Student Name: Yohan Auguste

Advisor: Dr. Dimitri Mavris

Milestone: PhD Thesis Proposal

Degree Program: Aerospace Engineering

Title: Development of A Simulator Based Training Framework for Autorotation Safety Improvements

Abstract: Commercial aviation in the U.S has experienced decades of steadily improving safety standards, culminating in an extremely safe operation today. General Aviation (GA) has also seen safety improvements; however, accident rates remain significantly higher than those observed in commercial aviation. Within GA, powerplant failure accidents remain a major concern, ranking as the second highest cause of fatalities. In rotorcraft operations in particular, emergency procedures following engine failure—specifically autorotation—present pilots with challenging, high-workload situations characterized by limited time and constrained decision-making options. Autorotation-related mishaps account for a substantial portion of rotorcraft incidents, representing nearly one-third of all accidents. While pilot training is a critical requirement for improving safety outcomes, autorotation training itself carries inherent risk, with training-related accidents accounting for approximately 40% of all autorotation accidents. This combination of high training risk and the need for thorough skill development highlights the necessity for alternative training approaches. Simulator-based training programs offer a viable solution; however, to be effective, a structured simulator training framework must be developed. A critical component of such a framework is the provision of objective assessment criteria and integrated feedback systems to enable efficient training and ensure that performance targets are consistently achieved. This thesis proposes a data-driven approach to support the development of assessment criteria for each phase of autorotation, focusing on the evaluation of critical pilot performance indicators that are not adequately addressed in current training standards or that rely on inconsistent, or subjective judgment calls. Additionally, an integrated feedback mechanism is proposed to enhance training efficiency and reinforce correct pilot responses. Together these proposals enable the implementation of the autorotation training framework by providing the key missing components for proper assessment and feedback that are required for a successful simulator training program. 

Date and time: 2026-05-15, 2 PM

Location: CoVE Weber SST II

Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Marilyn Smith, School of Aerospace Engineering
Dr. Daniel Schrage, School of Aerospace Engineering
Dr. Alexia Payan, School of Aerospace Engineering
Mr. Charles Johnson, FAA