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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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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Phasing the antennas of the Very Large Array (VLA) for reception of telemetry from Voyager 2 at Neptune encounter

The Very Large Array (VLA) radio telescope is being instrumented at 8.4 GHz to receive telemetry from Voyager 2 during its encounter with Neptune in 1989. The procedure in which the 27 antennas have their phases adjusted in near real time so that the signals from the individual elements of the array can be added coherently is examined. Calculations of the expected signal to noise ratio, tests of the autophasing process at the VLA, and off-line simulations of that process are all presented. Various possible procedures for adjusting the phases are considered. It is shown that the signal to noise ratio at the VLA is adequate for summing the signals from the individual antennas with less than 0.1 dB of loss caused by imperfect coherence among the antennas. Tropospheric variations during the summer of 1989 could cause enough loss of coherence to make the losses higher than 0.1 dB. Experiments show that the losses caused by the troposphere can probably be kept below 0.2 dB if the time delay inherent in the phase adjustment process is no longer than approx. 5 secs. This relatively small combining loss meets the goal estabished to minimize the bit error rate in the Voyager telemetry and implies adequate autophasing of the VLA.

Ulvestad, J. S.↗
NASA NTRS1978

Measurements of noise produced by flow past lifting surfaces

Wind tunnel studies have been conducted to determine the specific locations of aerodynamic noise production within the flow field about various lifting-surface configurations. The models tested included low aspect ratio shapes intended to represent aircraft flaps, a finite aspect ratio NACA 0012 wing, and a multi-element wing section consisting of a main section, a leading edge flap, and dual trailing edge flaps. Turbulence was induced on the models by surface roughness. Lift and drag were measured for the flap models. Hot-wire anemometry was used for study of the flap-model vortex roll-up. Apparent noise source distributions were measured by use of a directional microphone system, located outside the tunnel, which was scanned about the flow region to be analyzed under computer control. These distributions exhibited a diversity of pattern, suggesting that several flow processes are important to lifting-surface noise production. Speculation concerning these processes is offered.

Kendall, J. M.↗
DOE OSTI2021

DeepSZ: identification of Sunyaev–Zel’dovich galaxy clusters using deep learning

Galaxy clusters identified via the Sunyaev–Zel’dovich (SZ) effect are a key ingredient in multiwavelength cluster cosmology. In this paper, we present and compare three methods of cluster identification: the standard matched filter (MF) method in SZ cluster finding, a convolutional neural networks (CNN), and a ‘combined’ identifier. We apply the methods to simulated millimeter maps for several observing frequencies for a survey similar to SPT-3G, the third-generation camera for the South Pole Telescope. The MF requires image pre-processing to remove point sources and a model for the noise, while the CNN requires very little pre-processing of images. Additionally, the CNN requires tuning of hyperparameters in the model and takes cut-out images of the sky as input, identifying the cut-out as cluster-containing or not. We compare differences in purity and completeness. The MF signal-to-noise ratio depends on both mass and redshift. Our CNN, trained for a given mass threshold, captures a different set of clusters than the MF, some with signal-to-noise-ratio below the MF detection threshold. However, the CNN tends to mis-classify cut-out whose clusters are located near the edge of the cut-out, which can be mitigated with staggered cut-out. We leverage the complementarity of the two methods, combining the scores from each method for identification. The purity and completeness are both 0.61 for MF, and 0.59 and 0.61 for CNN. The combined method yields 0.60 and 0.77, a significant increase for completeness with a modest decrease in purity. We advocate for combined methods that increase the confidence of many low signal-to-noise clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Uncertainty amplification due to density/refractive index gradients in background-oriented schlieren experiments

Here, we theoretically analyze the effect of density/refractive index gradients on the measurement precision of background-oriented schlieren (BOS) experiments by deriving the Cramer–Rao lower bound (CRLB) for the 2D centroid estimation process. A model is derived for the diffraction limited image of a dot viewed through a medium containing density gradients that includes the effect of the experimental parameters such as the magnification and f-number. It is shown using the model that nonlinearities in the density gradient field lead to blurring of the dot image. This blurring amplifies the effect of image noise on the centroid estimation process, leading to an increase in the CRLB and a decrease in the measurement precision. The ratio of position uncertainties of a dot in the reference and gradient images is shown to be a function of the ratio of the dot diameters and dot intensities. We termed this parameter the amplification ratio (A F ), and a methodology for reporting position uncertainties in tracking-based BOS measurements is proposed. The theoretical predictions of the dot position estimation variance from the CRLB are compared to ray tracing simulations, and agreement is obtained. The uncertainty amplification is also demonstrated on experimental BOS images of flow induced by a spark discharge, where it is seen that regions of high amplification ratio correspond to regions of density gradients. This analysis elucidates the dependence of the position uncertainty on density and refractive index gradient-induced distortion parameters, provides a methodology for accounting its effect on uncertainty quantification and provides a framework for optimizing experiment design.

42 ENGINEERING↗
NASA NTRS2011

Link Analysis in the Mission Planning Lab

The legacy communications link analysis software currently used at Wallops Flight Facility involves processes that are different for command destruct, radar, and telemetry. There is a clear advantage to developing an easy-to-use tool that combines all the processes in one application. Link Analysis in the Mission Planning Lab (MPL) uses custom software and algorithms integrated with Analytical Graphics Inc. Satellite Toolkit (AGI STK). The MPL link analysis tool uses pre/post-mission data to conduct a dynamic link analysis between ground assets and the launch vehicle. Just as the legacy methods do, the MPL link analysis tool calculates signal strength and signal- to-noise according to the accepted processes for command destruct, radar, and telemetry assets. Graphs and other custom data are generated rapidly in formats for reports and presentations. STK is used for analysis as well as to depict plume angles and antenna gain patterns in 3D. The MPL has developed two interfaces with the STK software (see figure). The first interface is an HTML utility, which was developed in Visual Basic to enhance analysis for plume modeling and to offer a more user friendly, flexible tool. A graphical user interface (GUI) written in MATLAB (see figure upper right-hand corner) is also used to quickly depict link budget information for multiple ground assets. This new method yields a dramatic decrease in the time it takes to provide launch managers with the required link budgets to make critical pre-mission decisions. The software code used for these two custom utilities is a product of NASA's MPL.

McCarthy, Jessica A.↗
NASA NTRS1976

Multiplexor and sensor system tradeoff study

The influence of certain sensor parameters on the accuracy of information extracted from satellite image data is studied, using a digital processing flow to simulate the effects of the sensor parameters. The method employed was to select representative images; scan and digitize them; process the digital data to simulate the effects of presampling filters, instantaneous field of view (IFOV) size and shape, sampling rates, noise, and word length; record the processed data on film; evaluate the film images; and draw conclusions from the evaluations. The study showed that presampling filters are not required to suppress aliasing, that the choice of square and circular IFOV shapes is not important, and that increased horizontal and vertical sampling rates produce an increase in apparent resolution. Work with low-contrast targets revealed a definite maximum in the tradeoff between IFOV size and SNR.

Ferneyhough, D. G., Jr.↗
NASA NTRS1980

Production of 1.25 K He-4 without He-4 superfluid film

A refrigeration process is described which enables the production of a sub-gamma-point He-4 temperatures without the production of superfluid. The advantages of the process for zero gravity and low-noise refrigeration are described. The lowest temperature produced to date is 1.25 K. The process is also useful with other gases for refrigeration; the output temperature is selected by gas type.

Goebel, J. H.↗
NASA NTRS1988

AVIRIS data characteristics and their effects on spectral discrimination of rocks exposed in the Drum Mountains, Utah: Results of a preliminary study

Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over a geologically diverse field site and over a nearby calibration site were analyzed and interpreted in efforts to document radiometric and geometric characteristics of AVIRIS, quantify and correct for detrimental sensor phenomena, and evaluate the utility of AVIRIS data for discriminating rock types and identifying their constituent mineralogy. AVIRIS data acquired for these studies exhibit a variety of detrimental artifacts and have lower signal-to-noise ratios than expected in the longer wavelength bands. Artifacts are both inherent in the image data and introduced during ground processing, but most may be corrected by appropriate processing techniques. Poor signal-to-noise characteristics of this AVIRIS data set limited the usefulness of the data for lithologic discrimination and mineral identification. Various data calibration techniques, based on field-acquired spectral measurements, were applied to the AVIRIS data. Major absorption features of hydroxyl-bearing minerals were resolved in the spectra of the calibrated AVIRIS data, and the presence of hydroxyl-bearing minerals at the corresponding ground locations was confirmed by field data.

Bailey, G. B.↗
NASA NTRS1997

Image discrimination models predict detection in fixed but not random noise

By means of a two-interval forced-choice procedure, contrast detection thresholds for an aircraft positioned on a simulated airport runway scene were measured with fixed and random white-noise masks. The term fixed noise refers to a constant, or unchanging, noise pattern for each stimulus presentation. The random noise was either the same or different in the two intervals. Contrary to simple image discrimination model predictions, the same random noise condition produced greater masking than the fixed noise. This suggests that observers seem unable to hold a new noisy image for comparison. Also, performance appeared limited by internal process variability rather than by external noise variability, since similar masking was obtained for both random noise types.

NASA Center ARC↗
NASA NTRS1999

Microphone Array Phased Processing System (MAPPS): Version 4.0 Manual

A processing system has been developed to meet increasing demands for detailed noise measurement of individual model components. The Microphone Array Phased Processing System (MAPPS) uses graphical user interfaces to control all aspects of data processing and visualization. The system uses networked parallel computers to provide noise maps at selected frequencies in a near real-time testing environment. The system has been successfully used in the NASA Ames 7- by 10-Foot Wind Tunnel.

Watts, Michael E.↗
DOE OSTI2022

Physics-informed machine learning modeling for predictive control using noisy data

Due to the occurrence of over-fitting at the learning phase, the modeling of chemical processes via artificial neural networks (ANN) by using corrupted data (i.e., noisy data) is an ongoing challenge. Therefore, this work investigates the effect of both Gaussian and non-Gaussian noise on the performance of process-structure based recurrent neural networks (RNN) models, which take the form of partially-connected RNN models in this work, that are used to approximate a class of multi-input-multi-outputs nonlinear systems. Furthermore, two different techniques, specifically Monte Carlo dropout and co-teaching, are utilized in the development of partially-connected RNN models. Here, these two techniques are employed to reduce the over-fitting in ANNs when noisy data is used in the training process and, hence, to improve the open-loop accuracy as well as the closed-loop performance under a Lyapunov-based model predictive controller (MPC). Aspen Plus Dynamics, a well-known high-fidelity process simulator, is used to simulate a large-scale chemical process application in order to demonstrate the anticipated improvements in both open-loop approximation and closed-loop controller performance in the presence of Gaussian and non-Gaussian noise in the data set using physics-informed RNNs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

On Estimating the Phase of Periodic Waveform in Additive Gaussian Noise, Part 2

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

Rauch, L. L.↗
NASA NTRS2014

Detecting Trend and Seasonal Changes in Bathymetry Derived from HICO Imagery: A Case Study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallowwater inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used.Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than +/-20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as lowas 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

Geolocations accuracy↗
NASA NTRS2014

Detecting Trend and Seasonal Changes in Bathymetry Derived from HICO Imagery: A Case Study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallow water inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used. Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than +/-20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as low as 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

coastal marine↗
NASA NTRS1977

Combustion noise

A review of the subject of combustion generated noise is presented. Combustion noise is an important noise source in industrial furnaces and process heaters, turbopropulsion and gas turbine systems, flaring operations, Diesel engines, and rocket engines. The state-of-the-art in combustion noise importance, understanding, prediction and scaling is presented for these systems. The fundamentals and available theories of combustion noise are given. Controversies in the field are discussed and recommendations for future research are made.

Strahle, W. C.↗
NASA NTRS1997

Planar Doppler Velocimetry for Large-Scale Wind Tunnel Testing

Recently, Planar Doppler Velocimetry (PDV) has been shown by several laboratories to offer an attractive means for measuring three-dimensional velocity vectors everywhere in a light sheet placed in a flow. Unlike other optical means of measuring flow velocities, PDV is particularly attractive for use in large wind tunnels where distances to the sample region may be several meters, because it does not require the spatial resolution and tracking of individual scattering particles or the alignment of crossed beams at large distances. To date, demonstrations of PDV have been made either in low speed flows without quantitative comparison to other measurements, or in supersonic flows where the Doppler shift is large and its measurement is relatively insensitive to instrumental errors. Moreover, most reported applications have relied on the use of continuous-wave lasers, which limit the measurement to time-averaged velocity fields. This work summarizes the results of two previous studies of PDV in which the use of pulsed lasers to obtain instantaneous velocity vector fields is evaluated. The objective has been to quantitatively define and demonstrate PDV capabilities for applications in large-scale wind tunnels that are intended primarily for the production testing of subsonic aircraft. For such applications, the adequate resolution of low-speed flow fields requires accurate measurements of small Doppler shifts that are obtained at distances of several meters from the sample region. The use of pulsed lasers provides the unique capability to obtain not only time-averaged fields, but also their statistical fluctuation amplitudes and the spatial excursions of unsteady flow regions such as wakes and separations. To accomplish the objectives indicated, the PDV measurement process is first modeled and its performance evaluated computationally. The noise sources considered include those related to the optical and electronic properties of Charge-Coupled Device (CCD) arrays and to speckle effects associated with coherent illumination from pulsed lasers. The signal noise estimates are incorporated into the PDV signal analysis process and combined with computed scattering signals using a Mie scattering theory for polydisperse smoke particles. The relevant parameters incorporate a range of practical aerodynamic test conditions and facility sizes. The results define the optimum instrument configurations, show that the expected signal levels from a practical PDV system are sufficiently large to allow its useful application in large facilities, and show that the expected velocity measurement uncertainties are small compared to the mean velocities of interest for most subsonic, large-scale wind tunnel testing. Experimental studies using several experimental bench-top setups are then described that validate the physics of the PDV model and to calibrate its computed results. The validated model allows estimates of the uncertainties of PDV measurements and a complete definition of the PDV capabilities to be made with sufficient confidence to decide the viability of PDV for large-scale wind tunnel applications.

McKenzie, Robert L.↗
NASA NTRS1997

Measurement Capabilities of Planar Doppler Velocimetry in Large-Scale Wind Tunnels

Over the past few years, Planar Doppler Velocimetry (PDT) has been shown by several laboratories to offer an attractive means for measuring three-dimensional velocity vectors everywhere in a light sheet placed in a flow. Unlike some other optical means of measuring flow velocities, PDT is particularly attractive for use in large wind tunnels where distances to the sample region may be several meters, because it does not require the spatial resolution and tracking of individual scattering particles or the alignment of crossed beams at large distances. To date, demonstrations of PDT (also called Doppler Global Velocimetry by some authors) have been made either in low speed flows without quantitative comparison to other measurements, or in supersonic flows where the Doppler shift is large and its measurement is relatively insensitive to instrumental errors. Moreover, most reported applications have relied on the use of continuous-wave lasers, which limit the measurement to time-averaged velocity fields. This work summarizes the results of two previous studies of PDT in which the use of pulsed lasers to obtain instantaneous velocity vector fields is evaluated. The objective has been to quantitatively define and demonstrate PDT capabilities for applications in large-scale wind tunnels that are intended primarily for the testing of rotorcraft and subsonic aircraft at speeds typically less than 100 m/s. For such applications, the adequate resolution of low-speed flow fields requires accurate measurements of small Doppler shifts that are obtained at distances of several meters from the sample region and with a field of view that is sufficient to encompass the entire region of interest. The use of pulsed lasers provides the unique capability to obtain not only time-averaged fields, but also their statistical fluctuation amplitudes and the spatial excursions of unsteady flow regions such as wakes, separations, and rotor-tip vortices. To accomplish the objectives of these studies, the PDT measurement process was first modeled and its performance evaluated computationally. The noise sources considered included those related to the optical and electronic properties of Charge-Coupled Device (CCD) arrays and to speckle effects associated with the coherent illumination of aerosols from pulsed lasers. The signal noise estimates were incorporated into the PDT signal analysis process and combined with computed scattering signals using a Mae scattering theory for a distributed range of aerosol particle sizes. The results are used to define the necessary instrument configuration, to show that the expected signal levels from a practical PDT system are sufficiently large to allow its useful application in large facilities, and to show that the expected velocity measurement uncertainties are small compared to the mean velocities of interest for most subsonic, large-scale wind tunnel testing, Experimental studies using several bench-top setups are then described that validate the physics of the PDT model and demonstrate the ability to obtain accurate PDT measurements using procedures that are compatible with large-scale wind tunnel operations. The PDT measurement capabilities found in this study lead to the conclusion that PDT offers significant advantages compared to other means of measuring velocity fields in large-scale wind tunnels, including those operating at low speeds.

McKenzie, Robert L.↗
NASA NTRS1991

On estimating the phase of a periodic waveform in additive Gaussian noise, part 3

Motivated by advances in signal processing technology that support more complex algorithms, researchers have taken a new look at the problem of estimating the phase and other parameters of a nearly periodic waveform in additive Gaussian noise, based on observation during a given time interval. Parts 1 and 2 are very briefly reviewed. In part 3, the actual performances of some of the highly nonlinear estimation algorithms of parts 1 and 2 are evaluated by numerical simulation using Monte Carlo techniques.

Rauch, L. L.↗