Identification of Dynamic Rollover Precursors for Enhanced Helicopter Flight Data Monitoring (HFDM) Applications

Author(s)
Baali, Ilias
Johnson, Charles C.
Advisor(s)
Editor(s)
Associated Organization(s)
Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
Series
Supplementary to:
Abstract
Dynamic rollovers represent a major hazard for helicopters during near-ground operations, often resulting in significant aircraft damage and passenger injuries. To improve safety in operations, recent studies have focused on developing a Helicopter Flight Data Monitoring framework to provide data-driven insights on operational safety. This work contributes to that effort by proposing an approach to identify precursors to dynamic rollovers. According to NTSB reports, approximately 60% of such incidents occur during in-flight phases like hover, hover-taxi, or landing. To capture the complex non-linear dynamics of helicopters, physics-based simulations were conducted to estimate a first hitting time metric, defined as the time until blade-ground contact, across a wide range of initial conditions for an inflight initial state of the helicopter. Eight parameters were identified as driving the first hitting time, and a probabilistic model was created to predict the distribution of that metric for different values of those parameters. Based on the predicted distributions, a risk-based metric was derived to robustly assess the risk of dynamic rollover and identify safer operational boundaries.
Sponsor
Sponsored by the FAA, GR00030231
Date
2025-05
Extent
Resource Type
Text
Resource Subtype
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