Unmanned Aerial Vehicle (UAV) Propulsion Research: Conceptual Studies of “Ultra-Compact Shaft-Less Jet Engines” for Next Generation UAVs
Aeronautics, Undergraduate Studies
Unmanned Aerial Vehicles are becoming more commonly used in today’s society, ranging anywhere from military applications to entertainment for enthusiasts and hobbyists. The complexity of current generation UAV’s propulsive devices, based upon a scaled turbine engine and separate gas & electrically powered rotating fan blades, require regular maintenance for every 24 hours of flight. This added cost coupled with necessary intricate machinery deters UAV designers from such engines, leaving a void in current production. Our research team believes that by combining a simplified alternative compression & combustion process with an electrically driven fan, we can develop an energy efficient, reliable, and cost effective next generation small-scale jet engine for UAVs. The underlying foundation to our design concept, ”Ultra-Compact Shaft-less Jet Engine”, was originally formulated by Cal State LA; our team is expanding on their model with innovation through simulation based design optimization, detailed component analysis, and experimental verifications in aerodynamics and combustion. A comprehensive study, utilizing Computational Fluid Dynamics based advanced computer-simulation analysis methodology and experimental investigations (wind tunnel and static tests), is currently underway. This project will greatly contribute to the current research efforts and potentially open new methods of developing the next generation UAV propulsion systems. Implementing the use of Computational Fluid Dynamics as well as wind tunnel results will yield in validation of the Shaft-less jet engine.
Grant or Award Name
Scholarly Commons Citation
Eiguren, T., Douglas, T., & Buchanan, T. (2015). Unmanned Aerial Vehicle (UAV) Propulsion Research: Conceptual Studies of “Ultra-Compact Shaft-Less Jet Engines” for Next Generation UAVs. , (). Retrieved from https://commons.erau.edu/publication/4
Faculty Mentors: Michael Fabian, Ph.D., Shigeo Hayashibara, Ph.D.