Comparison of Performance of Predicting the Wear Amount of Tire Tread Depending on Sensing Information.

Excessive tire wear can affect vehicle driving safety. While there are various methods for predicting the tire wear amount in real-time, it is unclear which method is the most effective in terms of the difficulty of sensing and prediction accuracy. The current study aims to develop prediction algorithms of tire wear and compare their performances. A finite element tire model was developed and validated against experimental data. Parametric tire rolling simulations were conducted using various driving and tire wear conditions to obtain tire internal accelerations. Machine-learning-based algorithms for tire wear prediction utilizing various sensing options were developed, and their performances were compared. A wheel translational and rotational speed-based (V and ω) method resulted in an average prediction error of 1.2 mm. Utilizing the internal pressure and vertical load of the tire with the V and ω improved the prediction accuracy to 0.34 mm. Acceleration-based methods resulted in an average prediction error of 0.6 mm. An algorithm using both the vehicle and tire information showed the best performance with a prediction error of 0.21 mm. When accounting for sensing cost, the V and ω-based method seems to be promising option. This finding needs to be experimentally verified.

Is optimized restraint system for an occupant with obesity different than that for a normal BMI occupant?

OBJECTIVE: To optimize the components of restraint systems for protecting obese (BMI = 35 kg/m2) and normal BMI (BMI = 25) human body models (HBMs) in frontal crash simulations, and to compare the two optimized designs. METHODS: The Life Years Lost metric, which incorporates the risk of injury and long-term disability to different body regions, was used as the optimization objective function. Parametric simulations, sampled from a 15-parameter design space using the Latin Hypercube technique, were performed and metamodels of the HBM responses were developed. A genetic algorithm was applied to the metamodels to identify the optimized designs. RESULTS: While most of the restraint parameters between the optimized design for obese and normal BMI HBMs were similar, the main difference was that the restraint for the obese HBM included an under-the-seat airbag, which mitigated its lower extremity excursion, improved its torso kinematics, and decreased its lower extremity and lumbar spine injury risks. The optimized designs for both HBMs included an inflatable seat belt, which reduced the risk of thoracic injury. CONCLUSIONS: The design recommendations from this study should be considered to improve safety of occupants with obesity.

Monte carlo method for estimating whole-body injury metrics from pedestrian impact simulation results.

The goal of the current study was to develop a method to estimate whole-body injury metrics (WBIMs), which measure the overall impact of injuries, using stochastic injury prediction results from a computational human surrogate. First, hospitalized pedestrian data was queried to identify injuries sustained by pedestrians and their frequencies. Second, with consideration for an understanding of injury mechanisms and the capability of the computational human surrogate, the whole-body was divided into 17 body regions. Then, an injury pattern database was constructed for each body region for various maximum abbreviated injury scale (MAIS) levels. Third, a two-step Monte Carlo sampling process was employed to generate N virtual pedestrians with an assigned list of injuries in AIS codes. Then, the expected values of WBIMs such as injury severity score (ISS), probability of death, whole-body functional capacity index (WBFCI), and lost years of life (LYL), were estimated. Lastly, the proposed method was verified using injury information from the inpatient pedestrian database. Also, the proposed method was applied to pedestrian impact simulations with various impact speeds to estimate the probability of death with respect to the impact speed. The probability of death from the proposed method was compared with those from epidemiological studies. The proposed method accurately estimated WBIMs such as ISS and WBFCI using either for a given distribution of injury risk or MAIS levels. The predicted probability of death with respect to the impact speed showed a good correlation with those from the epidemiological study. These results imply that if we have a human surrogate that can predict the risk of injury accurately, we can accurately estimate WBIMs using the proposed method. The proposed method can simplify a vehicle design optimization process by transforming the multi-objective optimization problem into the single-objective one. Lastly, the proposed method can be applied to other human surrogates such as occupant models.

Injury risk functions based on population-based finite element model responses: Application to femurs under dynamic three-point bending.

OBJECTIVE: The goal of this study was to explore a framework for developing injury risk functions (IRFs) in a bottom-up approach based on responses of parametrically variable finite element (FE) models representing exemplar populations. METHODS: First, a parametric femur modeling tool was developed and validated using a subject-specific (SS)-FE modeling approach. Second, principal component analysis and regression were used to identify parametric geometric descriptors of the human femur and the distribution of those factors for 3 target occupant sizes (5th, 50th, and 95th percentile males). Third, distributions of material parameters of cortical bone were obtained from the literature for 3 target occupant ages (25, 50, and 75 years) using regression analysis. A Monte Carlo method was then implemented to generate populations of FE models of the femur for target occupants, using a parametric femur modeling tool. Simulations were conducted with each of these models under 3-point dynamic bending. Finally, model-based IRFs were developed using logistic regression analysis, based on the moment at fracture observed in the FE simulation. In total, 100 femur FE models incorporating the variation in the population of interest were generated, and 500,000 moments at fracture were observed (applying 5,000 ultimate strains for each synthesized 100 femur FE models) for each target occupant characteristics. RESULTS: Using the proposed framework on this study, the model-based IRFs for 3 target male occupant sizes (5th, 50th, and 95th percentiles) and ages (25, 50, and 75 years) were developed. The model-based IRF was located in the 95% confidence interval of the test-based IRF for the range of 15 to 70% injury risks. The 95% confidence interval of the developed IRF was almost in line with the mean curve due to a large number of data points. CONCLUSIONS: The framework proposed in this study would be beneficial for developing the IRFs in a bottom-up manner, whose range of variabilities is informed by the population-based FE model responses. Specifically, this method mitigates the uncertainties in applying empirical scaling and may improve IRF fidelity when a limited number of experimental specimens are available.

Pelvic restraint cushion sled test evaluation of pelvic forward motion.

OBJECTIVE: This study was designed to evaluate the performance of a pelvic restraint cushion (PRC), a submarining countermeasure that deploys under the thighs when a crash is detected in order to block the forward motion of the pelvis. METHODS: Sled tests approximating low- and high-speed frontal impacts were conducted with 4 female postmortem human subjects (PMHS) restrained by a lap and shoulder belt in the right front passenger seat. The subjects were tested with and without a PRC. RESULTS: The PRC is effective in reducing forward motion of the PMHS pelvis and reduces the risk of injury due to lap belt loading in a high-speed frontal crash. CONCLUSIONS: Although small sample size limits the utility of the study's findings, the results suggest that the PRC can limit pelvic forward motion and that pelvic injury due to PRC deployment is not likely.

Identification of characteristics and frequent scenarios of single-vehicle rollover crashes during pre-ballistic phase; part 1 - A descriptive study.

This study aimed to identify common patterns of pre-ballistic vehicle kinematics and roadway characteristics of real-world rollover crashes. Rollover crashes that were enrolled in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) between the years 2000 and 2010 were analyzed. A descriptive analysis was performed to understand the characteristics of the pre-ballistic phase. Also, a frequency based pattern analysis was performed using a selection of NASS-CDS variables describing the pre-ballistic vehicle kinematics and roadway characteristics to rank common pathways of rollover crashes. Most case vehicles departed the road due to a loss of control/traction (LOC) (61%). The road departure with LOC was found to be 13.4 times more likely to occur with slippery road conditions compared to dry conditions. The vehicle was typically laterally skidding with yawing prior to a rollover (66%). Most case vehicles tripped over (82%) mostly at roadside/median (69%). The tripping force was applied to the wheels/tires (82%) from the ground (79%). The combination of these six most frequent attributes resulted in the most common scenario, which accounted for 26% of the entire cases. Large proportion of road departure with LOC (61%) implies electronic stability control (ESC) systems being an effective countermeasure for preventing single-vehicle rollover crashes. Furthermore, the correlation between the road departure with LOC and the reduced friction limit suggests the necessity of the performance evaluation of ESC under compromised road surface condition.

Prediction of the structural response of the femoral shaft under dynamic loading using subject-specific finite element models.

The goal of this study was to predict the structural response of the femoral shaft under dynamic loading conditions using subject-specific finite element (SS-FE) models and to evaluate the prediction accuracy of the models in relation to the model complexity. In total, SS-FE models of 31 femur specimens were developed. Using those models, dynamic three-point bending and combined loading tests (bending with four different levels of axial compression) of bare femurs were simulated, and the prediction capabilities of five different levels of model complexity were evaluated based on the impact force time histories: baseline, mass-based scaled, structure-based scaled, geometric SS-FE, and heterogenized SS-FE models. Among the five levels of model complexity, the geometric SS-FE and the heterogenized SS-FE models showed statistically significant improvement on response prediction capability compared to the other model formulations whereas the difference between two SS-FE models was negligible. This result indicated the geometric SS-FE models, containing detailed geometric information from CT images with homogeneous linear isotropic elastic material properties, would be an optimal model complexity for prediction of structural response of the femoral shafts under the dynamic loading conditions. The average and the standard deviation of the RMS errors of the geometric SS-FE models for all the 31 cases was 0.46 kN and 0.66 kN, respectively. This study highlights the contribution of geometric variability on the structural response variation of the femoral shafts subjected to dynamic loading condition and the potential of geometric SS-FE models to capture the structural response variation of the femoral shafts.

Evaluation of biofidelity of THUMS pedestrian model under a whole-body impact conditions with a generic sedan buck.

OBJECTIVE: The goal of this study was to evaluate the biofidelity of the Total Human Model for Safety (THUMS; Ver. 4.01) pedestrian finite element models (PFEM) in a whole-body pedestrian impact condition using a well-characterized generic pedestrian buck model. METHODS: The biofidelity of THUMS PFEM was evaluated with respect to data from 3 full-scale postmortem human subject (PMHS) pedestrian impact tests, in which a pedestrian buck laterally struck the subjects using a pedestrian buck at 40 km/h. The pedestrian model was scaled to match the anthropometry of the target subjects and then positioned to match the pre-impact postures of the target subjects based on the 3-dimensional motion tracking data obtained during the experiments. An objective rating method was employed to quantitatively evaluate the correlation between the responses of the models and the PMHS. Injuries in the models were predicted both probabilistically and deterministically using empirical injury risk functions and strain measures, respectively, and compared with those of the target PMHS. RESULTS: In general, the model exhibited biofidelic kinematic responses (in the Y-Z plane) regarding trajectories (International Organization for Standardization [ISO] ratings: Y = 0.90 ± 0.11, Z = 0.89 ± 0.09), linear resultant velocities (ISO ratings: 0.83 ± 0.07), accelerations (ISO ratings: Y = 0.58 ± 0.11, Z = 0.52 ± 0.12), and angular velocities (ISO ratings: X = 0.48 ± 0.13) but exhibited stiffer leg responses and delayed head responses compared to those of the PMHS. This indicates potential biofidelity issues with the PFEM for regions below the knee and in the neck. The model also demonstrated comparable reaction forces at the buck front-end regions to those from the PMHS tests. The PFEM generally predicted the injuries that the PMHS sustained but overestimated injuries in the ankle and leg regions. CONCLUSIONS: Based on the data considered, the THUMS PFEM was considered to be biofidelic for this pedestrian impact condition and vehicle. Given the capability of the model to reproduce biomechanical responses, it shows potential as a valuable tool for developing novel pedestrian safety systems.

Biofidelity evaluation of WorldSID and ES-2re under side impact conditions with and without airbag.

This study evaluated the biofidelity of the WorldSID and the ES-2re under whole-body side impact conditions with and without a side airbag using the biomechanical cadaveric response data generated from 4.3m/s whole-body side impact tests. Impact forces, spinal kinematics, and chest deflections were considered in the biofidelity evaluation. Average responses and response corridors of PMHS were created using a time-alignment technique to reduce variability of the PMHS responses while maintaining the sum of the time shifts to be zero for each response. Biofidelity of the two dummies was compared using a correlation and analysis (CORA) method. The WorldSID demonstrated better biofidelity than the ES-2re in terms of CORA ratings in the conditions with airbag (0.53 vs. 0.46) and without an airbag (0.57 vs. 0.49). Lastly, the kinematic analysis of the two dummies indicated an overly compliant shoulder response of the WorldSID and excessive forward rotation of the ES-2re relative to the PMHS.

Validation of Shoulder Response of Human Body Finite-Element Model (GHBMC) Under Whole Body Lateral Impact Condition.

In previous shoulder impact studies, the 50th-percentile male GHBMC human body finite-element model was shown to have good biofidelity regarding impact force, but under-predicted shoulder deflection by 80% compared to those observed in the experiment. The goal of this study was to validate the response of the GHBMC M50 model by focusing on three-dimensional shoulder kinematics under a whole-body lateral impact condition. Five modifications, focused on material properties and modeling techniques, were introduced into the model and a supplementary sensitivity analysis was done to determine the influence of each modification to the biomechanical response of the body. The modified model predicted substantially improved shoulder response and peak shoulder deflection within 10% of the observed experimental data, and showed good correlation in the scapula kinematics on sagittal and transverse planes. The improvement in the biofidelity of the shoulder region was mainly due to the modifications of material properties of muscle, the acromioclavicular joint, and the attachment region between the pectoralis major and ribs. Predictions of rib fracture and chest deflection were also improved because of these modifications.

The Contribution of Pre-impact Spine Posture on Human Body Model Response in Whole-body Side Impact.

The objective of the study was to analyze independently the contribution of pre-impact spine posture on impact response by subjecting a finite element human body model (HBM) to whole-body, lateral impacts. Seven postured models were created from the original HBM: one matching the standard driving posture and six matching pre-impact posture measured for each of six subjects tested in previously published experiments. The same measurements as those obtained during the experiments were calculated from the simulations, and biofidelity metrics based on signals correlation were established to compare the response of HBM to that of the cadavers. HBM responses showed good correlation with the subject response for the reaction forces, the rib strain (correlation score=0.8) and the overall kinematics. The pre-impact posture was found to greatly alter the reaction forces, deflections and the strain time histories mainly in terms of time delay. By modifying only the posture of HBM, the variability in the impact response was found to be equivalent to that observed in the experiments performed with cadavers with different anthropometries. The patterns observed in the responses of the postured HBM indicate that the inclination of the spine in the frontal plane plays a major role. The postured HBM sustained from 2 to 5 bone fractures, including the scapula in some cases, confirming that the pre-impact posture influences the injury outcome predicted by the simulation.