| dc.description.abstract | Mission-adaptive aerostructural design considers the alteration of structural geometries to im-prove multi-objective performance in multiple aerodynamic environments. Geometric structural alterations can be tailored to flight conditions derived from specific mission profiles, but adaptive structures design requires evaluating the aerostructural responses for each geometry to determine the optimal configuration for each mission stage. However, the addition of adaptive structures increases the design difficulty for several reasons. First, the aerostructural response must be evaluated over a range of feasible geometries, and morphing feasibility between each possible geometric configuration must be determined considering the proposed actuation method. Next, the effects of altering geometry must be related to vehicle performance. From a mission-driven perspective, altering the geometry may lead to changes in vehicle control inputs necessary to maintain specified velocity, attitude, etc., and the vehicle must be properly trimmed to match mission requirements. Finally, adaptive structures can increase design complexity, with configurations for each objective.
This work develops a mission-driven design framework combining aerodynamic, structural, mission, and optimization computational tools to design and optimize adaptive aerostructures. Aerodynamic conditions and vehicle properties are defined by mission requirements, where a mission is defined as a sequence of specified flight phases with a unique set of mission performance objectives. Aerodynamic and structural analysis tools iteratively trim the vehicle for each mission stage while considering geometric changes, viable actuation methods, and actuator sizing required for a complete structural description. Preferred geometries for each mission stage are then determined via optimization to improve performance metrics defined by mission objectives and requirements. The computational framework searches algorithmically for structural configurations that improve mission-driven objectives based on trim flight for each mission stage using a novel algorithm to consider both adaptive and fixed design variable selection to effectively solve this complex design problem.
Framework effectiveness will be evaluated by considering multiple mission-driven adaptive design and optimization problems. Specifically, the framework will evaluate mission-driven morph-ing rotorcraft designs, which consider dynamic multi-physical responses and cyclic control inputs to trim the vehicle. First, the computational framework will determine the placement of adaptive systems in the rotor blade based on multi-objective optimizations to improve individual mission objectives to determine preferred actuator locations and sets of adaptive geometric configurations for each mission phase.
A wide range of adaptive technologies can be explored for mission-driven configurations early in the design process with effective aircraft modeling. However, many existing design and optimization methods, including genetic optimization techniques, are not specifically designed for optimizations in which some design variables are adaptive while others are not. A common technique to utilize these tools is to consider each morphable design variable as a different design variable for each state or objective, which can increase the optimization problem complexity.
A novel optimization technique is developed and evaluated in this work for mission-driven, multi-objective design of adaptive structures. By considering design variables that can and can-not adapt differently, preferred configurations can be evaluated based on adaptive multi-objective performance and feasibility across the design space. It will be shown that this design space de-composition can used both as a post-processing technique and as a selection technique during multi-objective genetic optimizations to determine sets of realizable adaptive designs. | |
