Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Waveform Data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

High Efficiency Traveling-Wave Tube Power Amplifier for Ka-Band Software Defined Radio on International Space Station-A Platform for Communications Technology Development

The design, fabrication and RF performance of the output traveling-wave tube amplifier (TWTA) for a space based Ka-band software defined radio (SDR) is presented. The TWTA, the SDR and the supporting avionics are integrated to forms a testbed, which is currently located on an exterior truss of the International Space Station (ISS). The SDR in the testbed communicates at Ka-band frequencies through a high-gain antenna directed to NASA s Tracking and Data Relay Satellite System (TDRSS), which communicates to the ground station located at White Sands Complex. The application of the testbed is for demonstrating new waveforms and software designed to enhance data delivery from scientific spacecraft and, the waveforms and software can be upgraded and reconfigured from the ground. The construction and the salient features of the Ka-band SDR are discussed. The testbed is currently undergoing on-orbit checkout and commissioning and is expected to operate for 3 to 5 years in space.

Simons, Rainee N.↗
NASA NTRS1989

Database for LDV signal processor performance analysis

A technique for the direct comparison of LDV signal processors is developed, based on the use of a data base of digitized signal bursts obtained from an LDV under various configurations. This data base can be used to evaluate the response of signal processors and processor algorithms to specific signal characteristics and not to generalized simplistic waveforms. Examples from such a data base are presented to illustrate the capabilities of the proposed method. This data base includes signal ensembles obtained with three laser power settings at two transmitted focal lengths.

Baker, Glenn D.↗
DOE OSTI2024

Power System Waveform Datasets for Machine Learning

The desire for increased visibility across the electricity grid will necessarily increase the deployment of sensing and measurement devices and associated data management needs to unprecedented levels. For the existing sensing and measurement infrastructure, there remains a great amount of “value” yet to be extracted through advanced data management and analytics. Availability of more data will not, by itself, lead to changes in grid visibility, security, and resiliency. To create the predictive and prescriptive environment required to enable new markets and transactions for customer revenue and a reliable grid, the data must be collected, organized, evaluated, and analyzed using sophisticated algorithms to provide actionable information allowing operators and customers to reliably manage an increasingly complex grid. Progress in artificial intelligence (AI) has been largely driven by large, publicly available datasets that can be used to train AI algorithms such as MNIST, a database of handwritten images of digits, and ImageNet, an image database of everyday objects. These types of publicly available databases of real-world training datasets have been largely credited for advancement of image processing, computer vision, and deep learning algorithms that these use cases deploy. However, in the power systems industry to date, there are few databases with proper event labeling, and data access to a publicly available collection of power system event waveforms that will allow users to interact with grid signature data. Publicly available datasets of power system event waveforms, such as the DOE/EPRI dataset, often lack critical metadata or contain limited examples of each event type, and data formats vary widely across these datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Detecting an underground tunnel by applying joint traveltime and waveform inversion

Underground tunnel and void detection is a challenging geophysical problem, and many methods have been proposed. Seismic techniques are promising because of the large seismic velocity contrasts between the air-filled void and the surrounding sediment and concrete. We apply a joint seismic traveltime and waveform inversion method to image a buried tunnel with concrete walls and a void space inside. The joint inversion images the top of the concrete tunnel as a high-velocity anomaly and the void space as a low-velocity anomaly. The location of the velocity anomalies predicted by the method agrees with the known location of the tunnel. As a comparison, the stand-alone full waveform inversion is also applied to the data. The first-arrival traveltime tomography shows weak nonlinearity but fails to image the hidden low-velocity layer. Full waveform inversion is able to image complex near-surface structures, but fitting waveforms may not honor the traveltime fit, especially when the data contain noise. Synthetic and real data tests show that the joint inversion method retains the advantages of both traveltime inversion and full waveform inversion and overcomes their respective drawbacks at the same time. The field example shows the joint inversion provides a better reconstruction of the high-velocity feature representing the top of the concrete wall in terms of its magnitude and location.

58 GEOSCIENCES↗
DOE OSTI2022

Making Invisible Visible: Data-Driven Seismic Inversion With Spatio-Temporally Constrained Data Augmentation

Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of obtaining data through expensive physical experiments, instruments, and simulations, data augmentation techniques for scientific applications have emerged as a new direction for obtaining scientific data recently. However, existing data augmentation techniques originating from computer vision yield physically unacceptable data samples that are not helpful for the domain problems that we are interested in. In this article, we develop new data augmentation techniques based on convolutional neural networks. Specifically, our generative models leverage different physics knowledge (such as governing equations, observable perception, and physics phenomena) to improve the quality of the synthetic data. To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO 2 leakage data. Our interest is to invert for subsurface velocity models associated with very small CO 2 leakage. We validate the performance of our methods using comprehensive numerical tests. Here via comparison and analysis, we show that data-driven seismic imaging can be significantly enhanced by using our data augmentation techniques. Particularly, the imaging quality has been improved by 15% in test scenarios of general-sized leakage and 17% in small-sized leakage when using an augmented training set obtained with our techniques.

58 GEOSCIENCES↗
DOE OSTI2020

A versatile X-ray phase retarder for lock-in XMCD measurements

X-ray magnetic circular dichroism (XMCD) is a technique commonly used to probe magnetic properties of materials with element and orbital selectivity, which requires the use of circularly polarized (CP) X-rays. It is possible to accomplish XMCD experiments with fixed CP and alternating the magnetic field orientation, but most reliable data are obtained when alternating the magnetization orientation and the polarization between right and left helicities. A versatile strategy has been developed to perform XMCD experiments using a hard X-ray quarter-wave plate, at both polychromatic dispersive and conventional monochromatic optics, in combination with synchronous data acquisition. The switching frequency waveform is fed into a lock-in amplifier to detect and amplify the XMCD signal. The results on a reference sample demonstrate an improvement in data quality and acquisition time. The instrumentation successfully generated 98% of CP X-rays switching the beam helicity at 13 Hz, with the possibility of faster helicity switching once it is installed at the new Brazilian fourth-generation source, SIRIUS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

PhotonIDs: ML-Powered Photon Identification System for Dark Count Elimination

Reliable single photon detection is the foundation for practical quantum communication and networking. However, today's superconducting nanowire single photon detector(SNSPD) inherently fails to distinguish between genuine photon events and dark counts, leading to degraded fidelity in long-distance quantum communication. In this work, we introduce PhotonIDs, a machine learning-powered photon identification system that is the first end-to-end solution for real-time discrimination between photons and dark count based on full SNSPD readout signal waveform analysis. PhotonIDs ~demonstrates: 1) an FPGA-based high-speed data acquisition platform that selectively captures the full waveform of signal only while filtering out the background data in real time; 2) an efficient signal preprocessing pipeline, and a novel pseudo-position metric that is derived from the physical temporal-spatial features of each detected event; 3) a hybrid machine learning model with near 98% accuracy achieved on photon/dark count classification. Additionally, proposed PhotonIDs ~ is evaluated on the dark count elimination performance with two real-world case studies: (1) 20 km quantum link, and (2) Erbium ion-based photon emission system. Our result demonstrates that PhotonIDs ~could improve more than 31.2 times of signal-noise-ratio~(SNR) on dark count elimination. PhotonIDs ~ marks a step forward in noise-resilient quantum communication infrastructure.

Linne, Karl C. [Chicago U.] (ORCID:000900091870358↗
NASA NTRS1993

A Study of Saturn's E-Ring Particles Using the Voyager 1 Plasma Wave Instrument

The flyby of Voyager 1 at Saturn resulted in the detection of a large variety of plasma waves, e.g., chorus, hiss, and electron cyclotron harmonics. Just before the outbound equator crossing, at about 6.1 R(sub s), the Voyager 1 plasma wave instrument detected a strong, well-defined low-frequency enhancement. Initially it was suggested that plasma waves might be responsible for the spectral feature but more recently dust was suggested as at least a partial contributor to the enhancement. In this report we present evidence which supports the conclusion that dust contributes to the low-frequency enhancement. A new method has been used to derive the dust impact rate. The method relies mainly on the 16-channel spectrum analyzer data. The few wide band waveform observations available (which have been used to study dust impacts during the Voyager 2 ring plane crossing) were useful for calibrating the impact rate from the spectrum analyzer data. The mass and, hence, the size of the dust particles were also obtained by analyzing the response of the plasma wave spectrum analyzer. The results show that the region sampled by Voyager 1 is populated by dust particles that have rms masses of up to few times 10(exp -11) g and sizes of up to a few microns. The dust particle number density is on the order of 10(exp -3) m(exp 3). The optical depth of the region sampled by the spacecraft is 1.04 x 10(exp -6). The particle population is centered about 2500 km south of the equatorial plane and has a north-south thickness of about 4000 km. Possible sources of these particles are the moons Enceladus and Tethys whose orbits lie within the E-ring radial extent. These results are in reasonable agreement with photometric studies and numerical simulations.

Tsintikidis, D.↗
DOE OSTI2020

Identifying Different Classes of Seismic Noise Signals Using Unsupervised Learning

Abstract Proper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources.

Johnson, Christopher W.↗
DOE OSTI2022

Method for determining a histogram of variable sample rate waveforms

A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining a plurality of bins; defining an array of elements; dividing the sampled data points into a plurality of sections; assigning a plurality of polynomial equations, one polynomial equation to each section, each polynomial equation having a waveform that fits the data points of the associated section; determining a plurality of section bin times, one section bin time for each bin in each section, each section bin time determined using the polynomial equation and indicating an amount of time that the waveform has values in the range of one of the bins; and adding the section bin time for each bin in each section to the histogram data in the array element pointed to by the number of the bin.

Tohlen, Michael Aaron↗
DOE OSTI2018

Full-waveform inversion and least-squares reverse-time migration imaging of collimated ultrasonic-beam data for high-resolution wellbore integrity monitoring

Los Alamos National Laboratory (LANL) has recently developed an ultrasonic side-lobe suppressed Bessel collimated beam transducer for low-frequency imaging through highly attenuating materials. In this paper, we study the effectiveness of using such a collimated ultrasonic-beam transducer for imaging concrete heterogeneities outside borehole casing for high-resolution borehole imaging and wellbore integrity monitoring. We obtain detailed concrete heterogeneities including a low-velocity zone using ultrasound data acquired with a 3D imaging prototype and our recently developed full-waveform inversion and least-squares reverse-time migration methods. Full-waveform inversion fits synthetic ultrasonic waveforms with recorded waveforms to build a high-resolution velocity model. Least-squares reverse-time migration produces a high-resolution structural image showing material discontinuities. Finally, our results demonstrate that LANL's 3D imaging system with a collimated ultrasonic-beam transducer together with full-waveform inversion and least-squares reverse-time migration imaging has great potential for high-resolution single-well borehole imaging and non-destructive evaluation.

47 OTHER INSTRUMENTATION↗
NASA NTRS2004

Reconfigurable Transceiver and Software-Defined Radio Architecture and Technology Evaluated for NASA Space Communications

The NASA Glenn Research Center is investigating the development and suitability of a software-based open-architecture for space-based reconfigurable transceivers (RTs) and software-defined radios (SDRs). The main objectives of this project are to enable advanced operations and reduce mission costs. SDRs are becoming more common because of the capabilities of reconfigurable digital signal processing technologies such as field programmable gate arrays and digital signal processors, which place radio functions in firmware and software that were traditionally performed with analog hardware components. Features of interest of this communications architecture include nonproprietary open standards and application programming interfaces to enable software reuse and portability, independent hardware and software development, and hardware and software functional separation. The goals for RT and SDR technologies for NASA space missions include prelaunch and on-orbit frequency and waveform reconfigurability and programmability, high data rate capability, and overall communications and processing flexibility. These operational advances over current state-of-art transceivers will be provided to reduce the power, mass, and cost of RTs and SDRs for space communications. The open architecture for NASA communications will support existing (legacy) communications needs and capabilities while providing a path to more capable, advanced waveform development and mission concepts (e.g., ad hoc constellations with self-healing networks and high-rate science data return). A study was completed to assess the state of the art in RT architectures, implementations, and technologies. In-house researchers conducted literature searches and analysis, interviewed Government and industry contacts, and solicited information and white papers from industry on space-qualifiable RTs and SDRs and their associated technologies for space-based NASA applications. The white papers were evaluated, compiled, and used to assess RT and SDR system architectures and core technology elements to determine an appropriate investment strategy to advance these technologies to meet future mission needs. The use of these radios in the space environment represents a challenge because of the space radiation suitability of the components, which drastically reduces the processing capability. The radios available for space are considered to be RTs (as opposed to SDRs), which are digitally programmable radios with selectable changes from an architecture combining analog and digital components. The limited flexibility of this design contrasts against the desire to have a power-efficient solution and open architecture.

Reinhart, Richard C.↗
DOE OSTI2017

Continued Data Acquisition Development

This task focused on improving techniques for integrating data acquisition of secondary particles correlated in time with detected cosmic-ray muons. Scintillation detectors with Pulse Shape Discrimination (PSD) capability show the most promise as a detector technology based on work in FY13. Typically PSD parameters are determined prior to an experiment and the results are based on these parameters. By saving data in list mode, including the fully digitized waveform, any experiment can effectively be replayed to adjust PSD and other parameters for the best data capture. List mode requires time synchronization of two independent data acquisitions (DAQ) systems: the muon tracker and the particle detector system. Techniques to synchronize these systems were studied. Two basic techniques were identified: real time mode and sequential mode. Real time mode is the preferred system but has proven to be a significant challenge since two FPGA systems with different clocking parameters must be synchronized. Sequential processing is expected to work with virtually any DAQ but requires more post processing to extract the data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

A study of the influence of the data acquisition system sampling rate on the accuracy of measured acceleration loads for transport aircraft

A research effort was initiated at National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC), to describe the relationship between the sampling rate and the accuracy of acceleration loads obtained from the data acquisition system of a transport aircraft. An accelerometer was sampled and digitized at a rate of 100 samples per second onboard a NASA Boeing 737 (B-737) flight research aircraft. Numerical techniques were used to reconstruct 2.5 hours of flight data into its original input waveform and then re-sample the waveform into rates of 4, 8, 16, and 32 samples per second. Peak-between-means counting technique and power spectral analysis were used to evaluate each sampling rate using the 32 samples per second data as the comparison. This paper presents the results from these methods and includes in appendix A, the peak-between-means counting results used in a general fatigue analysis for each of the sampling rates.

Whitehead, Julia H.↗
DOE OSTI2020

Recovery and Calibration of Legacy Underground Nuclear Test Seismic Data from the Leo Brady Seismic Network

The Leo Brady Seismic Network (LBSN, originally the Sandia Seismic Network) was established in 1960 by Sandia National Laboratories to monitor underground nuclear tests (UGTs) at the Nevada National Security Site (NNSS, formerly named the Nevada Test Site). The LBSN has been in various configurations throughout its existence, but it has generally been comprised of four to six stations at regional distances (~150–400 km) from the NNSS with approximately evenly spaced azimuthal coverage. Between 1962 and the end of nuclear testing in 1992, the LBSN—and a sister network operated by Lawrence Livermore National Laboratories—was the most comprehensive United States source of regional seismic data of UGTs. Approximately 75% of all UGTs performed by the United States occurred in the predigital era. At that time, LBSN data were transmitted as frequency-modulated (FM) audio over telephone lines to a central location and recorded as analog waveforms on high-fidelity magnetic audio tapes. These tapes have been in dry temperature-stable storage for decades and contain the sole record of this irreplaceable data; full waveforms of LBSN-recorded UGTs from this era were not routinely digitized or otherwise published. We have developed a process to recover and calibrate data from these tapes. First, we play back and digitize the tapes as audio. Next, we demodulate the FM “audio” into individual waveforms. We then estimate the various instrument constants through careful measurement of “weight-lift” tests performed prior to each UGT on each instrument. Finally, these coefficients allow us to scale and shape the derived instrument response of the seismographs and compute poles and zeros. Finally, the result of this process is a digital record of the recorded seismic ground motion in a modern data format, stored in a searchable database. To date, we have digitized tapes from 592 UGTs.

58 GEOSCIENCES↗
DOE OSTI2024

Collaborative Research: Properties and Dynamics of the Shallow Crust (Final Report)

Ground motions recorded at one location are often extrapolated to nearby regions within a given radius. Here, we explore the appropriateness of spatial extrapolation using data from seven small aperture seismic network deployments in southern California. Six of these deployments are linear arrays of 4-13 stations, and one is a 2D array of 13 stations at Pinyon Flats Observatory. The spatial footprint array diameters are 3 km or less, and each array was operational for a year or more. From our base catalog (M2.5+ earthquakes; 4038 events; September 2010 - June 2023), automated methods remove temporally overprinted waveforms from nearby events (< 5 km) in quick succession (< 5 min) and data with nonviable waveforms. These 200 samples per second data are filtered at 0.5-25 Hz and must have signal-tonoise ratios (SNRs) of 2.5+. Peak ground acceleration (PGA) and peak ground velocity (PGV) are derived individually from the maximum absolute values of each of the 3-component waveforms (vertical, northsouth, and east-west). Five of the seven arrays traverse the San Jacinto fault, and two do not. Ground motion observations are compared with theoretical estimates from Abrahamson et al., 2014. On average, arrays deployed within and across fault zones consistently record ground motions above theoretical expectations, whereas off-fault arrays record ground motions at or slightly below theoretical expectations. We attribute these differences to site conditions because these trends prevail for the full data suites. For each network and each individual channel, the coefficient of variation indicates that the standard deviations are ~30±6% of the mean. Exploring relative ground motion contributions from all three channels (ternary plots), as expected, most data show that vertical ground motions are attenuated compared to horizontal ones. However, this is not always the case for RA array data, where vertical motions can be ~2-3 times larger than horizontal motions for select events near Cahuilla, CA. These anomalously high vertical motions are focal mechanism-related. These results suggest that ternary plots created using only a small amount of data can be used as a data quality metric and a tool to find anomalous features in three-component data.

58 GEOSCIENCES↗