Research

Highlights and Recent Projects

Overview

My research focuses on impact/injury biomechanics, human modeling, safety design optimization, and statistical crash data analysis. The primary goal of my research is to reduce the incidence of injuries and fatalities in motor-vehicle crashes and other injurious events using a multidisciplinary approach. It involves

      1. analyzing field data to identify the injury problems and assess factors associated with the injuries,
      2. performing physical tests and computational simulations to investigate human impact responses, injury mechanisms, and injury tolerances for various body regions under impact conditions, and
      3. developing tools and conducting computational simulations to optimize safety designs for reducing impact-induced injuries.

Parametric Human Modeling Representing a Diverse Population

While my research addresses injury mitigation for the whole population, much of my recent work has been focused on improving protection for various vulnerable populations, including children, elderly, obese population, pregnant women, wheelchair users and pedestrians. One of the highlights for my recent research is the development of parametric finite element (FE) human models representing a diverse population. This research is extremely important, because current injury assessment tools (i.e. crash test dummies and human models) only represent a few sizes of healthy human subjects but do not consider morphological and biomechanical variations among the population. By using a combination of medical image analyses, statistical analyses, and mesh morphing methods, my colleagues and I have developed methodologies that can rapidly generate FE human models accounting for human morphological variations. Such models have been applied to study pediatric head injuries in falls, elderly and obese occupant protection in motor-vehicle crashes, and pedestrians. This new modeling paradigm will enable population-based simulations and overcome the limitation in existing methods for safety designs and forensic investigations that do not adequately consider human variability. The modeling methodologies are also expected to have significant impacts on many other fields, such as computer aided surgery and medical device design.

Rear-seat Restraint System Design Optimizations

My recent work on rear-seat occupant protection has focused on restraint-system optimization that addresses the different needs of a diverse population. Front-seat occupant protection has received most of the research attention due to higher occupancy rates, but protecting rear-seat occupants is more challenging, mainly due to the need to protect small children as well as older adults. In a recently-finished NHTSA project, my colleagues and I optimized advanced restraint systems for providing better protections for rear seat occupants of a wide range of sizes. In collaboration with ZF TRW, three series of sled tests (baseline tests, advanced restraint trail tests, and a final series of tests), two series of model validations (against each of the first two series of sled tests), and design optimizations using the validated computational models were conducted to investigate rear-seat occupant protection with 4 ATDs (HIII 6YO, HIII 5th female, THOR, ad HIII 95th male), 2 crash pulses, 2 impact angles, and 2 front seat locations. This study demonstrated the occupant safety improvements offered by the advanced restraint systems, especially special-designed airbags, for rear-seat occupants.

NHTSA Project on Rearseat Occupant Protection

Military Vehicle Safety

Advanced restraint systems, such as seatbelt pre-tensioners, load limiters, and airbags, are currently not utilized in military vehicles. Optimally implementing these technologies requires a better understanding of the occupant kinematics and injury risks in crash scenarios with military vehicles. The solutions are not necessarily the same as those used in passenger vehicles because of differences in crash type and pulse, occupant characteristics, vehicle compartment geometry, and occupant seating posture. Body-borne gear also significantly affects restraint system interaction. I am currently leading a large-scale research program to determine how to improve protection of occupants of military vehicles in frontal and rollover crashes through implementing and optimizing next-generation seatbelt and airbag technologies through a combination of physical testing and computational modeling. Much of this effort has focused on developing and validating models of body-borne gear, which may increase the effective mass of the occupant, change the fit and interaction between belt and occupant, and create alternative loading paths between the occupant and the vehicle interior. All of these factors greatly increase the complexity of the restraint optimization process. Despite this, optimized restraints dramatically reduce the injury risks in frontal crashes of military vehicles. In this research program, my colleagues and I also developed and validated a new test procedure for rollover testing of military vehicles. This procedure produces a rollover for a heavy vehicle with a repeatable rolling rate, which other existing rollover tests cannot produce.

TARDEC project on occupant protection for tactical vehicles

Evaluations on new safety technologies and regulations using multi-disciplinary data

Another highlight of my recent research is combining different types of data to evaluate the potential effects of new technologies or regulations on motor vehicle injury prevention. My research naturally ties crash/injury data, experimental data, and modeling data together through statistical approaches. As an example, in a recent Ford-funded study, I linked real-world crash data, naturalistic driving data, and computational human modeling data to investigate the potential safety benefit of integrated active and passive safety systems in vehicle frontal crashes. In a recent NHTSA-funded project, with collaborating researchers from GM, my colleagues and I combined field data and simulation data to investigate the potential benefit of seatbelt interlocks and the impact of removing the regulation of unbelted occupant crash requirement. I believe that with the fast development of computational power and new tools available for data analysis, fusing/combining different types of datasets together will help us conquer many extremely challenging research problems that would be otherwise very difficult to resolve.

Ford project on integration of active and passive safety

Reduction of Head/Brain Injury in Children

Head/brain injury is the leading cause of pediatric death, disability, and health-care costs in the United States. Unfortunately, both the anthropometric data and mechanical response data for pediatric heads are largely lacking. As a result, current injury assessment tools for children are either scaled version of adults, which cannot account for cranial sutures present in infant skulls, or are based only on head geometry from a single child, which neglects the large variation and growth effects on head geometry. To solve this problem, my students and I introduced the parametric FE modeling concept into this field. We developed statistical geometry models of the pediatric skull for 0- to 3-year-old children, which was linked to a baseline FE head model, so that the model can be rapidly morphed into various geometries representing children from different ages and sizes. This research is currently supported by National Institute of Justice (NIJ) to use this modeling approach for assessing pediatric head injuries in falls and child-abuse cases. We have a broad range of activities in this project, including in-depth investigations of pediatric falls, reconstructions of head-injury events using computational models, and further improvement of our modeling techniques.

An example of pediatric fall reconstructions using subject-specific FE head models