Contributions to the Characterization and Mitigation of Rotorcraft Brownout

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Rotorcraft brownout, the condition in which the flow field of a rotorcraft mobilizes sediment from the ground to generate a cloud that obscures the pilot's field of view, continues to be a significant hazard to civil and military rotorcraft operations. This dissertation presents methodologies for: (i) the systematic mitigation of rotorcraft brownout through operational and design strategies and (ii) the quantitative characterization of the visual degradation caused by a brownout cloud.

In Part I of the dissertation, brownout mitigation strategies are developed through simulation-based brownout studies that are mathematically formulated within a numerical optimization framework. Two optimization studies are presented. The first study involves the determination of approach-to-landing maneuvers that result in reduced brownout severity. The second study presents a potential methodology for the design of helicopter rotors with improved brownout characteristics. The results of both studies indicate that the fundamental mechanisms underlying brownout mitigation are aerodynamic in nature, and the evolution of a ground vortex ahead of the rotor disk is seen to be a key element in the development of a brownout cloud.

In Part II of the dissertation, brownout cloud characterizations are based upon the Modulation Transfer Function (MTF), a metric commonly used in the optics community for the characterization of imaging systems. The use of the MTF in experimentation is examined first, and the application of MTF calculation and interpretation methods to actual flight test data is described. The potential for predicting the MTF from numerical simulations is examined second, and an initial methodology is presented for the prediction of the MTF of a brownout cloud. Results from the experimental and analytical studies rigorously quantify the intuitively-known facts that the visual degradation caused by brownout is a space and time-dependent phenomenon, and that high spatial frequency features, i.e., fine-grained detail, are obscured before low spatial frequency features, i.e., large objects. As such, the MTF is a metric that is amenable to Handling Qualities (HQ) analyses.