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Methods: A Belleville desert combat boot model was assigned contacts and material properties based on previous experiments. The boot model was fit to a previously developed model of the barefoot ATD. Validation was performed through 6 matched pair component tests conducted on the Vertically Accelerated Loads Transfer System (VALTS). The load transfer capabilities of the FE model were assessed along with the force-mitigating properties of the boot. The booted lower limb subassembly was then incorporated into a whole-body model of the ATD. Two whole-body VALTS experiments were simulated to evaluate lower limb performance in the whole body.
Results: The lower limb model accurately predicted axial loads measured at heel, tibia, and knee load cells during matched pair component tests. Forces in booted simulations were compared to unbooted simulations and an amount of mitigation similar to that of experiments was observed. In a whole-body loading environment, the model kinematics match those recorded in experiments. The shape and magnitude of experimental force–time curves were accurately predicted by the model. Correlation between the experiments and simulations was backed up by high objective rating scores for all experiments.
Conclusion: The booted lower limb model is accurate in its ability to articulate and transfer loads similar to the physical dummy in simulated underbody loading experiments. The performance of the model leads to the recommendation to use it appropriately as an alternative to costly ATD experiments. 相似文献
Method: Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes―a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured).
Results: IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18–64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes.
Conclusions: The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h. 相似文献
Methods: The AM50 THUMS PFEM was used as the baseline model, and 2 morphed PFEM were created to the anthropometric specifications of 2 obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (correlation and analysis, CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold) and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy.
Results: The baseline model could not accurately capture all aspects of the PMHS kinematics, strain, and injury risks, whereas the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during posttest autopsy.
Conclusions: The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle–pedestrian impact scenarios. 相似文献