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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Neural Network (NN) Retrievals of Stratocumulus Cloud Properties Using Multiangle Polarimetric Observations During ORACLES

The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the SouthEast Atlantic during the Austral Spring for three consecutive years from 20162018. The study area encompasses one of the Earths three semipermanent subtropical Stratocumulus (Sc) cloud decks,and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), butstill challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe anew algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER2and P3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrievalscheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a morerealistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloudretrievals from ORACLES, compared with standard RSP low-levelcloud retrieval method that has been validated against in situ observations.

Cloud-aerosol↗
NASA NTRS1976

Macroscopic study of time unsteady noise of an aircraft engine during static tests

Static tests of aircraft engines can exhibit greater than 10 db random unsteadiness of tone noise levels because flow disturbances that prevail near test site facilities are ingested. Presumably such changes are related to installation and test site features. Some properties of unsteady noise observed during tests of a Lycoming YF-102 turbofan engine are presented. Time and spatial variations in tone noise obtained from closely spaced far field and inlet duct microphones are displayed. Long to extremely short intermittent tone bursts are observed. Unsteadiness of the tone, its harmonics, and the broadband noise show little similarity. In the far field, identity of tone bursts is retained over a directivity angle of less than 10 deg. In the inlet duct, tone bursts appear to propagate axially but exhibit little circumferential similarity. They show only slight relationship to tone bursts observed in the far field. The results imply an intermittent generation of random mixtures of propagating duct modes.

Clark, B. J.↗
NASA NTRS1976

Macroscopic study of time unsteady noise of an aircraft engine during static tests

Static tests of aircraft engines can exhibit greater than 10 dB random unsteadiness of tone noise levels because flow disturbances that prevail near test site facilities are ingested. Presumably such changes are related to installation and test site features. This paper presents some properties of unsteady noise observed at a NASA-Lewis facility during tests of a Lycoming YF-102 turbofan engine. Time and spatial variations in tone noise obtained from closely spaced far-field and inlet duct microphones are displayed. Long (0.5 sec) to extremely short (0.001 sec) intermittent tone bursts are observed. Unsteadiness of the tone, its harmonics, and the broadband noise show little similarity. In the far-field, identity of tone bursts is retained over a directivity angle of less than 10 deg. In the inlet duct, tone bursts appear to propagate axially but exhibit little circumferential similarity. They show only slight relationship to tone bursts observed in the far field. The results imply an intermittent generation of random mixtures of propagating duct modes.

Clark, B. J.↗
NASA NTRS1991

Sources of noise in magneto-optical readout

The various sources of noise which are often encountered in magneto-optical readout systems are analyzed. Although the focus is on magneto-optics, most sources of noise are common among the various optical recording systems and one can easily adapt the results to other media and systems. A description of the magneto-optical readout system under consideration is given, and the standard methods and the relevant terminology of signal and noise measurement are described. The characteristics of thermal noise, which originates in the electronic circuitry of the readout system, are described. The most fundamental of all sources of noise, the shot noise, is considered, and a detailed account of its statistical properties is given. Shot noise, which is due to random fluctuations in photon arrival times, is an ever-present noise in optical detection. Since the performance of magneto-optical recording devices in use today is approaching the limit imposed by the shot noise, it is important that the reader have a good grasp of this particular source of noise. A model for the laser noise is described, and measurement results which yield numerical values for the strength of the laser power fluctuations are presented. Spatial variations of the disk reflectivity and random depolarization phenomena also contribute to the overall level of noise in readout; these and related issues are treated. Numerical simulation results describing some of the more frequently encountered sources of noise which accompany the recorded waveform itself, namely, jitter noise and signal-amplitude fluctuation noise are presented.

Mansuripur, M.↗
NASA NTRS1971

Noise thermometry with the Josephson effect

Noise thermometry by Josephson effect, demonstrating self excitation random frequency modulation with thermal noise and thermometer having microkelvin noise temperature measurement capability

Kamper, R. A.↗
DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗
NASA NTRS1998

Advanced Water Vapor Lidar Detection System

In the present water vapor lidar system, the detected signal is sent over long cables to a waveform digitizer in a CAMAC crate. This has the disadvantage of transmitting analog signals for a relatively long distance, which is subjected to pickup noise, leading to a decrease in the signal to noise ratio. Generally, errors in the measurement of water vapor with the DIAL method arise from both random and systematic sources. Systematic errors in DIAL measurements are caused by both atmospheric and instrumentation effects. The selection of the on-line alexandrite laser with a narrow linewidth, suitable intensity and high spectral purity, and its operation at the center of the water vapor lines, ensures minimum influence in the DIAL measurement that are caused by the laser spectral distribution and avoid system overloads. Random errors are caused by noise in the detected signal. Variability of the photon statistics in the lidar return signal, noise resulting from detector dark current, and noise in the background signal are the main sources of random error. This type of error can be minimized by maximizing the signal to noise ratio. The increase in the signal to noise ratio can be achieved by several ways. One way is to increase the laser pulse energy, by increasing its amplitude or the pulse repetition rate. Another way, is to use a detector system with higher quantum efficiency and lower noise, on the other hand, the selection of a narrow band optical filter that rejects most of the day background light and retains high optical efficiency is an important issue. Following acquisition of the lidar data, we minimize random errors in the DIAL measurement by averaging the data, but this will result in the reduction of the vertical and horizontal resolutions. Thus, a trade off is necessary to achieve a balance between the spatial resolution and the measurement precision. Therefore, the main goal of this research effort is to increase the signal to noise ratio by a factor of 10 over the current system, using a newly evaluated, very low noise avalanche photo diode detector and constructing a 10 MHz waveform digitizer which will replace the current CAMAC system.

Elsayed-Ali, Hani↗
NASA NTRS1972

Bayesian recursive image estimation.

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.

Nahi, N. E.↗
NASA NTRS1976

Noise and vibration ride comfort criteria

A program is underway at Langley Research Center to develop a comprehensive ride quality model based upon the various physical and psychological factors that most affect passenger ride comfort. Two of the most important factors, namely, vibration and noise were studied to (1) determine whether composite or separate noise and vibration criteria are needed for the prediction of ride quality, (2) determine a noise correction for the previously-defined vibration criteria of the ride quality model, (3) assess whether these noise corrections depend on the nature of the vibration stimuli, i.e., deterministic as opposed to random, and (4) specify noise-vibration criteria for this combined environment. The stimuli for the study consisted of octave bands of noise centered at 500 or 2000 Hz and vertical vibrations composed of either 5 Hz sinusoidal vibration or random vibrations centered at 5 Hz and with a 5 Hz bandwidth. The noise stimuli were presented at levels ranging from ambient to 95 dB(A) and the vibrations at levels ranging from 0.02 to 0.13 g-rms.

Dempsey, T. K.↗
NASA NTRS1976

Noise and vibration ride comfort criteria

Two of the most important factors, namely, vibration and noise, were studied to (1) determine whether composite or separate noise and vibration criteria are needed for the prediction of ride quality, (2) determine a noise correction for the previously-defined vibration criteria of the ride quality model, (3) assess whether these noise corrections depend on the nature of the vibration stimuli, i.e., deterministic as opposed to random, and (4) specify noise-vibration criteria for this combined environment. The stimuli for the study consisted of octave bands of noise centered at 500 or 2,000 Hz and vertical vibrations composed of either 5 Hz sinusoidal vibration or random vibrations centered at 5 Hz and with a 5 Hz bandwidth. The noise stimuli were presented at levels ranging from ambient to 95 dB(A) and the vibrations at levels ranging from 0.02 to 0.13g rms.

Dempsey, T. K.↗
NASA NTRS1993

Reduced electrical bandwidth receivers for direct detection 4-ary PPM optical communication intersatellite links

One of the major sources of noise in a direct detection optical communication receiver is the shot noise due to the quantum nature of the photodetector. The shot noise is signal dependent and is neither Gaussian nor wide sense stationary. When a photomultiplier tube (PMT) or an avalanche photodiode (APD) is used, there is also a multiplicative excess noise due to the randomness of the internal photodetector gain. Generally speaking, the radio frequency (RF) communication theory cannot be applied to direct detection optical communication systems because noise in RF communication systems is usually additive and Gaussian. A receiver structure which is mathematically optimal for signal dependent shot noise is derived. Several suboptimal receiver structures are discussed and compared with the optimal receiver. The objective is to find a receiver structure which is easy to implement and gives close to optimal performance.

Davidson, Frederic M.↗
NASA NTRS2017

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Grauer, Jared A.↗
NASA NTRS1993

Multi-beam range imager for autonomous operations

For space operations from the Space Station Freedom the real time range imager will be very valuable in terms of refuelling, docking as well as space exploration operations. For these applications as well as many other robotics and remote ranging applications, a small potable, power efficient, robust range imager capable of a few tens of km ranging with 10 cm accuracy is needed. The system developed is based on a well known pseudo-random modulation technique applied to a laser transmitter combined with a novel range resolution enhancement technique. In this technique, the transmitter is modulated by a relatively low frequency of an order of a few MHz to enhance the signal to noise ratio and to ease the stringent systems engineering requirements while accomplishing a very high resolution. The desired resolution cannot easily be attained by other conventional approaches. The engineering model of the system is being designed to obtain better than 10 cm range accuracy simply by implementing a high precision clock circuit. In this paper we present the principle of the pseudo-random noise (PN) lidar system and the results of the proof of experiment.

Marzwell, Neville I.↗
NASA NTRS1972

Performance of correlation receivers in the presence of impulse noise.

An impulse noise model, which assumes that each noise burst contains a randomly weighted version of a basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. Unlike the performance results for additive white Gaussian noise, it is shown that the error performance for impulse noise is affected by the choice of signal-set basis function, and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy. Furthermore, it is demonstrated that the correlation-receiver error performance can be improved by inserting a properly specified nonlinear device prior to the receiver input.

Moore, J. D.↗
NASA NTRS1971

Characterization of impulse noise and analysis of its effect upon correlation receivers

A noise model is formulated to describe the impulse noise in many digital systems. A simplified model, which assumes that each noise burst contains a randomly weighted version of the same basic waveform, is used to derive the performance equations for a correlation receiver. The expected number of bit errors per noise burst is expressed as a function of the average signal energy, signal-set correlation coefficient, bit time, noise-weighting-factor variance and probability density function, and a time range function which depends on the crosscorrelation of the signal-set basis functions and the noise waveform. A procedure is established for extending the results for the simplified noise model to the general model. Unlike the performance results for Gaussian noise, it is shown that for impulse noise the error performance is affected by the choice of signal-set basis functions and that Orthogonal signaling is not equivalent to On-Off signaling with the same average energy.

Houts, R. C.↗
NASA NTRS1973

Digital random-number generator

For binary digit array of N bits, use N noise sources to feed N nonlinear operators; each flip-flop in digit array is set by nonlinear operator to reflect whether amplitude of generator which feeds it is above or below mean value of generated noise. Fixed-point uniform distribution random number generation method can also be used to generate random numbers with other than uniform distribution.

Brocker, D. H.↗