Brownout Cloud Characterization Using the Modulation Transfer Function

Tritschler, John; Celi, Roberto

doi:10.4050/jahs.58.012001

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…This metric could be estimated [43] from the control dwell fraction, which is the fraction of the duration of the piloting task in which the visual cues are sufficient to perform the task. Sufficient cues could be defined in terms of the modulation transfer function (MTF) [42], which is a measure of the loss of visibility caused by the brownout cloud [44][45][46], and linked to an equation like Eq. (11) with the MTF replacing the number of particles n P .…”

Section: B Objective Functionmentioning

confidence: 99%

Methodology for Rotorcraft Brownout Mitigation Through Flight Path Optimization

Tritschler

Celi

Leishman

2014

Journal of Guidance, Control, and Dynamics

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A methodology is presented for the selection of approach-to-landing maneuvers that may result in improved brownout characteristics. The methodology is based upon a brownout metric that assesses the relative brownout cloud volume densities in critical regions of the pilot's field of view. The metric becomes the objective function of a procedure in which a typical visual approach profile is parameterized and optimized to minimize brownout in a representative landing maneuver. The optimization is constrained to avoid maneuvers that would be conducive to the onset of vortex ring state or would result in flight within the "avoid" regions of a typical helicopter height-velocity diagram. The analysis uses a free-vortex wake model and simulates the dynamics of the dust particles immersed in the rotor downwash. The results show that the optimal approach trajectories affect the resulting flowfield, particularly the development of a ground vortex ahead of the rotor disk, which influences the rate of development, size, and volume density of the brownout cloud. The results are compared with prior experimental results, and potential operational interpretations of the outcomes are examined. Nomenclature A= rotor disk area, πR 2 , ft 2 BX = objective function, Eq. (12) bX; t = particle count in the "best" region of the pilot's field of view, Eq. (11) C T = rotor thrust coefficient, T∕ρAΩR 2 D = main rotor diameter, ft FX = additional design objective function gX = constraint equation, Eq.(2) H = Hessian matrix h = rotor hub height above ground, ft n ent = number of entrained particles n P = number of particles p app X = series of discrete points describing approach X p HV = series of discrete points describing the "avoid" region boundaries on a height-velocity diagram p VRS = series of discrete points describing flight regime boundaries where VRS may occur R = rotor radius, ft r = longitudinal range from landing point, ft r pd = longitudinal range from landing point at which the peak deceleration occurs, ft S = unit vector T = rotor thrust, lb V = forward velocity, ft∕s or kt V c = climb velocity, ft∕s v h = hover inflow velocity, ft∕s v 0 = initial (asymptotic) velocity, ft∕s or kt X = vector of design variables, γ v 0 r pd T X u = aircraft stability derivative, ∂X∕∂u γ = approach angle, deg ϵ = tolerance value for defining behavior constraints, Eqs. (15) and (16) θ = aircraft pitch angle, deg θ P , ϕ P , ρ P = particle location (azimuth, elevation, distance) in a spherical coordinate systemfluid density, slugs∕ft 3 χ = wake skew angle, deg Ω = rotational frequency, rad∕s Subscripts app = approximation max = maximum allowable value (upper bound) min = minimum allowable value (lower bound) Superscript = value for optimum configuration

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Section: B Objective Functionmentioning

confidence: 99%