Optimization of the NCAR in situ turbulence measurement algorithm

Robinson, P.; Buck, Bill K.; Bowles, Roland L.; Boyd, D. W.; Cornman, Larry

doi:10.2514/6.2000-492

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…The initial flight experiments were conducted during November and December of 2000. The aircraft, a B-757, was equipped with in situ sensors for wind, temperature and acceleration measurements 16 , and an airborne Doppler radar for forward-looking turbulence detection. During these flights, both radar and in situ data were collected for events ranging from smooth air to severe turbulence.…”

Section: The Flight Experimentsmentioning

confidence: 99%

“…The in situ turbulence measurements were quantified in terms of the peak normal load acceleration (∆n) and the root mean square (RMS) of the normal load acceleration, σ ∆n . 16 Measurements of σ ∆n exceeding 0.3 constitutes severe turbulence and is equivalent to peak normal load accelerations (∆n) exceeding one g. 21,22 An event was classified as significant turbulence if it was moderate or worse, i.e. σ ∆n ≥ 0.20.…”

Section: The Flight Experimentsmentioning

confidence: 99%

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Meteorology associated with turbulence encounters during NASA's Fall-2000 flight experiments

Hamilton

Proctor²

2002

40th AIAA Aerospace Sciences Meeting &Amp; Exhibit

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Initial flight experiments have been conducted to investigate convectively induced turbulence and to test technologies for its airborne detection. Turbulence encountered during the experiments is described with sources of data measured from in situ sensors, groundbased and airborne Doppler radars, and aircraft video. Turbulence measurements computed from the in situ system were quantified in terms of RMS normal loads (σ ∆n), where 0.20 g ≤ σ ∆n ≤ 0.30 g is considered moderate and σ ∆n > 0.30 g is severe. During two flights, 18 significant turbulence encounters (σ ∆n ≥ 0.20 g) occurred in the vicinity of deep convection; 14 moderate and 4 severe. In all cases, the encounters with turbulence occurred along the periphery of cumulus convection. These events were associated with relatively low values of radar reflectivity, i.e. RRF < 35 dBz, with most levels being below 20 dBz. The four cases of severe turbulence occurred in precipitation and were centered at the interface between a cumulus updraft turret and a downwind downdraft. Horizontal gradients of vertical velocity at this interface were found to be strongest on the downwind side of the cumulus turrets. Furthermore, the greatest loads to the aircraft occurred while flying along, not orthogonal to, the ambient environmental wind vector. During the two flights, no significant turbulence was encountered in the clear air (visual meteorological conditions), not even in the immediate vicinity of the deep convection.

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Section: The Flight Experimentsmentioning

confidence: 99%

Section: The Flight Experimentsmentioning

confidence: 99%

Meteorology associated with turbulence encounters during NASA's Fall-2000 flight experiments

Hamilton

Proctor²

2002

40th AIAA Aerospace Sciences Meeting &Amp; Exhibit

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“…The grid on wing-tail combination is generated beforehand. In the algorithm loop, the measured flight parameters are used to obtain turbulence components by Equation (2) and further local velocity is obtained by Equation (18). The parameters shown in Table 1 function as the data input.…”

Section: Acceleration-based Edr Estimationmentioning

confidence: 99%

“…The linear model or fitting function cannot accurately describe the acceleration response in turbulence. Furthermore, restricted by the turbulence-only excitation, these methods are unable to distinguish the acceleration change induced by aircraft maneuvers or turbulence; thus, the EDR values obtained are easily be affected by control surface deflections [18].…”

Section: Introductionmentioning

confidence: 99%

Acceleration-Based In Situ Eddy Dissipation Rate Estimation with Flight Data

Gao

Wang

Qi³

et al. 2020

Atmosphere

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Inducing civil aviation aircraft to bumpiness, atmospheric turbulence is a typical risk that seriously threatens flight safety. The Eddy Dissipation Rate (EDR) value, as an aircraft-independent turbulence severity indicator, is estimated by a vertical wind-based or aircraft vertical acceleration-based algorithm. Based on the flight data of civil aviation aircraft, the vertical turbulence component is obtained as the input of both algorithms. A new method of computing vertical acceleration response in turbulence is put forward through the Unsteady Vortex Lattice Method (UVLM). The lifting surface of the target aircraft is assumed to be a combination of wing and horizontal tail in a turbulent flight scenario. Vortex rings are assigned on the mean camber surface, forming a non-planar UVLM, to further improve the accuracy. Moreover, the neighboring vortex lattices are placed as close as possible to the structural edge of control surfaces. Thereby, a complete algorithm for estimating vertical acceleration and in situ EDR value from Quick Access Recorder (QAR) flight data is proposed. Experiments show that the aerodynamic performance is computed accurately by non-planar UVLM. The acceleration response by non-planar UVLM is able to track the recorded acceleration data with higher accuracy than that of the linear model. Different acceleration responses at different locations are also obtained. Furthermore, because the adverse effects of aircraft maneuvers are separated from turbulence-induced aircraft bumpiness, the new acceleration-based EDR algorithm shows better accuracy and stability.

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Relationship Between Vortex Meander and Ambient Turbulence

Rossow

Meyn

2006

6th AIAA Aviation Technology, Integration and Operations Conference (ATIO)

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Optimization of the NCAR in situ turbulence measurement algorithm

Cited by 3 publications

References 2 publications

Meteorology associated with turbulence encounters during NASA's Fall-2000 flight experiments

Meteorology associated with turbulence encounters during NASA's Fall-2000 flight experiments

Acceleration-Based In Situ Eddy Dissipation Rate Estimation with Flight Data

Relationship Between Vortex Meander and Ambient Turbulence

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