Author's School

School of Engineering & Applied Science

Author's Department/Program

Electrical and Systems Engineering

Language

English (en)

Date of Award

January 2010

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Chair and Committee

Ervin Rodin

Abstract

Aerial Refueling: AR) is the act of offloading fuel from one aircraft: the tanker) to another aircraft: the receiver) in mid flight. Meetings between tanker and receiver aircraft are referred to as AR events and are scheduled to: escort one or more receivers across a large body of water; refuel one or more receivers; or train receiver pilots, tanker pilots, and boom operators. In order to efficiently execute the Aerial Refueling Mission, the Air Mobility Command: AMC) of the United States Air Force: USAF) depends on computer models to help it make tanker basing decisions, plan tanker sorties, schedule aircraft, develop new organizational doctrines, and influence policy. We have worked on three projects that have helped AMC improve its modeling and decision making capabilities. Optimal Flight Planning: Currently Air Mobility simulation and optimization software packages depend on algorithms which iterate over three dimensional fuel flow tables to compute aircraft fuel consumption under changing flight conditions. When a high degree of fidelity is required, these algorithms use a large amount of memory and CPU time. We have modeled the rate of aircraft fuel consumption with respect to AC Gross Weight, Altitude and Airspeed. When implemented, this formula will decrease the amount of memory and CPU time needed to compute sortie fuel costs and cargo capacity values. We have also shown how this formula can be used in optimal control problems to find minimum costs flight plans. Tanker Basing Demand Mismatch Index: Since 1992, AMC has relied on a Tanker Basing/AR Demand Mismatch Index which aggregates tanker capacity and AR demand data into six regions. This index was criticized because there were large gradients along regional boundaries. Meanwhile tankers frequently cross regional boundaries to satisfy the demand for AR support. In response we developed continuous functions to score locations with respect to their proximity to demand for AR support as well as their isolation from existing tanker bases. Optimal Scheduling:<\bold> Because most of the tanker resources are controlled by individual Air National Guard Units there is little to no central authority coordinating tanker and receiver training schedules. We have been able to show that significant flying hour savings could be achieved if National Guard tanker units were to yield some of their scheduling autonomy to a central authority which was charged with the responsibility of matching tanker training requirements to receiver training requirements.

DOI

https://doi.org/10.7936/K7XW4GV3

Comments

Permanent URL: http://dx.doi.org/10.7936/K7XW4GV3

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