Abstract
As unmanned aerial vehicles (UAVs) continue to be of great interest, scientists are looking back at nature to aid development. Increases in lift relative to drag and improvements to energy efficiency are hoped to be gained from studies exploring natural fliers like birds and bugs. My technical capstone explores the flight of a dragonfly while attempting to replicate its geometry and maneuverability. Comparatively, my STS research looks at how UAVs can be utilized for disaster recovery efforts. Unfortunately, inequalities exist in the distribution of disaster recovery funding, so UAV utilization is inherently impacted.
Bio-inspired flight is significant for its ability to exploit more efficient flight, as well as the potential to thrive in atmospheres other than our own, including Mars. Dragonflies are a great research example, such that my capstone group has explored, designed, and built a UAV inspired by a dragonfly. Like a dragonfly, the UAV has independent actuation, where all four wings flap separately from each other. A 3D-printed weight-efficient body supports four mechanisms that convert a motor’s spin into oscillating flapping of carbon-fiber and Mylar wings. Matching a dragonfly’s flapping, the UAV flaps at a frequency of 25-27 Hertz (flaps per second).
Advancements in UAV technology allow for more significant applications, including (but not limited to) disaster recovery situations. Not constrained by ground accessibility, UAVs can cover inhospitable terrains in ways other vehicles cannot. However, innovative technologies like UAVs will have associated economic costs, and inequality in disaster recovery funding exists, with some communities receiving less support than others in the US. To effectively explore these disparities and couple them with the utilization of UAV technology, I used an Actor-Network Theory (ANT) approach to guide my analysis. ANT proved to be an effective tool as it allowed me to connect all the relevant actors, both human and nonhuman. Creation of an ANT diagram yielded important insights into how policymakers, communities, and UAV technologies interact. The analysis provided three significant results. First, it was seen that biases are illogical, considering that natural disaster effects propagate across the country, past the community that is directly impacted. Second, specific technologies like radars and remote sensing can be integrated with UAVs to improve damage assessment and search and rescue. Finally, the ethical schools of utilitarianism and Kantianism both oppose the existence of biases in funding in the first place.
My technical capstone provided a better understanding of how UAVs are designed, built, and operated. From there, my sociotechnical research allowed me to address inequalities in disaster recovery funding in the US while considering how UAVs can help stricken communities. I now understand how various other useful disaster mitigation technologies can be used in tandem with UAVs to provide support most effectively. With insights into funding inequalities now addressed, leveling the playing field should be the next step. At the same time, further UAV development should be explored.
Notes
School of Engineering and Applied Science
Bachelor of Science in Aerospace Engineering
Technical Advisor: Haibo Dong
STS Advisor: Sean Murray
Technical Team Members: Lily Byers, Kathryn Geoffroy, Theodore LengKong, Jafar Mansoor, Justin Matara, Owen McKenney, Andrew Golemon-Mercer, Carter Nickola, Jeremiah Nubbe, Mark Piatko, Luis Ramos-Garcia, James Scullin, Matthew Sendi, George Zach
