hip fracture for an average elderly male and an average elderly female. A previously developed human body model was positioned in a fall configuration that would give the highest impact forces toward regular asphalt.

Abstract In this study, a novel assessment approach of in-vehicle speech intelligibility is presented using psychometric curves. Speech recognition performance scores were modeled at an individual listener level for a set of speech recognition data previously collected under a variety of in-vehicle listening scenarios. The model coupled an objective metric of binaural speech intelligibility (i.e., the acoustic factors) with a psychometric curve indicating the listener’s speech recognition efficiency (i.e., the listener factors). In separate analyses, two objective metrics were used with one designed to capture spatial release from masking and the other designed to capture binaural loudness. The proposed approach is in contrast to the traditional approach of relying on the speech recognition threshold, the speech level at 50% recognition performance averaged across listeners, as the metric for in-vehicle speech intelligibility.

Abstract Computational and experimental studies have been undertaken to investigate injurious head-first impacts (HFI), which can occur during automotive rollovers. Recent studies assume a torso surrogate mass (TSM) boundary condition, wherein the first or first two thoracic vertebrae are potted and constrained to only move in the vertical loading direction. The TSM boundary condition has not been compared with a full body (FB) model computationally or experimentally for HFI. In this study, the Global Human Body Models Consortium 50th percentile male detailed human body model (M50-O, Version 6.0) was applied to compare the kinematic, kinetic, and injury response of an HFI with a TSM boundary condition (M50-TSM), and a full body boundary condition (M50-FB). Impacts (to M50-TSM and M50-FB) were simulated between the head and a rigid plate using a commercial FE code (LS-DYNA).

Abstract Rib fractures are associated with high rates of morbidity and mortality. Improved methods to assess rib bone quality are needed to identify at-risk populations. Quantitative computed tomography (QCT) can be used to calculate volumetric bone mineral density (vBMD) and bone mineral content (BMC), which may be related to rib fracture risk. The objective of this study was to determine if vBMD and BMC from QCT predict human rib structural properties. 127 mid-level (5th–7th) ribs were obtained from adult female (n = 67) and male (n = 60) postmortem human subjects (PMHS). Isolated rib QCT scans were performed to calculate vBMD and BMC.

Abstract Traumatic brain injury is a leading cause of global death and disability. Clinically relevant large animal models are a vital tool for understanding the biomechanics of injury, providing validation data for computation models, and advancing clinical translation of laboratory findings. It is well-established that large angular accelerations of the head can cause TBI, but the effect of head impact on the extent and severity of brain pathology remains unclear. Clinically, most TBIs occur with direct head impact, as opposed to inertial injuries where the head is accelerated without direct impact. There are currently no active large animal models of impact TBI. Sheep may provide a valuable model for studying TBI biomechanics, with relatively large brains that are similar in structure to that of humans. The aim of this project is to develop an ovine model of impact TBI to study the relationships between impact mechanics and brain pathology.

Abstract Objective: This study aimed to optimize restraint systems and improve safety equity by using parametric human body models (HBMs) and vehicle models accounting for variations in occupant size and shape as well as vehicle type. Methodology: A diverse set of finite element (FE) HBMs were developed by morphing the GHBMC midsize male simplified model into statistically predicted skeleton and body shape geometries with varied age, stature, and body mass index (BMI). A parametric vehicle model was equipped with driver, front passenger, knee, and curtain airbags along with seat belts with pretensioner(s) and load limiter and has been validated against US-NCAP results from four vehicles (Corolla, Accord, RAV4, F150). Ten student groups were formed for this study, and each group picked a vehicle model, occupant side (driver vs. passenger), and an occupant model among the 60 HBMs.

Eighteen research posters were prepared and presented by student authors at the 18th Annual Injury Biomechanics Symposium. The posters covered a wide breadth of works-in-progress and recently completed projects.

Abstract Letter from the Special Issue Editors

Abstract In this study, a parametric thoracic spine (T-spine) model was developed to account for morphological variations among the adult population. A total of 84 CT scans were collected, and the subjects were evenly distributed among age groups and both sexes. CT segmentation, landmarking, and mesh morphing were performed to map a template mesh onto the T-spine vertebrae for each sampled subject. Generalized procrustes analysis (GPA), principal component analysis (PCA), and linear regression analysis were then performed to investigate the morphological variations and develop prediction models. A total of 13 statistical models, including 12 T-spine vertebrae and a spinal curvature model, were combined to predict a full T-spine 3D geometry with any combination of age, sex, stature, and body mass index (BMI). A leave-one-out root mean square error (RMSE) analysis was conducted for each node of the mesh predicted by the statistical model for every T-spine vertebra.

Abstract Introduction: The use of less lethal impact munitions (LLIMs) by law enforcement has increased in frequency, especially following nationwide protests regarding police brutality and racial injustice in the summer of 2020. There are several reports of the projectiles causing severe injuries when they penetrate the skin including pulmonary contusions, bone fractures, liver lacerations, and, in some cases, death. The penetration threshold of skin in different body regions is due to differences in the underlying structure (varying degree of muscle, adipose tissue, and presence or absence of bone). Objective: The objective of this study was to further investigate what factors affected the likelihood of skin penetration in various body regions and to develop corresponding penetration risk curves.

Abstract Compressive impacts on the cervical spine can result in bony fractures. Bone fragments displaced into the spinal canal produce spinal canal occlusion, increasing the potential for spinal cord injury (SCI). Human body models (HBMs) provide an opportunity to investigate SCI but currently need to be improved in their ability to model compression fractures and the resulting material flow. Previous work to improve fracture prediction included the development of an anisotropic material model for the bone (hard tissues) of the vertebrae assessed in a functional spinal unit (FSU) model. In the FSU model, bony failure was modeled with strain-based element erosion, with a limitation that material that could occlude the spinal canal during compression was removed when an element was eroded.

Abstract Bilateral knee impacts were conducted on Hybrid III and THOR 5th percentile female anthropomorphic test devices (ATDs), and the results were compared to previously reported female PMHS data. Each ATD was impacted at velocities of 2.5, 3.5, and 4.9 m/s. Knee–thigh–hip (KTH) loading data, obtained either via direct measurement or through exercising a one-dimensional lumped parameter model (LPM), was analyzed for differences in loading characteristics including the maximum force, time to maximum force, loading rate, and loading duration. In general, the Hybrid III had the highest loading rate and maximum force, and the lowest loading duration and time to peak force for each point along KTH. Conversely, the PMHS generally had the lowest loading rate and maximum force, and the highest loading duration and time to peak force for each point along KTH.

Abstract The objective of this study was to compare head, neck, and chest injury risks between front and rear-seated Hybrid III 50th-percentile male anthropomorphic test devices (ATDs) during matched frontal impacts. Seven vehicles were converted to rear seat test bucks (two sedans, three mid-size SUVs, one subcompact SUV, and one minivan) and then used to perform sled testing with vehicle-specific frontal NCAP acceleration pulses and a rear seated (i.e., second row) Hybrid III 50th male ATD. Matched front seat Hybrid III 50th male ATD data were obtained from the NHTSA Vehicle Crash Test Database for each vehicle. HIC15, Nij, maximum chest acceleration, and maximum chest deflection were compared between the front and rear seat tests, as well as between vehicles with conventional and advanced three-point belt restraint systems in the rear seat. Additionally, a modified version of the NCAP frontal star rating was calculated for the front and rear seat tests.

Abstract Oblique motor vehicle crashes can cause serious head or brain injuries due to contact with interior vehicle structures even with the deployment of air bags, as they are not yet completely successful in preventing traumatic brain injury. Rotational head velocity is strongly correlated to the risk of brain injury, and this head motion is potentially related to the tangential friction force developed during contact between the head and air bags. Although crash test dummy head skins are designed with appropriate mass properties and anthropometry to simulate the normal direction impact response of the human head, it is not known whether they accurately represent the frictional properties of human skin during air bag interaction. This study experimentally characterized the dynamic friction coefficient between human/dummy skins and air bag fabrics using a pin-on-disc tribometer.

Abstract Previous volunteer studies focused on low-speed frontal events have demonstrated that muscle activation (specifically pre-impact bracing) can significantly affect occupant response. However, these tests do not always include a sufficient number of small female volunteers to compare their unique responses to the typically studied midsize male population. The purposes of this study were to quantify the occupant kinetics and muscle responses of relaxed and braced small female and midsize male volunteers during low-speed frontal sled tests and to compare between muscle states and demographic groups. Small female and midsize male volunteers experienced multiple low-speed frontal sled tests consisting of two pulse severities (1 g and 2.5 g) and two muscle states (relaxed and braced) per pulse severity. The muscle activity of 30 muscles (15 bilaterally) and reaction forces at the volunteer-test buck interfaces and seat belt were measured before and during each sled test.

Abstract Some anthropomorphic test devices (ATDs) currently being developed are equipped with abdominal pressure twin sensors (APTS) for the assessment of abdominal injuries and as an indicator of the occurrence of the submarining of an occupant during a crash event. The APTS is comprised of a fluid-filled polyurethane elastomeric bladder which is sealed by an aluminum cap with an implanted pressure transducer. It is integrated into ATD abdomens, and fluid pressure is increased due to the abdomen/bladder compression due to interactions with the seatbelt or other structures. In this article, a nonlinear dynamic finite element (FE) model is constructed of an APTS using LS-PrePost and converted to the LS-Dyna solver input format. The polyurethane bladder and the internal fluid are represented with viscoelastic and isotropic hypoelastic material models, respectively. The aluminum cap was considered a rigid part since it is significantly stiffer than the bladder and the fluid.

Abstract Through connectivity with the electric grid, electric vehicles (EVs) minimize or eliminate the need for fossil fuels. Despite the rapid adoption of EVs in recent times, most government adoption objectives have not been attained. This article aims to comprehend the reasons behind the limited uptake of electric scooters in India and the driving aspects. This research used a grounded theory methodology. Using a snowball sampling technique, we conducted 25 in-depth interviews with EV owners, mainly based in Delhi and Mumbai. As an outcome of the study, four drivers and four impediments to the adoption of EVs have been formulated. The study shows that there are Financial, Technological, Operational, and Psychological drivers and Technological/Infrastructural, Operational, and Psychological impediments to the adoption. The study identifies the key concern areas in the form of categories of drivers and impediments, which can be considered in industrial and public policymaking.

Abstract This article explores the value of simulation for autonomous-vehicle research and development. There is ample research that details the effectiveness of simulation for training humans to fly and drive. Unfortunately, the same is not true for simulations used to train and test artificial intelligence (AI) that enables autonomous vehicles to fly and drive without humans. Research has shown that simulation “fidelity” is the most influential factor affecting training yield, but psychological fidelity is a widely accepted definition that does not apply to AI because it describes how well simulations engage various cognitive functions of human operators. Therefore, this investigation reviewed the literature that was published between January 2010 and May 2022 on the topic of simulation fidelity to understand how researchers are defining and measuring simulation fidelity as applied to training AI.

Abstract Prediction of the surface finish of hardened bearing steels was estimated in machining with ceramic uncoated cutting tools under various process parameters using two statistical approaches. A second-order (quadratic) regression model (MQR, multiple quantile regression) for the surface finish was developed and then compared with the artificial neural network (ANN) method based on the coefficient determination (R 2), root mean square error (RMSE), and percentage error (PE). The experimental results exhibited that cutting speed was the dominant parameter, but feed rate and depth of cut were insignificant in terms of the Pareto chart and analysis of variance (ANOVA). The optimum surface finish in machining bearing steel was achieved at 100 m/min speed, 0.1 mm/revolution (rev) feed rate, and 0.6 mm depth of cut.

Abstract Human thoracic injury under frontal collisions is an inevitable problem in vehicle safety research. Compared with the Multiple Rigid-Body Models (MRBMs) and Finite Element Human Body Models (FEHBMs), Mathematical Equivalent Models (MEMs) can not only provide important data but also improve the research efficiency. The current thoracic MEMs usually adapted the mechanical isolation method to isolate the thorax from the human body; therefore, the effects of the head, neck, and lower body internal organs on the mechanical responses of the thorax are not considered. In this article, a new thoracic MEM, named as Improved Consistent Lobdell Model (ICLM), is developed based on the concentrated mass-spring-damping system to consider the energy absorbed by the deformation of the internal soft tissue and the motion hysteresis of the head, neck, and lower body.