Abstract

Many potential small Unmanned Aerial Systems (sUAS) applications require or would benefit from deploying a fleet of aircraft to perform a mission. Fleet operations present advantages to maximize mission success by using additional sUAS; however, an additional advantage exists in the ability to design a bespoke sUAS and capitalize on the innovation in rapid prototyping and collaborative control. If this fleet includes new, yet-to-be-designed sUAS, the problem of both designing the new sUAS and allocating the fleet becomes a challenging optimization problem. Starting from promising work in similar applications, this work will investigate how a decomposition approach will allow a top-level multi-objective problem to optimize fleet-level performance metrics, while lower-level problems will perform the aircraft design and sUAS allocation tasks. The allocation problem uses a fleet operations simulation environment to evaluate fleet level metrics outputted from the aircraft sizing problem. The aircraft sizing problem, driven by a SQP algorithm with legacy sUAS sizing predictions and a Breguet endurance equation-based sizing code, predicts the geometry, weight and performance of future sUAS.

The study incorporates objectives to minimizes the lifecycle cost of a five-year operation and maximize data collection opportunities for sUAS profiling missions within the atmospheric boundary layer (ABL). The newly found Pareto sUAS design solutions are then used to construct a response surface to describe the Pareto set and guide decision-makers through the selection process for best sUAS architecture and fleet solution. Traditional ABL profiling operations use weather towers, weather balloons, and manned fixed-wing aircraft to acquire data; however, leveraging the economic, modular, and simultaneous spatial coverage advantages, a sUAS fleet can provide an alternative to using manned aircraft. In this research, the goal is to determine how to formulate a multi-objective design optimization problem that guides decision-makers on what sUAS platforms and the number of sUAS needed to profile the ABL.

Degree Type

Thesis

Degree Name

Master of Science in Aeronautics and Astronautics

Department

Aeronautics and Astronautics

Committee Chair

William A. Crossley

Date of Award

8-2018

Committee Member 1

Daniel A. Delaurentis

Committee Member 2

Robin L. Tanamachi

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