Assessment of finite element human body and ATD models in estimating injury risk in far-side impacts using field-based injury risk.

The objective of this study was to assess the ability of finite element human body models (FEHBMs) and Anthropometric Test Device (ATD) models to estimate occupant injury risk by comparing it with field-based injury risk in far-side impacts. The study used the Global Human Body Models Consortium midsize male (M50-OS+B) and small female (F05-OS+B) simplified occupant models with a modular detailed brain, and the ES-2Re and SID-IIs ATD models in the simulated far-side crashes. A design of experiments (DOE) with a total of 252 simulations was conducted by varying lateral ΔV (10-50kph; 5kph increments), the principal direction of force (PDOF 50°, 60°, 65°, 70°, 75°, 80°, 90°), and occupant models. Models were gravity-settled and belted into a simplified vehicle model (SVM) modified for far-side impact simulations. Acceleration pulses and vehicle intrusion profiles used for the DOE were generated by impacting a 2012 Camry vehicle model with a mobile deformable barrier model across the 7 PDOFs and 9 lateral ΔV's in the DOE for a total of 63 additional simulations. Injury risks were estimated for the head, chest, lower extremity, pelvis (AIS 2+; AIS 3+), and abdomen (AIS 3+) using logistic regression models. Combined AIS 3+ injury risk for each occupant was calculated using AIS 3+ injury risk estimations for the head, chest, abdomen, and lower extremities. The injury risk calculated using computational models was compared with field-based injury risk derived from NASS-CDS by calculating their correlation coefficient. The field-based injury risk was calculated using risk curves that were created based on real-world crash data in a previous study (Hostetler et al., 2020). Occupant age (40 years), seatbelt use (belted occupant), collision deformation classification, lateral ΔV, and PDOF of the crash event were used in these curves to estimate field injury risk. Large differences in the kinematics were observed between HBM and ATD models. ATD models tended to overestimate risk in almost every case whereas HBMs yielded better risk estimates overall. Chest and lower extremity risks were the least correlated with field injury risk estimates. The overall risk of AIS 3+ injury risk was the strongest comparison to the field data-based risk curves. The HBMs were still not able to capture all the variance but future studies can be carried out that are focused on investigating their shortfalls and improving them to estimate injury risk closer to field injury risk in far-side crashes.

Development and Validation of a Brain Phantom for Therapeutic Cooling Devices.

Tissue cooling has been proven as a viable therapy for multiple conditions and injuries and has been applied to the brain to treat epilepsy and concussions, leading to improved long-term outcomes. To facilitate the study of temperature reduction as a function of various cooling methods, a thermal brain phantom was developed and analyzed. The phantom is composed of a potassium-neutralized, superabsorbent copolymer hydrogel. The phantom was tested in a series of cooling trials using a cooling block and 37 deg water representing nondirectional blood flow ranging up to 6 gph, a physiologically representative range based on the prototype volume. Results were compared against a validated finite difference (FD) model. Two sets of parameters were used in the FD model: one set to represent the phantom itself and a second set to represent brain parenchyma. The model was then used to calculate steady-state cooling at a depth of 5 mm for all flow rates, for both the phantom and a model of the brain. This effort was undertaken to (1) validate the FD model against the phantom results and (2) evaluate how similar the thermal response of the phantom is to that of a perfused brain. The FD phantom model showed good agreement with the empirical phantom results. Furthermore, the empirical phantom agreed with the predicted brain response within 3.5% at physiological flow, suggesting a biofidelic thermal response. The phantom will be used as a platform for future studies of thermally mediated therapies applied to the cerebral cortex.

An Objective Evaluation of Mass Scaling Techniques Utilizing Computational Human Body Finite Element Models.

Biofidelity response corridors developed from post-mortem human subjects are commonly used in the design and validation of anthropomorphic test devices and computational human body models (HBMs). Typically, corridors are derived from a diverse pool of biomechanical data and later normalized to a target body habitus. The objective of this study was to use morphed computational HBMs to compare the ability of various scaling techniques to scale response data from a reference to a target anthropometry. HBMs are ideally suited for this type of study since they uphold the assumptions of equal density and modulus that are implicit in scaling method development. In total, six scaling procedures were evaluated, four from the literature (equal-stress equal-velocity, ESEV, and three variations of impulse momentum) and two which are introduced in the paper (ESEV using a ratio of effective masses, ESEV-EffMass, and a kinetic energy approach). In total, 24 simulations were performed, representing both pendulum and full body impacts for three representative HBMs. These simulations were quantitatively compared using the International Organization for Standardization (ISO) ISO-TS18571 standard. Based on these results, ESEV-EffMass achieved the highest overall similarity score (indicating that it is most proficient at scaling a reference response to a target). Additionally, ESEV was found to perform poorly for two degree-of-freedom (DOF) systems. However, the results also indicated that no single technique was clearly the most appropriate for all scenarios.