Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article


Master of Engineering Science


Mechanical and Materials Engineering


Mao, Haojie


This study focuses on supporting the development of safety regulations for vulnerable populations during drone to head impacts. First, the small female head and neck model was compared to cadaveric data. Then, combined with lab’s previous work, gender-based disparities in head impact responses were highlighted, with small females experiencing higher injury risk metrics, despite lower skull von Mises stress. Beyond small females, children of various ages and their head responses during impacts were also analyzed. In addition to the previously developed quadcopter drone model, a new Mavic Pro drone model was developed, and this model was integrated with human head models during comparison against cadaveric data. The Mavic Pro, despite its lower weight, demonstrated higher injury risks compared to the previously studied Phantom 3. Overall, in this study head kinematics, head injury criteria (HIC), rotational velocities, and brain strains were analyzed, indicating potential risks for vulnerable populations. These findings underscore the need for tailored safety measures, regulatory guidelines, and comprehensive injury prevention strategies in the field of drone operations.

Summary for Lay Audience

Drones have gained widespread popularity across various industries but concerns about the safety of drone-head collisions have prompted research into head injury risks and protection strategies. This study presents a comprehensive investigation into this critical area.

The study investigated gender-based differences in head injury risks. A computational model was meticulously tested against experimental data, showcasing its reliability in simulating brain motion, and predicting injury responses. Notably, small females exhibited a higher vulnerability to head injuries compared to males. The research progressed on the focus shifted to vulnerable populations, particularly children, in drone-related impacts. Advanced models simulated various impact scenarios and highlighted injury risks based on age groups. Findings underscore the significance of considering both linear and rotational kinematics in assessing head injuries. Furthermore, the study delved into the complex dynamics of drone-to-human impacts, emphasizing small remotely piloted aircraft systems (sRPAS). A highly detailed finite element model accurately replicated real-world impact dynamics and revealed that different drone models pose varying injury risks. The study underscores the importance of rigorous safety measures in drone design and operations.