Session: 03-01 Mission-Adaptive Morphing UAVs

Paper Number: 168517

168517 - A Computational Framework for the Preliminary Design of Mission-Adaptive Unmanned Air Vehicles 

This work aims to explore the adaptivity trade-space for morphing unmanned aerial vehicles (UAVs), effectively determining the viability of morphing concepts. This is done through the continued development of a computational framework for preliminary morphing aircraft design.

In previous work, a preprocessor was presented that uses textbook equations to bound the design space to a set of feasible design variables. This bounded region is then used to generate enough designs to provide a sufficient sampling of the design space. The design configurations are generated based on the allowable morphing concepts selected by the user. Then, an automated aerodynamic and performance analysis is performed on the selected designs. These designs are then sorted into groups that can morph between one another, or adaptive families, through a process called Design Space Decomposition (DSD). DSD also ranks each of the adaptive families based on their performance. The highest-performing adaptive family is passed through structural realization where its structural integrity and morphing penalty are evaluated through actuator weight penalties and automated finite element analysis. This work will expand on this previous work by expanding the aerodynamic analysis with viscous effects and control surfaces, adding constraints to DSD, adding transient morphing for performance evaluation, and including a consideration of the total allowable morphing weight for the highest-performing family. 

Previous aerodynamic analyses were all inviscid, leading to the overprediction of range and endurance. A viscous turbulence model was added to the computational fluid dynamics for accurate drag estimates, and therefore, accurate range and endurance estimates. Control surfaces are added to the geometry generation and aerodynamic analyses for the estimation of control derivatives, enabling the trade between asymmetric morphing and control surfaces to be explored. With stability derivatives, control derivatives, and estimated component weights from the preprocessor, the dynamic response of each aircraft configuration and/or adaptive family can be tested across different maneuvers for transient morphing performance evaluation. 

In previous work, DSD was implemented but a consideration of constraints was not made. This means that families could be reported as highly performing while in actuality not being able to meet the constraints of the mission. This work will perform DSD with consideration of constraints to ensure that the reported highly performing adaptive families can meet all constraints of the mission. In addition, the adaptivity search and adaptivity design selection have been decoupled to enable the objective functions to operate over the entire family as opposed to one configuration (e.g. transient morphing). 

To answer whether morphing is viable and/or beneficial, a metric for the maximum weight penalty due to morphing has been developed. The performance of an adaptive family is evaluated with an added weight penalty until the adaptive family no longer outperforms the compromise design. Once this critical weight penalty is found, it can be reported as the max weight for morphing structures and give designers a better intuition for the viability of morphing. 

To showcase the impact of framework updates, previous missions are revisited with the addition of a maneuverability mission. The maneuverability mission includes a pitching maneuver for obstacle avoidance. These framework updates increase the applicability of the framework to diverse missions within the explorable adaptivity trade-space. 

Presenting Author: Walker Buckle Texas A&M University

Presenting Author Biography: Walker is a Senior Aerospace Engineering Student from Frisco, TX. To date, his work has spanned reduced-order structural modeling, adaptive radiator experimentation, and active rotor blade wind tunnel testing. Currently, his research is on the development of software to optimize morphing small UAS and creating a low-cost wind tunnel system to study free-flight maneuvers. Outside of the lab, he is the Advanced Class Chief Engineer for the SAE AERO Design Team developing autonomous aerial systems.