Session: 04-06: Morphing Aerospace Applications

Paper Number: 111011

111011 - High-Throughput Analysis and Morphing Design Space Decomposition for Mission-Adaptive Air Vehicles 

Morphing aircraft designers have often looked to birds for their ability to change shape and optimize performance characteristics such as range or maneuverability across different phases of flight. However, designing to optimize performance across multiple mission segments is highly challenging, in part because realistic morphing strategies are not without performance penalties. Common penalties include an increase in weight from additional actuators, structural weight to combat aeroelastic effects, and increased power requirements. In this work, a computational framework is developed to explore the adaptivity trade-space for a fixed wing unmanned aerial vehicle (UAV) across multiple mission segments early in the design process. To maximize feasibility, a preprocessor attempts to sample only aircraft geometry configurations that satisfy given mission requirements using textbook-level approximations. For each configuration, an aerodynamic analysis and a static stability analysis are run in parallel to determine mission performance across all given mission stages. Using the novel Non-dominated Sorting Genetic Algorithm for Adaptive Design (NSGA-AD), an extension of NSGA-II, the design space is decomposed into adaptive families based on morphing capability (e.g., adaptive sweep, twist, camber, etc.), there being quantitatively compared and rated for a given set of mission requirements. High-performance families are retained, penalized based on expected structural and system disadvantages (weight, power), and then analyzed using an uncoupled fluid structure interaction analysis method. To demonstrate the novel computational design framework, adaptivity schemes for fixed wing UAVs are algorithmically selected for two independent missions. One drives morphing to increase efficiency. The other focuses on navigating through congested environments with the use of instantaneous high g turns where flight through tight geometric bounds (e.g., windows or doors) inspire and guide the morphing behavior.

Presenting Author: Jared Lilly Texas A&M University

Presenting Author Biography: Jared is a PhD student at Texas A&M University in the Aerospace Engineering Department. He graduated from Texas A&M University with a Bachelor of Science in Mechanical Engineering in May 2021. Jared’s research has focused on the design and analysis of morphing aerospace structures including prototype space radiators, adaptive UAVs, and articulating missiles.