Research
Motivation
Urban air mobility could improve the quality of life of Americans by enabling point-to-point, on-demand air transportation in densely populated areas. Air taxis with vertical takeoff and landing (VTOL) capability would shorten commutes by several times and revolutionize cargo delivery and emergency medical services. However, the design of these vehicles is uniquely challenging, with many coupled design parameters and a lack of historical data, which makes traditional design methods unreliable.
Research aim
Led by the University of California San Diego, this University Leadership Initiative (ULI) project aims to create computational design tools that would enable the urban air mobility industry to design higher-performance eVTOL vehicles faster and with greater automation. The project approaches this goal using an emerging class of design methods called large-scale multidisciplinary design, analysis, and optimization (MDAO). Large-scale MDAO constructs multidisciplinary computational models of the system performance and applies numerical optimization algorithms that can efficiently search for designs of maximum performance or efficiency, based on up to thousands of design parameters.