Multilevel Variable Fidelity Optimization of a Morphing Unmanned Aerial Vehicle

The Morphing Aircraft Structures (MAS) program has grown substantially in technol-ogy and has received more attention in recent years. One main initiative of this project is to develop aerial vehicles that are capable of radical shape change. Such shape changes should enable the vehicle to efficiently perform single missions that normally would require two or more different aircraft. Many design optimization issues arise for such systems. Morphing aircraft have multiple configurations which create multiobjective and possibly multilevel optimization problems. The problems are multiobjective because of the perfor-mance trade-offs occurring between each morphed state. In many morphing concepts one configuration must be defined in order to design a second state; this produces a multi-level design problem. The complexity of the simulation model and the nested formulation of the multilevel design problem results in a very computationally intensive optimization problem. This paper includes a discussion of solution strategies for these multiobjective, multilevel morphing aircraft design problems. Two design tools are explored to combat the described issues of the optimization problem: conversion to a single-level design prob-lem and the use of variable fidelity optimization. A study is performed comparing the results obtained from the optimization processes of both a multi-level design problem and its corresponding single level problem. Finally a variable fidelity optimization framework is discussed and applied to design a morphing concept; the two fidelity models include a high fidelity computational fluid dynamics simulation and a low fidelity panel method. Nomenclature α Angle of attack γ Additive scaling function, error between high and low fidelity models Γ Circulation distribution γ ̃ Approximated additive scaling function ∆ Trust region size ǫf Convergence tolerance for objective function ǫx Convergence tolerance for design variables µ l1 penalty function weight ρ Trust region ratio φ Velocity potentia