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Ph.D. Thesis Proposal
By
Evan D. Harrison
(Advisor: Prof. Dimitri N. Mavris)
12:00 PM, Friday, January 19, 2018
Weber Space Science and Technology Building (SST-II)
Collaborative Visualization Environment (CoVE)
A METHODOLOGY FOR PREDICTING AND
MITIGATING LOSS OF CONTROL INCIDENTS FOR
GENERAL AVIATION AIRCRAFT
ABSTRACT:
In comparison with other modes of transportation, aviation has earned a clear distinction as the safest mode of travel. In recent years aviation has also achieved steady improvement in the accident rates, further distinguishing the safety of aviation with respect to other transportation modes. When aviation accidents do occur, however, it has been found that the most likely cause of these accidents is loss of control (LOC). Annual analysis of accident data performed by Boeing indicates that LOC is the most common cause of aviation accidents and fatalities for commercial aircraft worldwide and the Federal Aviation Administration (FAA) identifies LOC as the most important safety concern for general aviation (GA) as well.
Recent work to identify and mitigate LOC events has been largely successful in identifying the sequence of events that typically precedes a LOC incident. Using this knowledge, several proposals have been made to break this sequence through application of advanced techniques and methods to detect, mitigate, or recover from events that may lead to LOC. These methods often assume the presence of advanced vehicle systems, such as advanced avionic systems and automated aircraft control, which imply intended application to future aircraft systems. Many existing aircraft are not equipped with such systems, leaving a gap between existing aircraft capability and the proposed solutions to address LOC. This is particularly true for GA, where the average age of an active vehicle in the GA fleet is estimated by the FAA to be 40 years old, suggesting that the typical GA aircraft lack such advanced onboard systems.
The objective of this dissertation is to develop a methodology which enables the identification and mitigation of LOC for a typical GA fixed wing aircraft. This methodology will generate LOC envelopes for GA aircraft using existing understanding of LOC characteristics to enable to real-time evaluation of an aircraft's proximity to LOC conditions. This evaluation will be informed by aircraft data produced through collection of flight data parameters with personal electronic devices and estimation of any necessary aircraft states and pilot controls. Estimation of necessary and unobserved aircraft states will be achieved using existing filtering techniques, while the pilot control actions will be estimated using a combination of novel techniques developed within this dissertation. Finally, the methodology will aid in recovery of the aircraft in the event of LOC through synthesis of LOC recovery strategies which are proposed to be communicated to a human pilot through aural cues. The various aspects of this methodology will be tested through experimentation using flight simulation which will gauge to sensitivity of the methodology to various sources of uncertainty and estimate the efficacy of this methodology in mitigating LOC events.
Committee Members:
Professor Dimitri Mavris
Professor Daniel Schrage
Dr. Imon Chakraborty
