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Atmospheric turbulence effects on stellar irradiance and phase, discussing electro-optical recording technique and computer generated statistical data
The random process used to model atmospheric turbulence in aircraft response problems is examined. The first, second, and higher order probability density and characteristic functions were developed. The concepts of the Press model lead to an approximate procedure for the analysis of the response of linear dynamic systems to a class of non-Gaussian random processes. The Press model accounts for both the Gaussian and non-Gaussian forms of measured turbulence data. The nonstationary aspects of measured data are explicitly described by the transition properties of the random process. The effects of the distribution of the intensity process upon calculated exceedances are examined. It is concluded that the press model with a Gaussian intensity distribution gives a conservative prediction of limit load values.
A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.
A theory which gives statistical predictions for how often sonic booms propagating through the earth's turbulent boundary layer will encounter caustics, given the spectral properties of the atmospheric turbulence, is outlined. The theory is simple but approximately accounts for the variation of ray tube areas along ray paths. This theory predicts that the variation of ray tube areas is determined by the product of two similar area factors, psi (x) and phi (x), each satisfying a generic harmonic oscillator equation. If an area factor increases the peak acoustic pressure decreases, and if the factor decreases the peak acoustic pressure increases. Additionally, if an area factor decreases to zero and becomes negative, the ray has propagated through a caustic, which contributes a phase change of 90 degrees to the wave. Thus, it is clear that the number of times that a sonic boom wave passes through a caustic should be related to the distorted boom waveform received on the ground. Examples are given based on a characterization of atmospheric turbulence due to the structure function of Tatarski as modified by Crow.
Power spectrum measurements of atmospheric turbulence in severe storms and cumulus clouds
Effects of atmospheric turbulence on optical equipment in prelaunch alignment of missile guidance systems
Measurements of atmospheric turbulence obtained from airplane flights through cumulus clouds and thunderstorms
Light rigid civil aircraft response to continuous atmospheric turbulence estimated using two rigid body degrees of freedom method for vertical and lateral gusts
Light aircraft lateral and longitudinal response to atmospheric turbulence, presenting equations and charts for design load calculations
Light rigid civil aircraft response to continuous atmospheric turbulence estimated using two rigid body degrees of freedom method for vertical and lateral gusts
Atmospheric turbulence effects on sonic boom rise times by statistical theory
A method that produces realistic simulations of atmospheric turbulence is developed and analyzed. The procedure makes use of a generalized spectral analysis, often called a proper orthogonal decomposition or the Karhunen-Loeve expansion. A set of criteria, emphasizing a realistic appearance, a correct spectral shape, and non-Gaussian statistics, is selected in order to evaluate the model turbulence. An actual turbulence record is analyzed in detail, providing both a standard for comparison and input statistics for the generalized spectral analysis. The simulation utilizes the eigenfunction-expansion procedure to produce preliminary time histories of the three velocity components simultaneously. It is found that important cross-statistical features are reasonably well-behaved.
Method for estimation of atmospheric turbulence encountered by airplanes utilizes wealth of data captured by multichannel digital flight-data recorders and air-traffic-control radar. Developed as part of continuing effort to understand how airplanes respond to such potentially hazardous phenomena as: clear-air turbulence generated by destabilized wind-shear layers above mountains and thunderstorms, and microbursts (intense downdrafts striking ground), associated with thunderstorms. Reconstructed wind fields used to predict and avoid future hazards.
Crow instability can develop in most atmospheric turbulence levels, however, the ring vortices may not form in extremely strong turbulence cases due to strong dissipation of the vortices. It appears that strong turbulence tends to accelerate the occurrences of Crow instability. The wavelength of the most unstable mode is estimated to be about 5b(sub 0), which is less than the theoretical value of 8.6b(sub 0) (Crow, 1970) and may be due to limited domain size and highly nonlinear turbulent flow characteristics. Three-dimensional turbulence can decay wake vortices more rapidly. Axial velocity may be developed by vertical distortion of a vortex pair due to Crow instability or large turbulent eddy motion. More experiments with various non-dimensional turbulence levels are necessary to get useful statistics of wake vortex behavior due to turbulence. Need to investigate larger turbulence length scale effects by enlarging domain size or using grid nesting.
Atmospheric turbulence produces high frequency accelerations in aircraft, typically greater than the response to pilot input. Motion system equipped flight simulators must present cues representative of the aircraft response to turbulence in order to maintain the integrity of the simulation. Currently, turbulence motion cueing produced by flight simulator motion systems has been less than satisfactory because the turbulence profiles have been attenuated by the motion cueing algorithms. This report presents a new turbulence motion cueing algorithm, referred to as the augmented turbulence channel. Like the previous turbulence algorithms, the output of the channel only augments the vertical degree of freedom of motion. This algorithm employs a parallel aircraft model and an optional high bandwidth cueing filter. Simulation of aeroelastic effects is also an area where frequency content must be preserved by the cueing algorithm. The current aeroelastic implementation uses a similar secondary channel that supplements the primary motion cue. Two studies were conducted using the NASA Langley Visual Motion Simulator and Cockpit Motion Facility to evaluate the effect of the turbulence channel and aeroelastic model on pilot control input. Results indicate that the pilot is better correlated with the aircraft response, when the augmented channel is in place.
A non-Gaussian model of atmospheric turbulence is presented and analyzed. The model is restricted to the regions of the atmosphere where the turbulence is steady or continuous, and the assumptions of homogeneity and stationarity are justified. Also spatial distribution of turbulence is neglected, so the model consists of three independent, stationary stochastic processes which represent the vertical, lateral, and longitudinal gust components. The non-Gaussian and Gaussian models are compared with experimental data, and it is shown that the Gaussian model underestimates the number of high velocity gusts which occur in the atmosphere, while the non-Gaussian model can be adjusted to match the observed high velocity gusts more satisfactorily. Application of the proposed model to aircraft response is investigated, with particular attention to the response power spectral density, the probability distribution, and the level crossing frequency. A numerical example is presented which illustrates the application of the non-Gaussian model to the study of an aircraft autopilot system. Listings and sample results of a number of computer programs used in working with the model are included.
The explanation for the difference between simulation and the zero-order theory for heterodyne lidar returns in a turbulent atmosphere proposed by Belmonte and Rye is incorrect. The theoretical expansion is not developed under a square- law-structure function approximation (random wedge atmosphere). Agreement between the simulations and the zero-order term of the theoretical expansion is produced for the limit of statistically independent paths (bi-static operation with large transmitter-receiver separation) when the simulations correctly include the large-scale gradients of the turbulent atmosphere.
Results from an outdoor hover test of a full-scale Lynx tail rotor are presented. The investigation was designed to further the understanding of the acoustics of an isolated tail rotor hovering out-of-ground effect in atmospheric turbulence, without the effects of the main rotor wake or other helicopter components. Measurements include simultaneous rotor performance, noise, inflow, and far-field atmospheric turbulence. Results with grid-generated inflow turbulence are also presented. The effects of turbulence ingestion on rotor noise are quantified. Turbulence ingestion noise is found to be the dominant noise mechanism at locations near the rotor axis. At these locations, the sound radiated by the hovering rotor increases with both increasing atmospheric wind speed and ingested rms turbulent velocity.