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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 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Power System Event Identification Based on Deep Neural Network With Information Loading

Online power system event identification and classification are crucial to enhancing the reliability of transmission systems. In this study, we develop a deep neural network (DNN) based approach to identify and classify power system events by leveraging real-world measurements from hundreds of phasor measurement units (PMUs) and labels from thousands of events. Two innovative designs are embedded into the baseline model built on convolutional neural networks (CNNs) to improve the event classification accuracy. First, we propose a graph signal processing based PMU sorting algorithm to improve the learning efficiency of CNNs. Second, we deploy information loading based regularization to strike the right balance between memorization and generalization for the DNN. Numerical results based on real-world dataset from the Eastern Interconnection of the U.S power transmission grid show that the combination of PMU based sorting and the information loading based regularization techniques help the proposed DNN approach achieve highly accurate event identification and classification results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2013

Methods for Retrievals of CO2 Mixing Ratios from JPL Laser Absorption Spectrometer Flights During a Summer 2011 Campaign

The JPL airborne Laser Absorption Spectrometer instrument has been flown several times in the 2007-2011 time frame for the purpose of measuring CO2 mixing ratios in the lower atmosphere. This instrument employs CW laser transmitters and coherent detection receivers in the 2.05- micro m spectral region. The Integrated Path Differential Absorption (IPDA) method is used to retrieve weighted CO2 column mixing ratios. We present key features of the evolving LAS signal processing and data analysis algorithms and the calibration/validation methodology. Results from 2011 flights in various U.S. locations include observed mid-day CO2 drawdown in the Midwest and high spatial resolution plume detection during a leg downwind of the Four Corners power plant in New Mexico.

laser remote sensing↗

NASA NTRS1978

A multilevel system of algorithms for detecting and isolating signals in a background of noise

Signal information is processed with the help of algorithms, and then on the basis of such processing, a part of the information is subjected to further processing with the help of more precise algorithms. Such a system of algorithms is studied, a comparative evaluation of a series of lower level algorithms is given, and the corresponding algorithms of higher level are characterized.

Gurin, L. S.↗

DOE OSTI2019

Decentralized Signal Processing and Distributed Control of Collaborative Autonomous Networks (17-ERD-101 LDRD Final Report)

Intelligent autonomous sensor networks, often comprised of large numbers of sensors, must be capable of jointly exploiting data collected at each agent in the network, and using that data to optimize their future actions towards multiple mission objectives. Centralized signal processing and optimization solutions process all data and determine all future actions at a single agent, and the resulting information and commands are disseminated back to the network. The communications bandwidth this requires and the single point of failure the central agent represents often make these solutions untenable for national security applications. In this project, several fundamental algorithms for solving both the decentralized signal processing and network optimization were developed, as well as simulation software to validate the results of these algorithms at scale. Specifically, novel algorithms for Bayesian decentralized estimation and decentralized detection and optimization based on the alternating direction method of multipliers (ADMM) were developed for autonomous sensor networks and published in the literature. The first large scale simulation of autonomous sensor networks (1000 agents) was conducted on this project, validating the performance of the developed algorithms. These algorithms and simulation tools are critical components of any decentralized autonomous network and have current and future national security applications, including distributed sensor networks for detection, estimation, and tracking problems, and large decentralized cyber-physical infrastructure such as the power grid.

42 ENGINEERING↗

NASA NTRS1990

Rocket engine failure detection using system identification techiques

The theoretical foundation and application of two univariate failure detection algorithms to Space Shuttle Main Engine (SSME) test firing data is presented. Both algorithms were applied to data collected during steady state operation of the engine. One algorithm, the time series algorithm, is based on time series techniques and involves the computation of autoregressive models. Times series techniques have been previously applied to SSME data. The second algorithm is based on standard signal processing techniques. It consists of tracking the variations in the average signal power with time. The average signal power algorithm is a newly proposed SSME failure detection algorithm. Seven nominal test firings were used to develop failure indication thresholds for each algorithm. These thresholds were tested using four anomalous firings and one additional nominal firing. Both algorithms provided significantly earlier failure indication times than did the current redline limit system. Neither algorithm gave false failure indications for the nominal firing. The strengths and weaknesses of the two algorithms are discussed and compared. The average signal algorithm was found to have several advantages over the time series algorithm.

Meyer, Claudia M.↗

NASA NTRS1990

Rocket engine failure detection using system identification techniques

The theoretical foundation and application of two univariate failure detection algorithms to Space Shuttle Main Engine (SSME) test firing data is presented. Both algorithms were applied to data collected during steady state operation of the engine. One algorithm, the time series algorithm, is based on time series techniques and involves the computation of autoregressive models. Time series techniques have been previously applied to SSME data. The second algorithm is based on standard signal processing techniques. It consists of tracking the variations in the average signal power with time. The average signal power algorithm is a newly proposed SSME failure detection algorithm. Seven nominal test firings were used to develop failure indication thresholds for each algorithm. These thresholds were tested using four anomalous firings and one additional nominal firing. Both algorithms provided significantly earlier failure indication times than did the current redline limit system. Neither algorithm gave false failure indications for the nominal firing. The strengths and weaknesses of the two algorithms are discussed and compared. The average signal algorithm was found to have several advantages over the time series algorithm.

Meyer, Claudia M.↗

NASA NTRS1997

Sequence information signal processor for local and global string comparisons

A sequence information signal processing integrated circuit chip designed to perform high speed calculation of a dynamic programming algorithm based upon the algorithm defined by Waterman and Smith. The signal processing chip of the present invention is designed to be a building block of a linear systolic array, the performance of which can be increased by connecting additional sequence information signal processing chips to the array. The chip provides a high speed, low cost linear array processor that can locate highly similar global sequences or segments thereof such as contiguous subsequences from two different DNA or protein sequences. The chip is implemented in a preferred embodiment using CMOS VLSI technology to provide the equivalent of about 400,000 transistors or 100,000 gates. Each chip provides 16 processing elements, and is designed to provide 16 bit, two's compliment operation for maximum score precision of between -32,768 and +32,767. It is designed to provide a comparison between sequences as long as 4,194,304 elements without external software and between sequences of unlimited numbers of elements with the aid of external software. Each sequence can be assigned different deletion and insertion weight functions. Each processor is provided with a similarity measure device which is independently variable. Thus, each processor can contribute to maximum value score calculation using a different similarity measure.

Peterson, John C.↗

DOE OSTI2024

Robust Iterative Method for Symmetric Quantum Signal Processing in All Parameter Regimes

Here, this paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on quantum computers. Symmetric QSP focuses on representing target polynomials as products of matrices in SU(2) that possess symmetry properties. We present a novel Newton’s method tailored for efficiently solving the nonlinear system involved in determining the phase factors within the symmetric QSP framework. Our method demonstrates rapid and robust convergence in all parameter regimes, including the challenging scenario with ill-conditioned Jacobian matrices, using standard double precision arithmetic operations. For instance, solving symmetric QSP for a highly oscillatory target function α cos(1000x) (polynomial degree ≈ 1433) takes 6 iterations to converge to machine precision when α = 0.9, and the number of iterations only increases to 18 iterations when α = 1 – 10 -9 with a highly ill-conditioned Jacobian matrix. Leveraging the matrix product state structure of symmetric QSP, the computation of the Jacobian matrix incurs a computational cost comparable to a single function evaluation. Moreover, we introduce a reformulation of symmetric QSP using real-number arithmetics, further enhancing the method’s efficiency. Extensive numerical tests validate the effectiveness and robustness of our approach, which has been implemented in the QSPPACK software package.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

A review of non-cognitive applications for neuromorphic computing

Abstract Though neuromorphic computers have typically targeted applications in machine learning and neuroscience (‘cognitive’ applications), they have many computational characteristics that are attractive for a wide variety of computational problems. In this work, we review the current state-of-the-art for non-cognitive applications on neuromorphic computers, including simple computational kernels for composition, graph algorithms, constrained optimization, and signal processing. We discuss the advantages of using neuromorphic computers for these different applications, as well as the challenges that still remain. The ultimate goal of this work is to bring awareness to this class of problems for neuromorphic systems to the broader community, particularly to encourage further work in this area and to make sure that these applications are considered in the design of future neuromorphic systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Revealing the Crystalline Architecture of Semicrystalline Ion Exchange Membranes for the Design of Conductive and Durable Alkaline Anion Exchange Membranes

Alkaline anion exchange membrane (AAEM) fuel cells offer a cost-effective alternative to proton exchange membrane (PEM) fuel cells by eliminating the need for expensive precious metal catalysts. In both PEMs and AAEMs, semicrystalline polymers are a common choice, as the crystalline domains can act as mechanical reinforcements that limit swelling and promote mechanical durability in the material. However, spatially resolved characterization of crystalline organization in ion exchange membranes beyond ensemble-averaged X-ray scattering is underrepresented, likely in part due to ionization damage limitations in soft materials. Here, in this study, we resolve the nanometer-size crystallites in semicrystalline ion exchange membranes by applying cryogenic four-dimensional scanning transmission electron microscopy (cryo-4D-STEM) along with data-processing algorithms designed to optimize signals at a low dose to minimize radiation damage. We investigate the effects of synthesis components, including molecular weight and thermal treatment, on a model system of AAEMs in comparison to Nafion, the most commonly used and commercially successful PEM today. We find that excess water uptake in polymer membranes, a property directly associated with weak mechanical durability and with possible negative impacts on ion conductivity, can be reduced by over 30% by varying the polymer's crystalline morphology through changes in synthesis parameters such as molecular weight and thermal history. Our results indicate that this improvement is correlated with smaller crystalline domains with a more homogeneous distribution. More broadly, these results demonstrate how the crystalline architecture of polymer membranes can be tuned through their chemistry and thermal treatment in order to improve their conductivity and durability for commercial fuel cell performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Quantum advantage for noisy channel discrimination

Many quantum mechanical experiments can be viewed as multiround interactive protocols between known quantum circuits and an unknown quantum process. Fully quantum “coherent” access to the unknown process is known to provide an advantage in many discrimination tasks compared to when only incoherent access is permitted, but it is unclear if this advantage persists when the process is noisy. Here, we show that a quantum advantage can be maintained when distinguishing between two noisy single-qubit rotation channels. Numerical and analytical calculations reveal a distinct transition between the performance of fully coherent and fully incoherent protocols as a function of noise strength. Moreover, the size of the region of coherent quantum advantage shrinks inverse polynomially in the number of channel uses, and in an intermediate regime an improved strategy is a hybrid of fully coherent and fully incoherent subroutines. The fully coherent protocol is based on quantum signal processing, suggesting a generalizable algorithmic framework for the study of quantum advantage in the presence of realistic noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

sdt (Solar Data Tools) [SWR-25-130]

Solar Data Tools (sdt) is an open-source Python library for analyzing PV power (and irradiance) time-series data. It was developed to enable analysis of unlabeled PV data, i.e. with no model, no meteorological data, and no performance index required, by taking a statistical signal processing approach in the algorithms used in the package’s main data processing pipeline. Solar Data Tools empowers PV system fleet owners or operators to analyze system performance a hundred times faster even when they only have access to the most basic data stream—power output of the system.

Meyers-Im, Bennet [National Laboratory of the Rock↗

NASA NTRS1987

A post-processing system for automated rectification and registration of spaceborne SAR imagery

An automated post-processing system has been developed that interfaces with the raw image output of the operational digital SAR correlator. This system is designed for optimal efficiency by using advanced signal processing hardware and an algorithm that requires no operator interaction, such as the determination of ground control points. The standard output is a geocoded image product (i.e. resampled to a specified map projection). The system is capable of producing multiframe mosaics for large-scale mapping by combining images in both the along-track direction and adjacent cross-track swaths from ascending and descending passes over the same target area. The output products have absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 per cent relative to local variations from the assumed geoid.

Curlander, John C.↗

NASA NTRS1990

Spectral Analysis Of Linear, Shift-Invariant Interpolants

Method of analysis provides quantitative measure of reconstruction and interpolation performances of linear, shift-invariant interpolants. Criterion of performance based upon mean-square error of difference between sampled and reconstructed functions. Applicable to reconstruction algorithms used in processing of signals and images and to types of interpolants used in numerical analysis, computer-aided design, and computer graphics.

Lansing, Donald L.↗

NASA NTRS1991

Description, characteristics and testing of the NASA airborne radar

Presented here is a description of a coherent radar scattermeter and its associated signal processing hardware, which have been specifically designed to detect microbursts and record their radar characteristics. Radar parameters, signal processing techniques and detection algorithms, all under computer control, combine to sense and process reflectivity, clutter, and microburst data. Also presented is the system's high density, high data rate recording system. This digital system is capable of recording many minutes of the in-phase and quadrature components and corresponding receiver gains of the scattered returns for selected spatial regions, as well as other aircraft and hardware related parameters of interest for post-flight analysis. Information is given in viewgraph form.

Jones, W. R.↗

NASA NTRS1988

On the precision of automated activation time estimation

We examined how the assignment of local activation times in epicardial and endocardial electrograms is affected by sampling rate, ambient signal-to-noise ratio, and sinx/x waveform interpolation. Algorithms used for the estimation of fiducial point locations included dV/dtmax, and a matched filter detection algorithm. Test signals included epicardial and endocardial electrograms overlying both normal and infarcted regions of dog myocardium. Signal-to-noise levels were adjusted by combining known data sets with white noise "colored" to match the spectral characteristics of experimentally recorded noise. For typical signal-to-noise ratios and sampling rates, the template-matching algorithm provided the greatest precision in reproducibly estimating fiducial point location, and sinx/x interpolation allowed for an additional significant improvement. With few restrictions, combining these two techniques may allow for use of digitization rates below the Nyquist rate without significant loss of precision.

NASA Discipline Cardiopulmonary↗

NASA NTRS2007

NASA Tech Briefs, August 2007

Topics include: Program Merges SAR Data on Terrain and Vegetation Heights; Using G(exp 4)FETs as a Data Router for In-Plane Crossing of Signal Paths; Two Algorithms for Processing Electronic Nose Data; Radiation-Tolerant Dual Data Bus; General-Purpose Front End for Real-Time Data Processing; Nanocomposite Photoelectrochemical Cells; Ultracapacitor-Powered Cordless Drill, Cumulative Timers for Microprocessors; Photocatalytic/Magnetic Composite Particles; Separation and Sealing of a Sample Container Using Brazing; Automated Aerial Refueling Hitches a Ride on AFF; Cobra Probes Containing Replaceable Thermocouples; High-Speed Noninvasive Eye-Tracking System; Detergent-Specific Membrane Protein Crystallization Screens; Evaporation-Cooled Protective Suits for Firefighters; Plasmonic Antenna Coupling for QWIPs; Electronic Tongue Containing Redox and Conductivity Sensors; Improved Heat-Stress Algorithm; A Method of Partly Automated Testing of Software; Rover Wheel-Actuated Tool Interface; and Second-Generation Electronic Nose.

Source record↗

NASA NTRS2012

RFI Risk Reduction Activities Using New Goddard Digital Radiometry Capabilities

The Goddard Radio-Frequency Explorer (GREX) is the latest fast-sampling radiometer digital back-end processor that will be used for radiometry and radio-frequency interference (RFI) surveying at Goddard Space Flight Center. The system is compact and deployable, with a mass of about 40 kilograms. It is intended to be flown on aircraft. GREX is compatible with almost any aircraft, including P-3, twin otter, C-23, C-130, G3, and G5 types. At a minimum, the system can function as a clone of the Soil Moisture Active Passive (SMAP) ground-based development unit [1], or can be a completely independent system that is interfaced to any radiometer, provided that frequency shifting to GREX's intermediate frequency is performed prior to sampling. If the radiometer RF is less than 200MHz, then the band can be sampled and acquired directly by the system. A key feature of GREX is its ability to simultaneously sample two polarization channels simultaneously at up to 400MSPS, 14-bit resolution each. The sampled signals can be recorded continuously to a 23 TB solid-state RAID storage array. Data captures can be analyzed offline using the supercomputing facilities at Goddard Space Flight Center. In addition, various Field Programmable Gate Array (FPGA) - amenable radiometer signal processing and RFI detection algorithms can be implemented directly on the GREX system because it includes a high-capacity Xilinx Virtex-5 FPGA prototyping system that is user customizable.

Bradley, Damon↗