Session: 03-01 Mission-Adaptive Morphing UAVs

Paper Number: 167957

167957 - Development of a Software Framework for Analysis, Optimization, and Design of Highly Maneuverable Morphing Small Uavs 

This presentation presents the development and user interface of a Software Design Framework entitled “Software for Parallelized Analyses and Rapid Optimization (SPARRO),” for rapid and cost-effective design, analysis, and performance estimation of a family of avian-inspired, fixed-wing SUAVs in cruising flight conditions, the avoidance of stationary obstacles, and the pursuit of moving obstacle avoidance enabled by morphing for extreme maneuverability.

Fixed-wing UAVs have high endurance but have difficulty negotiating dense and congested areas. Avian species handle both tasks by their incredible ability to morph into a variety of shapes depending on the demands of the current environment.  Taking inspiration from birds and building upon prior work done by the team members and other researchers [1-9], we can develop shape changing (i.e., morphing) UAV designs which would approach the high maneuverability of quadcopters while overcoming their limitations on range, endurance, and speed.

While these and other recent work provide a good foundation to develop bird-like UAVs (albeit with fixed wings and thrust obtained by motor-driven props), developing morphing SUAV designs for a given set of requirements presents several unique challenges. Two key ones are: i) combinatorial explosion in the number of design configurations to be analyzed, especially when multiple morphing concepts appear feasible and need to be evaluated; and ii) performing non-linear aeroelastic analysis of flexible wings undergoing large deformations which require significant computational resources.

Our work addresses this critical gap in current design and analysis tools for small UAVs – i.e., the capability to rapidly, efficiently, and accurately analyze a large number of aircraft configurations for multiple missions and flight segments and evaluate the feasibility and advantages of adaptive structures in those given mission conditions.

Program accomplishments include: development of a Preprocessor which uses mission requirements to create a set of parametric aircraft configurations that reduces the number of runs requiring high-fidelity analyses by several orders of magnitude through rapidly generating feasible aircraft configurations and evaluating the flight performance estimates, maneuverability estimates, and design space constraint limits; implementation of adaptive design space decomposition to determine morphing aircraft designs and overall mission performance; exploration of the adaptive design space with realistic examples.

This presentation focuses on details of the software development and results of examples using the  Preprocessor. The user can design each mission segment including the type of mission (cruise, dash, loiter, avoid, pursue) and the parameters of the given mission (speed, altitude, obstacle dimensions, etc.). Once the mission segments have been defined, the user designs the layout of the internal components of the fuselage including the payload components, the engine selection, and the battery location. The locations of these elements affect the stability of the aircraft, and the fuselage internal layout design can be updated based on the results of subsequent analysis.

Afterwards,Subsequently the user sets the design parameters being explored (span, chord, taper, sweep, incidence, airfoil, tail area, and fuselage empennage length) and those parameters quantitatively define the design space (feasible ranges of span, area, wing loading, tail volume, etc.). The feasible aircraft geometries are analyzed using Class II analytical equations and the resulting power, stall angle, pitch rate, etc. determine the optimal design for the given mission conditions.

Using the pareto frontier of designs, the Preprocessor decomposes these aircraft designs into aircraft configuration parameters and populates a Latin hypercube design of experiments of adaptive designs used as starting points for high-fidelity CFD and structural analyses, significantly reducing the number of configurations to be explored.

In the exploration of the design space for adaptive vehicles, the framework will continue illustrating the mission designs that will most benefit from adaptivity and the adaptive structures that will provide the largest mission benefits for the next generation of sUAS.

The full presentation will describe the details of the Preprocessor user interface and results of a set of adaptive examples.

Presenting Author: Matthew Smalling NextGen Aeronautics

Presenting Author Biography: Matthew Smalling