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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Method has been developed to improve the lower bound of the first excursion probability that can apply to the problem with either constant or time-dependent barriers. The method requires knowledge of the joint density function of the random process at two arbitrary instants.
Random processes in daily variations of geomagnetic vector during summertime quiet days by statistical investigations
Boundary value problem for elliptic-parabolic partial differential equations in theory of random processes, obtaining analytical solution in terms of hypergeometric functions
Stable linear system /shaping filter/ synthesis transforming stationary white noise into random process having given covariance function
N-dimensional theorem for evaluating time continuous channel capacity or rate distortion function of random process
The Space Shuttle, being an hybrid – an airplane and a launch vehicle – represents the greatest challenge that the dynamicist and the aeroelastician have faced. Some specific problem areas related to the Space Shuttle are listed on figure 1. Dynamics and aeroelasticity envelop many disciplines, including aerodynamics, vibration, random processes, structures, fluid flow, mechanics, etc., but, of more importance, they involve the interaction and coupling of many of these various disciplines. Fundamentally, we are concerned with structural integrity and safe flight, i.e., trying to ensure that the vehicle will remain structurally intact as well as function properly in the presence of the many faceted dynamic environment. A new area which may have an impact on our task is the effect of the high temperature environment. In the past, we have been able to successfully decouple the temperature effects from our problem formulation. For the Space Shuttle, this problem must be closely reexamined. As has been pointed out in the opening remarks of the Conference, the Dynamics and Aeroelasticity Technology Group comprises one of several technology groups which are attempting to provide the necessary research to support a successful and safe vehicle. The group has members from most of the NASA Centers as well as from the Air Force groups. We meet periodically to review ongoing work, search for new problem areas; and we are constantly updating and revising our program. The group is organized into three panels as shown on figure 2: a panel on Dynamic Loads and Response, one on Aeroelasticity, and one on Flight Dynamics and Environment. The Conference papers accordingly have been grouped in these same three areas, with each Panel Chairman acting as moderator for his particular session.
Monograph on state variable approach to continuous estimation of random processes with applications to analog communication theory
Random process model and feature reduction of spontaneous and alpha frequency electroencephalograms
Random process theory method for estimating response of flexible airplanes to atmospheric turbulence
Flexible bar as spatial filter for measuring wave number-frequency spectra of distributed random processes
Nonstationary colored noise linear shaping filter to transform white noise into nonstationary random process with specified covariance function
Structural dynamic responses as nonstationary narrow band random process, establishing peak values distribution functions with frequency interpretation
An analysis is made of steady-state and non-steady-state methods for the measurement of panel damping. Particular emphasis is placed on the use of random process techniques in conjunction with digital data reduction methods. The steady-state methods considered use the response power spectral density, response autocorrelation, excitation-response crosspower spectral density, or single-sided Fourier transform (SSFT) of the response autocorrelation function. Non-steady-state methods are associated mainly with the use of rapid frequency sweep excitation. Problems associated with the practical application of each method are evaluated with specific reference to the case of a panel exposed to a turbulent airflow, and two methods, the power spectral density and the single-sided Fourier transform methods, are selected as being the most suitable. These two methods are demonstrated experimentally, and it is shown that the power spectral density method is satisfactory under most conditions, provided that appropriate corrections are applied to account for filter bandwidth and background noise errors. Thus, the response power spectral density method is recommended for the measurement of the damping of panels exposed to a moving airflow.
Computer simulation was performed to estimate displacements and bending moments experienced by the SKYLAB 1B vehicle on the launch pad due to atmospheric winds. The vehicle was assumed to be a beam-like structure represented by a finite number of generalized coordinates. Wind flow across the vehicle was treated as a nonhomogeneous, stationary random process. Response computations were performed by the assumption of simple strip theory and application of generalized harmonic analysis. Displacement and bending moment statistics were obtained for six vehicle propellant loading conditions and four representative reference wind profile and turbulence levels. Means, variances and probability distributions are presented graphically for each case. A separate analysis was performed to indicate the influence of wind gradient variations on vehicle response statistics.
A procedure for recursively estimating images that are characterized statistically by the mean and correlation functions associated with the random process representing the brightness level is proposed for the case where the images are corrupted by additive noise. First, a dynamic model is developed with a response characteristic which matches that of the scanner output (the input of the estimator is the output of a horizontal line scanner) in a statistical sense. Such models have the form of an ordinary differential or difference equation with white noise input. An insignificant approximation is introduced by using a constant-coefficient model. The appropriate model is a vector valued difference equation with the solution representing a vector Markov process. The next step is to obtain the minimum mean square estimate of the image by using a Kalman filter. Since the image estimation is an interpolation problem, two successive runs over the observation are performed in opposite directions and the resultant estimates are averaged. Examples are included for illustration.
A method is proposed for dealing with the divergence phenomenon problem encountered in applications of minimum-variance recursive estimators when the error covariance calculated by the estimator becomes inconsistent with the actual error covariance. The proposed method differs from previous ones in that the state model and statistics are accepted as given. The form of the optimal estimator is used, but a constant check is made on the consistency of the calculated and actual error covariances. The method is independent of the source of error, whether it be inaccuracies in the system model, incorrect values of the a priori and random process statistics, approximations required in the case of nonlinear systems, or computational roundoff. Several simulated examples, in which inconsistencies in the calculated and actual error covariances exist, show a significant improvement in the performance of the estimator when the given procedure is applied.
The enhancement of images that are characterized only by statistical data where the picture contains additive noise is considered. The random process representing the output of the scanner is characterized by the output of a dynamic system with white noise input. The dynamic system describes a first-order vector-Markov process. The procedure of Kalman filtering is then utilized to recursively determine the minimum mean-square error estimate of the image. The result is then extended to obtain the smoothing of the data.
The shadowing function, defined as the probability that a point on a rough surface will be illuminated by radiation from a source at fixed height above the surface, is considered. An exact expression for this probability is derived and evaluated approximately when the surface elevation is a normal random process. The effect of surface correlation is considered and shown to be appreciable. Several numerical computations of the shadowing function are presented.