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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Development of CMOS Active Pixel Image Sensors for Low Cost Commercial Applications

This paper describes ongoing research and development of CMOS active pixel image sensors for low cost commercial applications. A number of sensor designs have been fabricated and tested in both p-well and n-well technologies. Major elements in the development of the sensor include on-chip analog signal processing circuits for the reduction of fixed pattern noise, on-chip timing and control circuits and on-chip analog-to-digital conversion (ADC). Recent results and continuing efforts in these areas will be presented.

active pixel image sensors CMOS signal processing ↗
NASA NTRS2012

Noise Whitening in Airborne Wind Profiling With a Pulsed 2-Micron Coherent Doppler Lidar at NASA Langley Research Center

Two different noise whitening methods in airborne wind profiling with a pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia are presented. In order to provide accurate wind parameter estimates from the airborne lidar data acquired during the NASA Genesis and Rapid Intensification Processes (GRIP) campaign in 2010, the adverse effects of background instrument noise must be compensated properly in the early stage of data processing. The results of the two methods are presented using selected GRIP data and compared with the dropsonde data for verification purposes.

Beyon, Jeffrey Y.↗
DOE OSTI2020

Experimental Modal Analysis Using Phase Quantities from Phase-Based Motion Processing and Motion Magnification

Phase-based motion processing and the associated Motion Magnification that it enables has become popular not only for the striking videos that it can produce of traditionally stiff structures visualized with very large deflections, but also for its ability to pull information out of the noise floor of images so that they can be processed with more traditional optical techniques such as digital image correlation or feature tracking. While the majority of papers in the literature have utilized the Phase-based Image Processing approach as a pre-processor for more quantitative analyses, the technique itself can be used directly to extract modal parameters from an image, noting that the extracted phases are proportional to displacements in the image. Therefore, once phases are extracted, they can be fit using traditional experimental modal analysis techniques. This produces a mode “shape” where the degrees of freedom are phases instead of physical motions. These phases can be scaled to produce on-image visualizations of the mode shapes, rather than operational shapes produced by bandpass filtering. Modal filtering techniques can also be used to visualize motions from an environment on an image using the modal phases as a basis for the expansion.

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

Quiet STOL propulsion session introductory remarks

Research activities, preliminary design activities, and system optimization studies in support of the development of advanced, quiet, STOL propulsion systems are discussed. Noise alleviation by means of controlling the source and by means of acoustical treatment receive considerable emphasis. A STOL airplane designed for a given payload has essentially double the installed thrust of a comparable CTOL airplane. Unless compensated for during the design process, this alone will tend to increase the source noise by 3 db. The propulsive lift introduces flap impingement noise or duct and flap scrubbing noise, noise sources not present in CTOL airplanes to any significant degree. These additional noise sources are illustrated. Depending on the specific configuration, this will tend to increase the noise by several db or more. Although the propulsive lift characteristics of STOL airplanes will tend to increase source noise significantly, the proximity of STOL airfields to populated areas leads to STOL noise objectives considerably lower than those currently applicable to CTOL airplanes.

Schroeder, R. W.↗
DOE OSTI2024

Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal classification and detection; however, these methods aren't designed to handle the low signal-to-noise ratios inherent within non-vision signal processing tasks. While they are powerful, they are currently not the method of choice in the inherently noisy and dynamic critical infrastructure domain, such as smart-grid sensing, anomaly detection, and non-intrusive load monitoring. Currently, these models can be brittle, which makes them susceptible to noisy input. This also means they have sub-optimal stability of explanation outputs. Experts and technicians using these models to make decisions in real world scenarios need assurance that a model is performing as it is supposed to. The classification or prediction outputs it generates should be sound and grounded, not likely to change in the presence of shifting noise landscapes. In this work, we explore the idea of Neural Stochastic Differential Equations (NSDE's) to improve the robustness of models trained to classify time series data and the effect of NSDE's on the explainability of outputs. We then test the effectiveness of these approaches by applying them to a non-intrusive load monitoring (NILM) dataset that consists of simulated harmonic signals injected into a real building.

Brogan, Joel↗
DOE OSTI2023

High-sensitivity electronic Stark spectrometer featuring a laser-driven light source

We report developmental details of a high-sensitivity Stark absorption spectrometer featuring a laser-driven light source. The light source exhibits intensity fluctuations of ~0.3% over timescales ranging from 1 min to 12 h, minimal drift (≤0.1%/h), and very little 1/f noise at frequencies greater than 200 Hz, which are comparable to or better than an arc-driven light source. Additional features of the spectrometer include balanced detection with multiplex sampling, which yielded lower noise in A, and constant wavelength or wavenumber (energy) spectral bandpass modes. We achieve noise amplitudes of ~7 × 10 –4 and ~6 × 10 –6 in measurements of single A and ΔA spectra (with 92 data points) taking ~7 and ~19 min, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Phase transitions in Schloegl's second model for autocatalysis on a Bethe lattice

Schloegl's second model (also known as the quadratic contact process) on a lattice involves spontaneous particle annihilation at rate p and autocatalytic particle creation at empty sites with n ≥ 2 occupied neighbors. The particle creation rate for exactly n occupied neighbors is selected here as n(n - 1)/[z(z - 1)] for lattice coordination number z. We analyze this model on a Bethe lattice. Precise behavior for stochastic models on regular periodic infinite lattices is usually surmised from kinetic Monte Carlo simulation on a finite lattice with periodic boundary conditions. However, the persistence of boundary effects for a Bethe lattice complicates this process, e.g., by inducing spatially heterogenous states. This motivates the exploration of various boundary conditions and unconventional simulation ensembles on the Bethe lattice to predict behavior for infinite size. Here, we focus on z = 3, and predict a discontinuous transition to the vacuum state on the infinite lattice when p exceeds a threshold value of around 0.053.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Effect of atmospherics on beamforming accuracy

Two mathematical representations of noise due to atmospheric turbulence are presented. These representations are derived and used in computer simulations of the Bartlett Estimate implementation of beamforming. Beamforming is an array processing technique employing an array of acoustic sensors used to determine the bearing of an acoustic source. Atmospheric wind conditions introduce noise into the beamformer output. Consequently, the accuracy of the process is degraded and the bearing of the acoustic source is falsely indicated or impossible to determine. The two representations of noise presented here are intended to quantify the effects of mean wind passing over the array of sensors and to correct for these effects. The first noise model is an idealized case. The effect of the mean wind is incorporated as a change in the propagation velocity of the acoustic wave. This yields an effective phase shift applied to each term of the spatial correlation matrix in the Bartlett Estimate. The resultant error caused by this model can be corrected in closed form in the beamforming algorithm. The second noise model acts to change the true direction of propagation at the beginning of the beamforming process. A closed form correction for this model is not available. Efforts to derive effective means to reduce the contributions of the noise have not been successful. In either case, the maximum error introduced by the wind is a beam shift of approximately three degrees. That is, the bearing of the acoustic source is indicated at a point a few degrees from the true bearing location. These effects are not quite as pronounced as those seen in experimental results. Sidelobes are false indications of acoustic sources in the beamformer output away from the true bearing angle. The sidelobes that are observed in experimental results are not caused by these noise models. The effects of mean wind passing over the sensor array as modeled here do not alter the beamformer output as significantly as expected.

Alexander, Richard M.↗
NASA NTRS1994

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Lai, Jonathan Y.↗
NASA NTRS1995

Reduction of Background Noise in the NASA Ames 40- by 80-Foot Wind Tunnel

Background noise in both open-jet and closed wind tunnels adversely affects the signal-to-noise ratio of acoustic measurements. To measure the noise of increasingly quieter aircraft models, the background noise will have to be reduced by physical means or through signal processing. In a closed wind tunnel, such as the NASA Ames 40- by 80- Foot Wind Tunnel, the principle background noise sources can be classified as: (1) fan drive noise; (2) microphone self-noise; (3) aerodynamically induced noise from test-dependent hardware such as model struts and junctions; and (4) noise from the test section walls and vane set. This paper describes the steps taken to minimize the influence of each of these background noise sources in the 40 x 80.

Jaeger, Stephen M.↗
NASA NTRS2007

Design and Fabrication Highlights Enabling a 2 mm, 128 Element Bolometer Array for GISMO

The Backshort-Under-Grid (BUG) superconducting bolometer array architecture is intended to be highly versatile, operating in a large range of wavelengths and background conditions. We have undertaken a three-year program to develop key technologies and processes required to build kilopixel arrays. To validate the basic array design and to demonstrate its applicability for future kilopixel arrays, we have chosen to demonstrate a 128 element bolometer array optimized for 2 mm wavelength using a newly built Goddard instrument, GISMO (Goddard /RAM Superconducting 2-millimeter Observer). The arrays are fabricated using batch wafer processing developed and optimized for high pixel yield, low noise, and high uniformity. The molybdenum-gold superconducting transition edge sensors are fabricated using batch sputter deposition and are patterned using dry etch techniques developed at Goddard. With a detector pitch of 2 mm 8x16 array for GISMO occupies nearly one half of the processing area of a 100 mm silicon-on-insulator starting wafer. Two such arrays are produced from a single wafer along with witness samples for process characterization. To provide thermal isolation for the detector elements, at the end of the process over 90% of the silicon must be removed using deep reactive ion etching techniques. The electrical connections for each bolometer element are patterned on the top edge of the square grid supporting the array. The design considerations unique to GISMO, key fabrication challenges, and laboratory experimental results will be presented.

Allen, Christine↗
NASA NTRSDate not supplied

Effect of Flight on Turbulence Statistics and Noise Sources in a Round Turbulent Jet

Turbulence statistics relevant to noise modeling and prediction are computed in a near-sonic, unheated round jet in the presence of a flight stream using Large Eddy Simulation. The Naval Research Laboratory’s Jet Engine Noise REduction (JENRE) code is used to obtain unsteady flow solutions which are post-processed for single- and two-point, space-time statistical quantities, including the nominal noise sources from an acoustic analogy formulation. Jets subject to three different flight-stream speeds, along with a baseline static case, are considered. The impact of flight-stream speed on mean flow and turbulence profiles and the amplitudes, length and time scales of Reynolds-stress auto co-variances are determined and scalings for representing the flight stream effect are explored. The implications for source modeling in jet mixing noise predictions within an acoustic analogy formulation are discussed.

Jet noise, flight effects, aircraft noise↗
NASA NTRSDate not supplied

Effect of Flight on Turbulence Statistics and Noise Sources in a Round Turbulent Jet

Turbulence statistics relevant to noise modeling and prediction are computed in a series near-sonic, unheated round jets in the presence of a flight stream using Large Eddy Simulation. The Naval Research Laboratory’s Jet Engine Noise REduction (JENRE®) code is used to obtain unsteady flow solutions which are post-processed for single- and two-point, space-time statistical quantities, including the nominal noise sources from an acoustic analogy formulation. Jets subject to three different flight-stream speeds, along with a baseline static case, are considered. The impact of flight-stream speed on mean flow and turbulence profiles and the amplitudes, length and time scales of Reynolds-stress auto co-variances are determined and scalings for representing the flight-stream effect are explored. The implications for source modeling in jet mixing noise predictions within an acoustic analogy formulation are discussed.

Jet noise↗
NASA NTRSDate not supplied

Effect of Flight on Turbulence Statistics and Noise Sources in a Round Turbulent Jet

Turbulence statistics relevant to noise modeling and prediction are computed in a series near-sonic, unheated round jets in the presence of a flight stream using Large Eddy Simulation. The Naval Research Laboratory’s Jet Engine Noise REduction (JENRE) code is used to obtain unsteady flow solutions which are post-processed for single- and two-point, space-time statistical quantities, including the nominal noise sources from an acoustic analogy formulation. Jets subject to three different flight-stream speeds, along with a baseline static case, are considered. The impact of flight-stream speed on mean flow and turbulence profiles and the amplitudes, length and time scales of Reynolds-stress auto co-variances are determined and scalings for representing the flight-stream effect are explored. The implications for source modeling in jet mixing noise predictions within an acoustic analogy formulation are discussed.

Jet noise↗
DOE OSTI2022

Characterization of a 1D-imaging high-energy x-ray backlighter driven by the National Ignition Facility Advanced Radiographic Capability laser

Plastic deformation of samples compressed to Mbar pressures at high strain rates at the National Ignition Facility (NIF) forms the basis of ongoing material strength experiments in conditions relevant to meteor impacts, geophysics, armor development, and inertial confinement fusion. Hard x-ray radiography is the primary means of measuring the evolution of these samples, typically employing a slit-collimated high-Z microdot driven by the NIF laser to generate >40 keV x rays [E. Gumbrell et al., Rev. Sci. Instrum. 89, 10G118 (2018) and C. M. Huntington et al., Rev. Sci. Instrum. 89, 10G121 (2018)]. Alternatively, a dysprosium “micro-flag” target driven by the Advanced Radiographic Capability laser (~2 kJ, 10 ps) can deliver significantly higher spatiotemporal resolution [M. P. Hill et al., Rev. Sci. Instrum. 92, 033535 (2021)], especially in high-opacity samples. Here, initial experiments revealed problematic brightness and spectral gradients from this source, but by radiographing a set of diamond-turned, 105 µm-thick Pb test objects and supported by simulations using the 3D Monte Carlo code GEANT4, these geometry-dependent gradients across the field of view are quantified and mitigation strategies are assessed. In addition to significantly enhancing the modulation transfer function compared to the existing system, image stacking from multiple layers of image plate is shown to almost double the signal to noise ratio that will reduce uncertainties in future dynamic strength experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm

The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.

D estefani, André↗
DOE OSTI2024

Drifting Acoustic Measurements around C-Power's SeaRay WEC

The repository contains underwater noise measurements and associated metadata collected around C-Power's SeaRay wave energy converter on July 15, 2024 and July 16, 2024 while it was deployed at the U.S. Navy's Wave Energy Test Site (WETS) in Kaneohe, HI. Measurements were obtained using Drifting Acoustic Instrumentation SYstems (DAISYs). DAISYs consist of a surface expression connected to a hydrophone recording package by a tether. Both elements are instrumented to provide metadata (e.g., position, orientation, and depth). Information about how to build DAISYs is available at https://www.pmec.us/research-projects/daisy. The repository's primary content is a compressed archive (.zip format), containing multiple MATLAB binary data files (.mat format). The structure of each file is included in the repository as a Word document (Data Description MHK-DR.docx). Each file contains time series information for a single DAISY deployment (file naming convention: WETS_DAISY_[Drift #].mat) consisting of processed hydrophone data and associated metadata. During these measurements, C-Power's SeaRay was located at approximately 21.48112 N, 157.74451 W.

16 TIDAL AND WAVE POWER↗
NASA NTRS1990

Olympus receiver evaluation and phase noise measurements

A set of measurements performed by the Michigan Tech Sensing and Signal Processing Group on the analog receiver built by the Virginia Polytechnic Institute (VPI) and the Jet Propulsion Laboratory (JPL) for propagation measurements using the Olympus Satellite is described. Measurements of local oscillator (LO) phase noise were performed for all of the LOs supplied by JPL. In order to obtain the most useful set of measurements, LO phase noise measurements were made using the complete VPI receiver front end. This set of measurements demonstrates the performance of the receiver from the Radio Frequency (RF) input through the high Intermediate Frequency (IF) output. Three different measurements were made: LO phase noise with DC on the voltage controlled crystal oscillator (VCXO) port; LO phase noise with the 11.381 GHz LO locked to the reference signal generator; and a reference measurement with the JPL LOs out of the system.

Campbell, Richard L.↗