Multifidelity Rotor Wake Modeling with Uncertainty Quantification of Transitioning Tilt-Propeller Aircraft Performance

A framework for efficient multifidelity modeling of tilt-propeller aircraft performance is developed, with an emphasis on accurate modeling of transition maneuvers between vertical and forward flight. Low- and midfidelity vortex models are used for the propeller aerodynamic data sources and lifting surface analyses. Uncertainty quantification of propeller model parameters is conducted and used as the input uncertainty of the source data over the operational domain. A multifidelity approach is proposed, using active learning of Gaussian processes (GPs) that are sequentially and adaptively enhanced with additional higher-fidelity data queried at strategic points selected from an acquisition function. This process is applied to the buildup of single- and multifidelity GPs, forming surrogate models of propeller performance over the operational domain. Each surrogate model is used in the full aircraft mission analysis of a tilt-propeller aircraft and provides quantified uncertainty in aircraft performance over the full flight envelope. Optimal maneuvers are also explored, balancing the tradeoff between maximum power, tilt rates, and time efficiency of conversion. The developed methods are applicable to many distributed electric propulsion aircraft configurations and are applied in this paper to a pusher-configured tilt-propeller aircraft.