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An Experimental and Finite Element Protocol to Investigate the Transport of Neutral and Charged Solutes across Articular Cartilage
Published on: April 23, 2017
Numerical investigation of driver lower extremity injuries in finite element frontal crash reconstruction
Xin Ye1,2, James P Gaewsky1,2, Logan E Miller1,2
1a Wake Forest University School of Medicine , Winston-Salem , North Carolina.
Objective:
Lower extremity injuries are the most frequent Abbreviated Injury Scale (AIS) 2 injury for drivers in frontal crashes. The objective was to reconstruct 11 real-world motor vehicle crashes (2 with AIS 2+ distal lower extremity injury and 9 without lower extremity injury) and to analyze the vehicle parameters and driver attributes that affect injury risk.
Methods:
Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM) using a semi-automated optimization method. The SVM was tuned to each corresponding vehicle and the Total HUman Model for Safety (THUMS) Ver 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as the boundary condition for each case. Additionally, for the 2 cases with lower extremity injury, 120 simulations to quantify the uncertainty and response variation were performed varying the following parameters using a Latin hypercube design of experiment (DOE): seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Injury metrics implemented within THUMS were calculated from the femur, tibia, and ankle and cross-compared among the 11 baseline cases using tibia index and multiple injury risk functions. Kinetic and kinematic data from the 120-simulation DOE were analyzed and fit to regression models to examine any causal relationship between occupant positioning and lower extremity injury risk.
Results:
Of the 11 real-world crashes, both cases with lower extremity injuries resulted in elevated tibia axial forces and resultant bending moments, compared to the 9 cases without lower extremity injury. The average tibia index of the 2 cases with distal lower extremity injury (left: 1.79; right: 1.19) was higher than that in the 9 cases without lower extremity injury (left: 1.16, P =.024; right: 0.82, P =.024). An increased risk of AIS 2+ tibia shaft (33.6%), distal tibia and hindfoot (20.0%), as well as ankle malleolar (14.5%) fracture was also observed for the injured compared to the noninjured cases. Rearward seat track position, reclined seat back angle, and reduced seat height were correlated with elevated tibia axial force and increased tibia index, imposing additional lower extremity injury risk.
Conclusions:
This study provides a computational framework for assessing lower extremity injuries and elucidates the effect of precrash driver posture on lower extremity injury risk while accounting for vehicle parameters and driver attributes. Results from the study aid in the evaluation of real-world injury data, the understanding of factors contributing to injury risk, and the prevention of lower extremity injuries.
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