Simulation of occupant response in space capsule landing configurations with suit hardware.

The purpose of this study was to compare the response of the total human model for safety (THUMS) human body finite element model (FEM) to experimental postmortem human subject (PMHS) test results and evaluate possible injuries caused by suit ring elements. Experimental testing evaluated the PMHS response in frontal, rear, side, falling, and spinal impacts. The THUMS was seated in a rigid seat that mirrored the sled buck used in the experimental testing. The model was then fitted with experimental combinations of neck, shoulder, humerus and thigh rings with a five-point restraint system. Experimental seat acceleration data was used as the input for the simulations. The simulation results were analyzed and compared to PMHS measurements to evaluate the response of the THUMS in these loading conditions. The metrics selected to compare the THUMS simulation to PMHS tests were the chest acceleration, seat acceleration and belt forces with additional metrics implemented in THUMS. The chest acceleration of the simulations and the experimental data was closely matched except in the Z-axis (superior/inferior) loading scenarios based on signal analysis. The belt force data of the model better correlated to the experimental results in loading scenarios where the THUMS interacted primarily with the restraint system compared to load cases where the primary interaction was between the seat and the occupant (rear, spinal and lateral impacts). The simulation output demonstrated low injury metric values for the occupant in these loading conditions. In the experimental testing, rib fractures were recorded for the frontal and left lateral impact scenarios. Fractures were not seen in the simulations, most likely due to variations between the simulation and the PMHS initial configuration. The placement of the rings on the THUMS was optimal with symmetric placement about the centerline of the model. The experimental placement of the rings had more experimental variation. Even with this discrepancy, the THUMS can still be considered a valuable predictive tool for occupant injury because it can compare results across many simulations. The THUMS also has the ability to assess a wider variety of other injury information, compared to anthropomorphic test devices (ATDs), that can be used to compare simulation results.

Robust human body model injury prediction in simulated side impact crashes.

This study developed a parametric methodology to robustly predict occupant injuries sustained in real-world crashes using a finite element (FE) human body model (HBM). One hundred and twenty near-side impact motor vehicle crashes were simulated over a range of parameters using a Toyota RAV4 (bullet vehicle), Ford Taurus (struck vehicle) FE models and a validated human body model (HBM) Total HUman Model for Safety (THUMS). Three bullet vehicle crash parameters (speed, location and angle) and two occupant parameters (seat position and age) were varied using a Latin hypercube design of Experiments. Four injury metrics (head injury criterion, half deflection, thoracic trauma index and pelvic force) were used to calculate injury risk. Rib fracture prediction and lung strain metrics were also analysed. As hypothesized, bullet speed had the greatest effect on each injury measure. Injury risk was reduced when bullet location was further from the B-pillar or when the bullet angle was more oblique. Age had strong correlation to rib fractures frequency and lung strain severity. The injuries from a real-world crash were predicted using two different methods by (1) subsampling the injury predictors from the 12 best crush profile matching simulations and (2) using regression models. Both injury prediction methods successfully predicted the case occupant's low risk for pelvic injury, high risk for thoracic injury, rib fractures and high lung strains with tight confidence intervals. This parametric methodology was successfully used to explore crash parameter interactions and to robustly predict real-world injuries.

Implementation and validation of thoracic side impact injury prediction metrics in a human body model.

This study's purpose was to implement injury metrics into the Total Human Model for Safety (THUMS) mirroring the spinal accelerometers, rib accelerometers and chest band instrumentation from two lateral post-mortem human subject sled test configurations. In both sled configurations, THUMS contacted a flat rigid surface (either a wall or beam) at 6.7 m/s. Sled A maximum simulated wall forces for the thorax, abdomen and pelvis were 7.1, 5.0 and 10.0 kN versus 5.7 ± 0.8, 3.4 ± 1.2 and 6.2 ± 2.7 kN experimentally. Sled B maximum simulated beam forces for the torso and pelvis were 8.0 and 7.6 kN versus 8.5 ± 0.2 and 7.9 ± 2.5 kN experimentally. Quantitatively, force magnitude contributed more to variation between simulated and experimental forces than phase shift. Acceleration-based injury metrics were within one standard deviation of experimental means except for the lower spine in the rigid wall sled test. These validated metrics will be useful for quantifying occupant loading conditions and calculating injury risks in various loading configurations.

Finite element comparison of human and Hybrid III responses in a frontal impact.

The improvement of finite element (FE) Human Body Models (HBMs) has made them valuable tools for investigating restraint interactions compared to anthropomorphic test devices (ATDs). The objective of this study was to evaluate the effect of various combinations of safety restraint systems on the sensitivity of thoracic injury criteria using matched ATD and Human Body Model (HBM) simulations at two crash severities. A total of seven (7) variables were investigated: 3-point belt with two (2) load limits, frontal airbag, knee bolster airbag, a buckle pretensioner, and two (2) delta-v's - 40kph and 50kph. Twenty four (24) simulations were conducted for the Hybrid III ATD FE model and repeated with a validated HBM for 48 total simulations. Metrics tested in these conditions included sternum deflection, chest acceleration, chest excursion, Viscous Criteria (V*C) criteria, pelvis acceleration, pelvis excursion, and femur forces. Additionally, chest band deflection and rib strain distribution were measured in the HBM for additional restraint condition discrimination. The addition of a frontal airbag had the largest effect on the occupant chest metrics with an increase in chest compression and acceleration but a decrease in excursion. While the THUMS and Hybrid III occupants demonstrated the same trend in the chest compression measurements, there were conflicting results in the V*C, acceleration, and displacement metrics. Similarly, the knee bolster airbag had the largest effect on the pelvis with a decrease in acceleration and excursion. With a knee bolster airbag the simulated occupants gave conflicting results, the THUMS had a decrease in femur force and the ATD had an increase. Preferential use of dummies or HBM's is not debated; however, this study highlights the ability of HBM metrics to capture additional chest response metrics.

Injury prediction in a side impact crash using human body model simulation.

BACKGROUND: Improved understanding of the occupant loading conditions in real world crashes is critical for injury prevention and new vehicle design. The purpose of this study was to develop a robust methodology to reconstruct injuries sustained in real world crashes using vehicle and human body finite element models. METHODS: A real world near-side impact crash was selected from the Crash Injury Research and Engineering Network (CIREN) database. An average sedan was struck at approximately the B-pillar with a 290 degree principal direction of force by a lightweight pickup truck, resulting in a maximum crush of 45 cm and a crash reconstruction derived Delta-V of 28 kph. The belted 73-year-old midsized female driver sustained severe thoracic injuries, serious brain injuries, moderate abdominal injuries, and no pelvic injury. Vehicle finite element models were selected to reconstruct the crash. The bullet vehicle parameters were heuristically optimized to match the crush profile of the simulated struck vehicle and the case vehicle. The Total Human Model for Safety (THUMS) midsized male finite element model of the human body was used to represent the case occupant and reconstruct her injuries using the head injury criterion (HIC), half deflection, thoracic trauma index (TTI), and pelvic force to predict injury risk. A variation study was conducted to evaluate the robustness of the injury predictions by varying the bullet vehicle parameters. RESULTS: The THUMS thoracic injury metrics resulted in a calculated risk exceeding 90% for AIS3+ injuries and 70% risk of AIS4+ injuries, consistent with her thoracic injury outcome. The THUMS model predicted seven rib fractures compared to the case occupant's 11 rib fractures, which are both AIS3 injuries. The pelvic injury risk for AIS2+ and AIS3+ injuries were 37% and 2.6%, respectively, consistent with the absence of pelvic injury. The THUMS injury prediction metrics were most sensitive to bullet vehicle location. The maximum 95% confidence interval width for the mean injury metrics was only 5% demonstrating high confidence in the THUMS injury prediction. CONCLUSIONS: This study demonstrates a variation study methodology in which human body models can be reliably used to robustly predict injury probability consistent with real world crash injury outcome.

Head impact exposure in youth football: high school ages 14 to 18 years and cumulative impact analysis.

Sports-related concussion is the most common athletic head injury with football having the highest rate among high school athletes. Traditionally, research on the biomechanics of football-related head impact has been focused at the collegiate level. Less research has been performed at the high school level, despite the incidence of concussion among high school football players. The objective of this study is to twofold: to quantify the head impact exposure in high school football, and to develop a cumulative impact analysis method. Head impact exposure was measured by instrumenting the helmets of 40 high school football players with helmet mounted accelerometer arrays to measure linear and rotational acceleration. A total of 16,502 head impacts were collected over the course of the season. Biomechanical data were analyzed by team and by player. The median impact for each player ranged from 15.2 to 27.0 g with an average value of 21.7 (±2.4) g. The 95th percentile impact for each player ranged from 38.8 to 72.9 g with an average value of 56.4 (±10.5) g. Next, an impact exposure metric utilizing concussion injury risk curves was created to quantify cumulative exposure for each participating player over the course of the season. Impacts were weighted according to the associated risk due to linear acceleration and rotational acceleration alone, as well as the combined probability (CP) of injury associated with both. These risks were summed over the course of a season to generate risk weighted cumulative exposure. The impact frequency was found to be greater during games compared to practices with an average number of impacts per session of 15.5 and 9.4, respectively. However, the median cumulative risk weighted exposure based on combined probability was found to be greater for practices vs. games. These data will provide a metric that may be used to better understand the cumulative effects of repetitive head impacts, injury mechanisms, and head impact exposure of athletes in football.