Development and Validation of Human Body Finite Element Models for Pedestrian Protection
| dc.contributor.author | Pak, Wansoo | en |
| dc.contributor.committeechair | Untaroiu, Costin D. | en |
| dc.contributor.committeemember | Untaroiu, Alexandrina | en |
| dc.contributor.committeemember | Gayzik, F. Scott | en |
| dc.contributor.committeemember | Hardy, Warren N. | en |
| dc.contributor.committeemember | Lee, Yong Woo | en |
| dc.contributor.department | Department of Biomedical Engineering and Mechanics | en |
| dc.date.accessioned | 2019-10-22T08:00:24Z | en |
| dc.date.available | 2019-10-22T08:00:24Z | en |
| dc.date.issued | 2019-10-21 | en |
| dc.description.abstract | The pedestrian is one of the most vulnerable road users. According to the World Health Organization (WHO), traffic accidents cause about 1.34 million fatalities annually across the world. This is the eighth leading cause of death across all age groups. Among these fatalities, pedestrians represent 23% (world), 27% (Europe), 40% (Africa), 34% (Eastern Mediterranean), and 22% (Americas) of total traffic deaths. In the United States, approximately 6,227 pedestrians were killed in road crashes in 2018, the highest number in nearly three decades. To protect pedestrians during Car-to-Pedestrian Collisions (CPC), subsystem impact tests, using impactors corresponding to the pedestrian's head and upper/lower leg were included in regulations. However, these simple impact tests cannot capture the complex vehicle-pedestrian interaction, nor the pedestrian injury mechanisms, which are crucial to understanding pedestrian kinetics/kinematics responses in CPC accidents. Numerous variables influence injury variation during vehicle-pedestrian interactions, but current test procedures only require testing in the limited scenarios that mostly focus on the anthropometry of the 50th percentile male subject. This test procedure cannot be applied to real-world accidents nor the entire pedestrian population due to the incredibly specific nature of the testing. To better understand the injury mechanisms of pedestrians and improve the test protocols, more pre-impact variables should be considered in order to protect pedestrians in various accident scenarios. In this study, simplified finite element (FE) models corresponding to 5th percentile female (F05), 50th percentile male (M50), and 95th percentile male (M95) pedestrians were developed and validated in order to investigate the kinetics and kinematics of pedestrians in a cost-effective study. The model geometries were reconstructed from medical images and exterior scanned data corresponding to a small female, mid-sized male, and tall male volunteers, respectively. These models were validated based on post mortem human surrogate (PMHS) test data under various loading including valgus bending at knee joint, lateral/anterior-lateral impact at shoulder, pelvis, thorax, and abdomen, and lateral impact during CPC. Overall, the kinetic/kinematic responses predicted by the pedestrian FE models showed good agreement against the corresponding PMHS test data. To predict injuries from the tissue level up to the full-body, detailed pedestrian models, including sophisticated musculoskeletal system and internal organs, were developed and validated as well. Similar validations were performed on the detailed pedestrian models and showed high-biofidelic responses against the PMHS test data. After model development and validation, the effect of pre-impact variables, such as anthropometry, pedestrian posture, and vehicle type in CPC impacts were investigated in different impact scenarios. The M50-PS model's posture was modified to replicate pedestrian gait posture. Five models were developed to demonstrate pedestrian posture in 0, 20, 40, 60, and 80 % of the gait cycle. In a sensitivity study, the 50th percentile male pedestrian simplified (M50-PS) model in gait predicted various kinematic responses as well as the injury outcomes in CPC impact with different vehicle type. The pedestrian FE models developed in this work have the capability to reproduce the kinetic/kinematic responses of pedestrians and to predict injury outcomes in various CPC impact scenarios. Therefore, this work could be used to improve the design of new vehicles and current pedestrian test procedures, which eventually may reduce pedestrian fatalities in traffic accidents. | en |
| dc.description.abstractgeneral | The pedestrian is one of the most vulnerable road users. According to the World Health Organization, traffic accidents cause about 1.34 million fatalities annually across the world. This is the eighth leading cause of death across all age groups. Among these fatalities, pedestrians represent 23% (world), 27% (Europe), 40% (Africa), 34% (Eastern Mediterranean), and 22% (Americas) of total traffic deaths. In the United States, approximately 6,227 pedestrians were killed in road crashes in 2018, the highest number in nearly three decades. To protect pedestrians in traffic accidents, subsystem impact tests, using impactors corresponding to the pedestrian’s head and upper/lower leg were included in regulations. However, these simple impact tests cannot capture the complex vehicle-pedestrian interaction, nor the pedestrian injury mechanisms, which are crucial to understanding pedestrian kinetics/kinematics responses in traffic accidents. Numerous variables influence injury variation during vehicle-pedestrian interactions, but current test procedures only require testing in the limited scenarios that mostly focus on the anthropometry of the average male subject. This test procedure cannot be applied to real-world accidents nor the entire pedestrian population due to the incredibly specific nature of the testing. To better understand the injury mechanisms of pedestrians and improve the test protocols, more pre-impact variables should be considered in order to protect pedestrians in various accident scenarios. In this study, simplified pedestrian computational models corresponding to small female, average male, and large male pedestrians were developed and validated in order to investigate the kinetics and kinematics of pedestrians in a cost-effective study. Overall, the kinetic/kinematic responses predicted by the pedestrian models showed good agreement against the corresponding test data. To predict injuries from the tissue level up to the full-body, detailed pedestrian computational models, including sophisticated musculoskeletal system and internal organs, were developed and validated as well. Similar validations were performed on the detailed pedestrian models and showed high-biofidelic responses against the test data. After model development and validation, the pre-impact variables were examined using the average male pedestrian model, which was modified the position to replicate pedestrian gait posture. In a sensitivity study, the average male pedestrian model in gait predicted various kinematic responses as well as the injury outcomes in lateral impact with different vehicle types. The pedestrian models developed in this work have the capability to reproduce the kinetic/kinematic responses of pedestrian and to predict injury outcomes in various pedestrian impact scenarios. Therefore, this work could be used to improve the design of new vehicles and current pedestrian test procedures, which eventually many reduce pedestrian fatalities in traffic accidents. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:22657 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/95019 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | finite element modeling | en |
| dc.subject | impact biomechanics | en |
| dc.subject | pedestrian safety | en |
| dc.subject | computational biomechanics | en |
| dc.title | Development and Validation of Human Body Finite Element Models for Pedestrian Protection | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Biomedical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |