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This paper first describes an experimental analytical approach and numerical procedures used to establish crushable foam material constants needed in finite element (FE) analysis. Dynamic compressive stress-strain data of a 2 pcf Dytherm foam, provided by ARCO Chemical, is used to determine the material parameters which appears in the foam constitutive equation. A finite element model simulating a 15 mph spherical headform impact with a foam sample 6 in. x 6 in. x 1 in. fixed against a rigid plate is developed. The predicted force-deflection characteristic is validated against test data to characterize the initial loading and final unloading stiffnesses of the foam during impact. Finite element modeling and analysis of 15 mph spherical headform impact with component sections of upper interior structures of a passenger compartment is presented.

Locations of key body segments of Hybrid III dummies used in FMVSS 208 compliance tests and NCAP tests were measured and subjected to statistical analysis. Mean clearance dimensions and their standard deviations for selected body segments of driver and passenger occupants with respect to selected vehicle surfaces were determined for several classes of vehicles. These occupant locations were then investigated for correlation with impact responses measured in crash tests and by using a three dimensional human-dummy mathematical model in comparable settings. Based on these data, the importance of some of the clearance dimensions between the dummy and the vehicle surfaces was determined. The study also compares observed Hybrid III dummy positions within selected vehicles with real world occupant positions reported in published literature.

Axial loading of the calcaneus-talus-tibia complex is an important injury mechanism for moderate and severe vehicular foot-ankle trauma. To develop a more definitive and quantitative relationship between biomechanical parameters such as specimen age, axial force, and injury, dynamic axial impact tests to isolated lower legs were conducted at the Medical College of Wisconsin (MCW). Twenty-six intact adult lower legs excised from unembalmed human cadavers were tested under dynamic loading using a mini-sled pendulum device. The specimens were prepared, pretest radiographs were taken, and input impact and output forces together with the pathology were obtained using load cell data. Input impact forces always exceeded the forces recorded at the distal end of the preparation. The fracture forces ranged from 4.3 to 11.4 kN.

An age-dependent, serious-to-fatal (AIS3+), thoracic risk curve was derived and evaluated for frontal impacts. The study consisted of four parts. In Part 1, two datasets of post mortem human subjects (PMHS) were generated for statistical and sensitivity analyses. In Part 2, logistic regression analyses were conducted. For each dataset, two statistical methods were applied: (1) a conventional maximum likelihood method, and (2) a modified maximum likelihood method. Therefore, four statistical models were derived — one for each dataset/statistical method combination. For all of the resulting statistical models (risk curves), the linear combination of maximum normalized sternum deflection and age of the PMHS was identified as a feasible predictor of AIS3+ thoracic injury probability. In Part 3, the PMHS-based risk curves were transformed into test-dummy-based risk curves. In Part 4, validation studies were conducted for each risk curve.

A review and analysis of existing cadaver head impact data has been conducted in this paper. The association of the Head Injury Criterion with experimental cadaver skull fracture and brain damage has been investigated, and risk curves of HIC versus skull fracture and brain damage have been developed. Limitation of the search for the maximum HIC duration to 15ms has been recommended for the proper use of HIC in the automotive crash environment.

Lower-body injury data for adults in real-world frontal impacts in the National Automotive Sampling System (NASS) were collected, analyzed, and modeled via statistical methods. Two levels of lower-body injury were considered: maximum serious-to-fatal (MAIS3+) and moderate-to-fatal (MAIS2+). In the analysis, we observed that a substantial fraction of all lower-body injured occupants had no recorded floor/toe pan intrusion: 47% of all MAIS3+ injured occupants; 69% of all MAIS2+ injured occupants. In the statistical modeling, we developed binary logistic regression models to fit the MAIS3+ and MAIS 2+ injury data. The statistically significant variables (p ≤ 0.05) were the speed change of the crash, postcrash floor/toe pan intrusion, level of restraint, occupant age, and occupant gender.

An anatomically detailed rhesus monkey brain FE model was developed to simulate in vivo responses of the brain of sub-human primates subjected to rotational accelerations resulting in diffuse axonal injury (DAI). The material properties used in the monkey model are those in the GHBMC 50th percentile male head model (Global Human Body Model Consortium). The angular loading simulations consisted of coronal, oblique and sagittal plane rotations with the center of rotation in neck to duplicate experimental conditions. Maximum principal strain (MPS) and Cumulative strain damage measure (CSDM) were analyzed for various white matter structures such as the cerebrum subcortical white matter, corpus callosum and brainstem.

An overview NASS study of US frontal crashes was performed to investigate crash involvement, driver injury distributions and rates in airbag equipped vehicles by vehicle class and structural engagement. Frontal crash bins were based on taxonomy of structural engagement, i.e., Full Engagement, Offset, Between Rails and Corner impact crashes. A new classification of Corner impacts included frontal small overlap impacts with side damage as coded by NASS CDS. Belted drivers of two age groups, between 16 and 50 and over 50 years old, were considered. Vehicles were grouped into light and heavy passenger cars and lights trucks, and vans. A method to identify and address overly influential NASS weights was developed based on considerations of weighting factor statistics. The new taxonomy, with an expanded definition of corner impacts, allowed a more comprehensive classification of frontal crash modes.

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.

The objectives of this study were to provide insights on how injury risk is influenced by occupant demographics such as sex, age, and size; and to quantify differences within the context of commonly-occurring real-world crashes. The analyses were confined to either single-event collisions or collisions that were judged to be well-defined based on the absence of any significant secondary impacts. These analyses, including both logistic regression and descriptive statistics, were conducted using the Crash Investigation Sampling System for calendar years 2017 to 2021. In the case of occupant sex, the findings agree with those of many recent investigations that have attempted to quantify the circumstances in which females show elevated rates of injury relative to their male counterparts given the same level bodily insult. This study, like others, provides evidence of certain female-specific injuries.