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The present study had three objectives: (1) define a reasonable number of categories to bin head injuries, (2) develop an overarching risk function to estimate head-injury probability based on injury probabilities pertaining to those subordinate categories, and (3) assess the fidelity of both the overarching function and approximations to it. To achieve these objectives, we used real-world data from the National Automotive Sampling System (NASS), pertaining to adult drivers in full-engagement frontal crashes. To provide practical value, we factored the proposed US New Car Assessment Program (US NCAP) and the corresponding Request for Comments from the government. Finally, the NASS data stratifications included three levels of injury (AIS1+, AIS2+, AIS3+), two levels of restraint (properly-belted, unbelted), and two eras based on driver-airbag fitment (Older Vehicles, Newer Vehicles).

The National Highway Traffic Safety Administration (NHTSA) recently published a Request for Comments regarding a potential upgrade to the US New Car Assessment Program (US NCAP) - a star-rating program pertaining to vehicle crashworthiness. Therein, NHTSA (a) cited two metrics for assessing head risk: Head Injury Criterion (HIC15) and Brain Injury Criterion (BrIC), and (b) proposed to conduct risk assessment via its risk curves for those metrics, but did not prescribe a specific method for applying them. Recent studies, however, have indicated that the NHTSA risk curves for BrIC significantly overstate field-based head injury rates. Therefore, in the present three-part study, a new set of BrIC-based risk curves was derived, an overarching head risk equation involving risk curves for both BrIC and HIC15 was assessed, and some additional candidate-predictor-variable assessments were conducted. Part 1 pertained to the derivation.

A provisional, age-dependent thoracic risk equation (or, “risk curve”) was derived to estimate moderate-to-fatal injury potential (AIS2+), pertaining to men with responses gaged by the advanced mid-sized male test dummy (THOR50). The derivation involved two distinct data sources: cases from real-world crashes (e.g., the National Automotive Sampling System, NASS) and cases involving post-mortem human subjects (PMHS). The derivation was therefore more comprehensive, as NASS datasets generally skew towards younger occupants, and PMHS datasets generally skew towards older occupants. However, known deficiencies had to be addressed (e.g., the NASS cases had unknown stimuli, and the PMHS tests required transformation of known stimuli into THOR50 stimuli).

Transfer or response equations are important as they provide relationships between the responses of different surrogates under matched, or nearly identical loading conditions. In the present study, transfer equations for different body regions were developed via mathematical modeling. Specifically, validated finite element models of the age-dependent Ford human body models (FHBM) and the mid-sized male Hybrid III (HIII50) were used to generate a set of matched cases (i.e., 192 frontal sled impact cases involving different restraints, impact speeds, severities, and FHBM age). For each impact, two restraint systems were evaluated: a standard three-point belt with and without a single-stage inflator airbag. Regression analyses were subsequently performed on the resulting FHBM- and HIII50-based responses. This approach was used to develop transfer equations for seven body regions: the head, neck, chest, pelvis, femur, tibia, and foot.

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.

In the present study, transfer equations relating the responses of post-mortem human subjects (PMHS) to the mid-sized male Hybrid III test dummy (HIII50) under matched, or nearly-identical, loading conditions were developed via math modeling. Specifically, validated finite element (FE) models of the Ford Human Body Model (FHBM) and the HIII50 were used to generate sets of matched cases (i.e., 256 frontal impact cases involving different impact speeds, severities, and PMHS age). Regression analyses were subsequently performed on the resulting age-dependent FHBM- and HIII50-based responses. This approach was conducted for five different body regions: head, neck, chest, femur, and tibia. All of the resulting regression equations, correlation coefficients, and response ratios (PHMS relative to HIII50) were consistent with the limited available test-based results.

A three-step process was developed to estimate fracture criteria for a human body model. The process was illustrated via example wherein skull fracture criteria were estimated for the Ford Human Body Model (FHBM)~a finite element model of a mid-sized human male. The studied loading condition was anterior-to-posterior, blunt (circular/planar) cylinder impact to the frontal bone. In Step 1, a conditional reference risk curve was derived via statistical analysis of the tests involving fractures in a recently reported dataset (Cormier et al., 2011a). Therein, Cormier et al., authors reported results for anterior-to-posterior dynamic loading of the frontal bone of rigidly supported heads of male post mortem human subjects, and fracture forces were measured in 22 cases. In Step 2, the FHBM head was used to conduct some underlying model validations relative to the Cormier tests. The model-based Force-at-Peak Stress was found to approximate the test-based Fracture Force.

The increasing number of people over 65 years old (YO) is an important research topic in the area of impact biomechanics, and finite element (FE) modeling can provide valuable support for related research. There were three objectives of this study: (1) Estimation of the representative age of the previously documented Ford Human Body Model (FHBM)~an FE model which approximates the geometry and mass of a mid-sized male, (2) Development of FE models representing two additional ages, and (3) Validation of the resulting three models to the extent possible with respect to available physical tests. Specifically, the geometry of the model was compared to published data relating rib angles to age, and the mechanical properties of different simulated tissues were compared to a number of published aging functions. The FHBM was determined to represent a 53-59 YO mid-sized male. The aforementioned aging functions were used to develop FE models representing two additional ages: 35 and 75 YO.

Various frontal impact risk curves were assessed for the next-generation USA New Car Assessment Program (NCAP). Specifically, the “NCAP risk curves” — those chosen by the government for the 2011 model year NCAP — as well as other published risk curves were used to estimate theoretically the injury rates of belted drivers in real-world frontal crashes. Two perspectives were considered: (1) a “point” estimate of NCAP-type events from NCAP fleet tests, and (2) an “aggregate” estimate of 0 ≤ ΔV ≤ 56 km/h crashes from a modeled theoretical vehicle whose NCAP performance approximated the average of the studied fleet. Four body regions were considered: head, neck, chest, and knee-thigh-hip complex (KTH). The curve-based injury rates for each body region were compared with those of real-world frontal crashes involving properly-belted adult drivers in airbag-equipped light passenger vehicles. The assessment yielded mixed results.

A set of risk equations was derived to estimate the probability of sustaining a moderate-to-serious injury to the knee-thigh-hip complex (KTH) in a frontal crash. The study consisted of four parts. First, data pertaining to knee-loaded, whole-body, post-mortem human subjects (PMHS) were collected from the literature, and the attendant response data (e.g., axial compressive load applied to the knee) were normalized to those of a mid-sized male. Second, numerous statistical analyses and mathematical constructs were used to derive the set of risk equations for adults of various ages and genders. Third, field data from the National Automotive Sampling System (NASS) were analyzed for subsequent comparison purposes.