James P. Gaewsky

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

This studys 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.

Lumbar Vertebrae Fracture Injury Risk in Finite Element Reconstruction of CIREN and NASS Frontal Motor Vehicle Crashes

ABSTRACT Introduction: The objective of this study was to reconstruct 4 real-world motor vehicle crashes (MVCs), 2 with lumbar vertebral fractures and 2 without vertebral fractures in order to elucidate the MVC and/or restraint variables that increase this injury risk. Methods: A finite element (FE) simplified vehicle model (SVM) was used in conjunction with a previously developed semi-automated tuning method to arrive at 4 SVMs that were tuned to mimic frontal crash responses of a 2006 Chevrolet Cobalt, 2012 Ford Escape, 2007 Hummer H3, and 2002 Chevrolet Cavalier. Real-world crashes in the first 2 vehicles resulted in lumbar vertebrae fractures, whereas the latter 2 did not. Once each SVM was tuned to its corresponding vehicle, the Total HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations in each SVM by varying 5 parameters using a Latin hypercube design (LHD) of experiments: seat track position, seatback angle, steering column angle, steering column telescoping position, and d-ring height. For each case, the event data recorder (EDR) crash pulse was used to apply kinematic boundary conditions to the model. By analyzing cross-sectional vertebral loads, vertebral bending moments, and maximum principal strain and stress in both cortical and trabecular bone, injury metric response as a function of posture and restraint parameters was computed. Results: Tuning the SVM to specific vehicle models produced close matches between the simulated and experimental crash test responses for head, T6, and pelvis resultant acceleration; left and right femur loads; and shoulder and lap belt loads. Though vertebral load in the THUMS simulations was highly similar between injury cases and noninjury cases, the amount of bending moment was much higher for the injury cases. Seatback angle had a large effect on the maximum compressive load and bending moment in the lumbar spine, indicating the upward tilt of the seat pan in conjunction with precrash positioning may increase the likelihood of suffering lumbar injury even in frontal, planar MVCs. Conclusion: In conclusion, precrash positioning has a large effect on lumbar injury metrics. The lack of lumbar injury criteria in regulatory crash tests may have led to inadvertent design of seat pans that work to apply axial force to the spinal column during frontal crashes.

Driver injury risk variability in finite element reconstructions of Crash Injury Research and Engineering Network (CIREN) frontal motor vehicle crashes

Objective: A 3-phase real-world motor vehicle crash (MVC) reconstruction method was developed to analyze injury variability as a function of precrash occupant position for 2 full-frontal Crash Injury Research and Engineering Network (CIREN) cases. Method: Phase I: A finite element (FE) simplified vehicle model (SVM) was developed and tuned to mimic the frontal crash characteristics of the CIREN case vehicle (Camry or Cobalt) using frontal New Car Assessment Program (NCAP) crash test data. Phase II: The Toyota HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations per case within the SVM. Five occupant positioning variables were varied using a Latin hypercube design of experiments: seat track position, seat back angle, D-ring height, steering column angle, and steering column telescoping position. An additional baseline simulation was performed that aimed to match the precrash occupant position documented in CIREN for each case. Phase III: FE simulations were then performed using kinematic boundary conditions from each vehicles event data recorder (EDR). HIC15, combined thoracic index (CTI), femur forces, and strain-based injury metrics in the lung and lumbar vertebrae were evaluated to predict injury. Results: Tuning the SVM to specific vehicle models resulted in close matches between simulated and test injury metric data, allowing the tuned SVM to be used in each case reconstruction with EDR-derived boundary conditions. Simulations with the most rearward seats and reclined seat backs had the greatest HIC15, head injury risk, CTI, and chest injury risk. Calculated injury risks for the head, chest, and femur closely correlated to the CIREN occupant injury patterns. CTI in the Camry case yielded a 54% probability of Abbreviated Injury Scale (AIS) 2+ chest injury in the baseline case simulation and ranged from 34 to 88% (mean = 61%) risk in the least and most dangerous occupant positions. The greater than 50% probability was consistent with the case occupants AIS 2 hemomediastinum. Stress-based metrics were used to predict injury to the lower leg of the Camry case occupant. The regional-level injury metrics evaluated for the Cobalt case occupant indicated a low risk of injury; however, strain-based injury metrics better predicted pulmonary contusion. Approximately 49% of the Cobalt occupants left lung was contused, though the baseline simulation predicted 40.5% of the lung to be injured. Conclusions: A method to compute injury metrics and risks as functions of precrash occupant position was developed and applied to 2 CIREN MVC FE reconstructions. The reconstruction process allows for quantification of the sensitivity and uncertainty of the injury risk predictions based on occupant position to further understand important factors that lead to more severe MVC injuries.

Numerical investigation of driver lower extremity injuries in finite element frontal crash reconstruction

ABSTRACT 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.

Finite Element Human Body Model Thorax Response Validation With Matched Experimental Tests

Finite Element Models (FEMs) are increasingly used to evaluate occupant response and safety system effectiveness in automotive safety research.[1, 2] These models are validated against experimental tests with known results to evaluate the model’s ability to predict the occupant response. The FEM used for this study was the Total HUman Model for Safety (THUMS). The occupant thorax model has already been validated in three basic thorax loading conditions.[3] The hypothesis of this study was if the model had been successfully validated in these simplified configurations, additional loading conditions that involve a more complex load path should also follow the experimental response.© 2013 ASME

Computational Modeling and Analysis of Thoracolumbar Spine Fractures in Frontal Crash Reconstruction

Abstract Objective: This study aimed to reconstruct 11 motor vehicle crashes (6 with thoracolumbar fractures and 5 without thoracolumbar fractures) and analyze the fracture mechanism, fracture predictors, and associated parameters affecting thoracolumbar spine response. Methods: Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM). The SVM was tuned to each case 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 a boundary condition. For the 6 thoracolumbar fracture cases, 120 simulations to quantify uncertainty and response variation were performed using a Latin hypercube design of experiments (DOE) to vary seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Vertebral loads and bending moments were analyzed, and lumbar spine indices (unadjusted and age-adjusted) were developed to quantify the combined loading effect. Maximum principal strain and stress data were collected in the vertebral cortical and trabecular bone. DOE data were fit to regression models to examine occupant positioning and thoracolumbar response correlations. Results: Of the 11 cases, both the vertebral compression force and bending moment progressively increased from superior to inferior vertebrae. Two thoracic spine fracture cases had higher average compression force and bending moment across all thoracic vertebral levels, compared to 9 cases without thoracic spine fractures (force: 1,200.6 vs. 640.8 N; moment: 13.7 vs. 9.2 Nm). Though there was no apparent difference in bending moment at the L1–L2 vertebrae, lumbar fracture cases exhibited higher vertebral bending moments in L3–L4 (fracture/nonfracture: 45.7 vs. 33.8 Nm). The unadjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 9 of the 11 cases (sensitivity = 1.0; specificity = 0.6). The age-adjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 10 of the 11 cases (sensitivity = 1.0; specificity = 0.8). The age-adjusted principal stress in the trabecular bone was an excellent indicator of fracture occurrence (sensitivity = 1.0; specificity = 1.0). A rearward seat track position and reclined seatback increased the thoracic spine bending moment by 111–329%. A more reclined seatback increased the lumbar force and bending moment by 16–165% and 67–172%, respectively. Conclusions: This study provided a computational framework for assessing thoracolumbar fractures and also quantified the effect of precrash driver posture on thoracolumbar response. Results aid in the evaluation of motor vehicle crash–induced vertebral fractures and the understanding of factors contributing to fracture risk.