A Methodology to Improve the Proactive Mitigation of Helicopter Accidents Related to Loss of Tail Rotor Effectiveness

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Zanella, Paola
Mavris, Dimitri N.
Prasad, Jonnalagadda V. R.
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Loss of tail rotor effectiveness (LTE) has been recognized to be a major contributing factor in several helicopter accidents where pilots lost directional control. However, it has been noticed that different definitions of this phenomenon exist in the rotorcraft community. Further, the somewhat imprecise representation of LTE in some flight training simulators has led to its low awareness, placing pilots at a much higher risk for potential accidents. One significant method to specifically address those gaps and support rotorcraft safety involves the proactive mitigation of LTE via the analysis of flight data within the Helicopter Flight Data Monitoring (HFDM) program. Through this program, the pilots receive constant flight evaluation reports to promote improved LTE risk evaluations. The main method used for flight data analysis is the detection of safety metrics, i.e., predefined hazardous flight conditions. Nevertheless, a sufficiently reliable LTE safety metric still does not exist, leading to false or missed detections that degrade the quality of the overall safety analysis. The objective of this thesis is to formulate a methodology to enhance the detection capability of the proximity to LTE within the HFDM program. This promotes the awareness of LTE within the rotorcraft community while supporting the proactive mitigation of helicopter accidents related to this critical helicopter safety threat. An alternative approach is used to develop a more reliable LTE safety metric, using a combination of physics-based simulations and machine learning techniques. First, a physics-based investigation is performed to enhance the understanding of the nature of the LTE. A more comprehensive LTE definition is proposed and analyzed, including three different aspects that can lead to LTE behavior, i.e., loss of weathercock stability, running out of pedal (tail rotor collective) for trim, and tail rotor vortex ring state. The modeling of the flight dynamics of each phenomenon is individually analyzed to ensure an accurate physics-based representation of LTE. Further, the parameters that support the detection of LTE are investigated to enable the recognition and classification of each LTE phenomenon in simulation results. Ultimately, a physics-based investigation of the aircraft flight envelope is combined with the application of supervised learning techniques to develop the predictive models of the different LTE phenomena. This provides the operator with a physics-based LTE safety metric designed to detect the proximity to LTE without the need for a simulation model. The methodology is implemented using a generic nonlinear helicopter simulation model. To verify the enhanced capabilities of the final methodology, the physics-based LTE safety metric is compared against the LTE metric currently used within the HFDM program. The results confirm the improved detection of the proximity to LTE, validating the overarching hypothesis of this research and satisfying the research objective.
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