Prediction and Validation of High Lift Performance with Strong Wing Propulsor Interactions

Numerous efforts are under way to develop aircraft for Advanced Air Mobility (AAM). Efficient flight for Urban Air Mobility (UAM) and short inter-city transportation promises to alleviate urban congestion and revolutionize air travel, while the use of Distributed Electric Propulsion (DEP) promises to do so in a safe, quiet, and energy-efficient manner. Many promising concepts are highly integrated electric vehicles with strong coupling between DEP system and airframe. One such concept is Electrarsquo;s hybrid electric Short Takeoff and Landing (eSTOL) vehicle which uses blown-lift technology to achieve substantial range-payload capacity while operating with a 100-ft ground roll. Such an eSTOL vehicle is an alternative to eVTOL that can meet similar AAM requirements safely and efficiently. All these DEP-enabled integrated concepts would benefit from improvements in aerodynamics design and analysis tools, but the lack of full-scale validation data remains a barrier.nbsp;Electra and the University of Southern California propose to address the need for such validation data via the design in Phase I, and execution in Phase II, of experiments to gather in-flight aerodynamic data specifically targeting tool validation. The overall program is envisioned to cover acquisition of full-scale flight data and improvement of state-of-the-art design and analysis tools via development of advanced aerodynamic models for vehicles with closely integrated DEP systems. Included in Phase I are estimation of in-flight performance and DEP-wing interactions using high-fidelity numerical tools, and development of an experimental test plan for the acquisition of high-quality detailed flight data using Electrarsquo;s full-scale 2-passengers eSTOL Technology Demonstrator vehicle. By complementing a test vehicle whose construction is already funded, the proposed STTR program will be able to use best-in-class instrumentation and gather a significant amount of data in a cost-effective and time-efficient manner.