Rapid Development of Urban Air Mobility Vehicle Concepts through Full-Configuration Multidisciplinary Design, Analysis, and Optimization

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.

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.

There are four project objectives. The first objective is to develop a large-scale MDAO toolset that will be made available to the urban air mobility industry by publishing it as open-source software with extensive documentation. The second objective is to use these tools to achieve three technical challenges, formulated as computation time targets for low-fidelity system-level MDAO, mid-fidelity system-level MDAO, and high-fidelity subsystem-level optimization, respectively. The third objective is to advance knowledge in three high-impact research areas: mathematical modeling of eVTOL vehicles; partial-differential-equation-based computational engineering (code generation methods, isogeometric analysis, immersed methods); and multidisciplinary design optimization (local sensitivity analysis, modeling languages). The final objective is to broaden diverse participation in aeronautics research through local outreach, the creation of student research opportunities that promote diversity, and the deployment of the design tools from this project in undergraduate and graduate curricula.