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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Making Phase-Picking Neural Networks More Consistent and Interpretable

Improving the interpretability of phase-picking neural networks remains an important task to facilitate their deployment to routine, real-time seismic monitoring. The popular phase-picking neural networks published in the literature lack interpretability because their output prediction scores do not necessarily correspond with the reliability of phase picks and can even be highly inconsistent depending on how we window the waveform data. Here, we show that systematically shifting the waveforms during training and using an antialiasing filter within the neural network architecture can substantially improve the consistency of the output prediction scores and can even make them scale with the signal-to-noise ratios of the waveforms. We demonstrate the improvements by applying these approaches to a commonly used phase-picking neural network architecture and using waveform data from the 2019 Ridgecrest earthquake sequence.

58 GEOSCIENCES↗
DOE OSTI2014

Three-dimensional NDE of VHTR core components via simulation-based testing. Final report

A next generation, simulation-driven-and-enabled testing platform is developed for the 3D detection and characterization of defects and damage in nuclear graphite and composite structures in Very High Temperature Reactors (VHTRs). The proposed work addresses the critical need for the development of high-fidelity Non-Destructive Examination (NDE) technologies for as-manufactured and replaceable in-service VHTR components. Centered around the novel use of elastic (sonic and ultrasonic) waves, this project deploys a robust, non-iterative inverse solution for the 3D defect reconstruction together with a non-contact, laser-based approach to the measurement of experimental waveforms in VHTR core components. In particular, this research (1) deploys three-dimensional Scanning Laser Doppler Vibrometry (3D SLDV) as a means to accurately and remotely measure 3D displacement waveforms over the accessible surface of a VHTR core component excited by mechanical vibratory source; (2) implements a powerful new inverse technique, based on the concept of Topological Sensitivity (TS), for non-iterative elastic waveform tomography of internal defects - that permits robust 3D detection, reconstruction and characterization of discrete damage (e.g. holes and fractures) in nuclear graphite from limited-aperture NDE measurements; (3) implements state-of-the art computational (finite element) model that caters for accurately simulating elastic wave propagation in 3D blocks of nuclear graphite; (4) integrates the SLDV testing methodology with the TS imaging algorithm into a non-contact, high-fidelity NDE platform for the 3D reconstruction and characterization of defects and damage in VHTR core components; and (5) applies the proposed methodology to VHTR core component samples (both two- and three-dimensional) with a priori induced, discrete damage in the form of holes and fractures. Overall, the newly established SLDV-TS testing platform represents a next-generation NDE tool that surpasses all existing techniques for the 3D ultrasonic imaging of material damage from non-contact, limited-aperture waveform measurements. Outlook. The next stage in the development of this technology includes items such as (a) non-contact generation of mechanical vibrations in VHTR components via thermal expansion created by high-intensity laser; (b) development and incorporation of Synthetic Aperture Focusing Technique (SAFT) for elevating the accuracy of 3D imaging in highly noisy environments with minimal accessible surface; (c) further analytical and computational developments to facilitate the reconstruction of diffuse damage (e.g. microcracks) in nuclear graphite as they lead to the dispersion of elastic waves, (d) concept of model updating for accurate tracking of the evolution of material damage via periodic inspections; (d) adoption of the Bayesian framework to obtain information on the certainty of obtained images; and (e) optimization of the computational scheme toward real-time, model-based imaging of damage in VHTR core components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Use Case Realization Report: UCR-03.02 Refines Event

This architecturally significant use case describes how the Analyst refines an event hypothesis. The Analyst checks waveform quality (see 'Determines Waveform Data Quality' UC). For waveforms of sufficient quality, the Analyst enhances signals and suppresses noise on waveforms for relevant stations (see 'Enhances Signals' UC), adds and associates missing detections, and modifies or unassociates detections already associated with the event hypothesis (see 'Detects Signals' UC). The Analyst rejects event hypotheses that are invalid. For valid event hypotheses, the Analyst measures signal features associated with the detections (see 'Measures Signal Features' UC) and evaluates the moment tensor ('Evaluates Moment Tensor' UC). The Analyst uses these signal features to refine the location (see 'Refines Event Location' UC) and magnitude (see 'Refines Event Magnitude' UC) of the event hypothesis. The Analyst compares events to determine how similar events were constructed (see 'Compares Events' UC). The Analyst repeats these steps until satisfied with the results. Analysts may provide feedback for previous Analysts during any of these steps (see 'Provides Analyst Feedback' UC). This use case is architecturally significant because it captures the interplay between all of the Analyst activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

ParelastiFWI 1.0 User Guide

ParelastiFWl is a python-based frontend to the seismic full waveform inversion process using Sandia Geophysics Department's 3-D isotropic elastic full waveform simulation code, Parelasti. The arguments one provides to ParelastiFWl guide the full waveform inversion process, including resolution of the inversion grid and basic regularization. This report outlines the user flags and ParelastiFWI usage to control the full waveform inversion procedure.

58 GEOSCIENCES↗
DOE OSTI2021

Aftershock Identification Using a Paired Neural Network Applied to Constructed Data

This report is intended to detail the findings of our investigation of the applicability of machine learning to the task of aftershock identification. The ability to automatically identify nuisance aftershock events to reduce analyst workload when searching for events of interest is an important step in improving nuclear monitoring capabilities and while waveform cross - correlation methods have proven successful, they have limitations (e.g., difficulties with spike artifacts, multiple aftershocks in the same window) that machine learning may be able to overcome. Here we apply a Paired Neural Network (PNN) to a dataset consisting of real, high quality signals added to real seismic noises in order to work with controlled, labeled data and establish a baseline of the PNN's capability to identify aftershocks. We compare to waveform cross - correlation and find that the PNN performs well, outperforming waveform cross - correlation when classifying similar waveform pairs, i.e., aftershocks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Preliminary Transfer Learning Results on Israel Data

In this preliminary report, we use publicly available data recorded in Israel to test and expand upon existing machine learning models for seismic-phase detection and arrival-time measurement. We downloaded 3-years of waveform data from Geofon, and cross referenced the waveforms to Israel bulletin picks (Schardong et al., 2021). The initial results using existing models directly generated ubiquitous false detections and that obscured detections of signals that are clearly visible in the waveforms. However, after applying transfer learning (tuning parameters in the existing ML models using one year of the Israel-network data), the results are encouraging, i.e. ML picks agree within a few tenths of a second with bulletin picks and the number of false detections is greatly reduced. The bulletin picks are a good starting point, but they cannot be considered ground-truth. To test potential improvement in picking using ML we would like to relocate the events using the ML picks to see if the events cluster more tightly at known mine locations. However, in order to constrain event locations, we need ML picks for the whole Israeli-Jordanian network, which requires waveforms that are not publicly available.

58 GEOSCIENCES↗
DOE OSTI2024

Electron Density Measurements Using USPR (Final Scientific/Technical Report)

UC Davis has fabricated an ultrashort pulse reflectometer (USPR) diagnostic instrument for electron density profile measurements on compact, short duration, magnetically-confined fusion-energy concept devices such as spheromaks and FRCs. The USPR system transmits extremely short duration (~few nsec) chirped waveforms that together span 29 to 75 GHz. These chirped waveforms illuminate and reflect from the target plasma, with each frequency component reflecting from a different density layer (higher frequencies probe deeper into the plasma before reflecting). The reflected waveforms are split into roughly 42 different frequencies; time-of-flight (TOF) measurements made at each frequency with high resolution (~25 psec measurement resolution which corresponds to ~5 mm). These TOF data may then be inverted via software to generate electron density profiles with high time resolution (~10 μsec). At the heart of the system is a field programmable gate array (FPGA) based controller which collects and processes all of the USPR data in addition to generating all of the control signals required for maximum flexibility. The FPGA controller has the software flexibility to be easily reconfigured for different plasma devices, and the entire system sufficiently compact to be easily and quickly transported between devices. A high speed impulse generator was transformed into a set of three ultrashort pulse transmitter chirps using a combination of dispersive waveguide, frequency doublers and high-pass filters. A mm-wave controller was fabricated to sequentially switch between the three chirps, directing the chirps one-by-one to three different mm-wave assemblies spanning 29-75 GHz. Each mm-wave assembly consists of a high power active multiplier chain which converts the transmitter chirp to higher frequencies, and a broadband mixer which downconverts the reflected waveform to the 2-18 GHz range of the UPSR receiver. The 16-channel receiver (shared by all 3 mm-wave assemblies) was fabricated employing custom TOF modules capable of operating at a high 1 MHz sampling rate. Laboratory testing of the full system revealed the presence of unwanted harmonics from the multiplication process, with interference observed in the downconverted reflections at selected frequency channels that could not be completely filtered out. Additional interference effects arising from internal reflections within the mm-wave assemblies were minimized using a high-speed switch which served to “gate out” much of these reflections. The USPR diagnostic was transported and installed onto the HIT-SIU plasma device, becoming operational on 11/08/2022. Although designed to span 3 distinct mm-wave bands, the HIT-SIU plasmas at this time were sufficiently low density such that only the lowest of the three bands was likely to have strong plasma reflections. The system was then set to operate on only the lowest band (assembly #1), with data collected every 1 μsec rather than 3 μsec which would have been the case when cycling through all three bands. Connected to HIT-SIU, time-varying plasma reflections were observed on 9 of 16 possible frequency channels. Close examination of the data collected revealed issues previously unobserved in laboratory testing, associated with (a) reflections from the small aperture horns required for operation within the HIT-SIU device, and (b) a dependence of the recorded TOF with the threshold voltage of a given channel. Plans were made to address each of these issues before undertaking any future campaigns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine Learning Inference of Random Medium Properties

Earth materials are heterogeneous across a range of spatial scales, but the resolvability of small structures is limited by sparse data coverage, noise, bandlimitedness, and other difficulties. In practice, heterogeneities below a certain size cannot be recovered from seismic data except through statistical medium descriptions, which even then can be difficult to uniquely determine. To improve the characterization of such heterogeneities, we develop a novel supervised machine learning (ML) model that provides insight about the recoverability of statistical medium properties from elastic waveform data and succeeds despite cycle-skipping and other challenges well known from elastic waveform inversion. We demonstrate the approach using random media generated by superimposing self-affine random variations on homogeneous and layered background structures. After training on sparsely-recorded, high-frequency waveforms from hundreds of different random medium realizations, we show the ability of our ML model to recover correlation lengths and other statistical properties of interest to near-surface and crustal seismology, among other fields. For frequency passbands and spatial offsets encountered in seismology, Gaussian correlation lengths and the amplitude of the random variations relative to the background model are recovered even in challenging scenarios involving unknown medium parameters, complex crustal structures, and low signal-to-noise ratio. In comparison, von Kármán correlation lengths, which are related to larger-wavelength variations of the medium than Gaussian correlation lengths, are not as well recovered. These results provide one of the first and most systematic investigations of the recoverability of statistical properties of heterogeneities below the resolution limit of deterministic seismic tomography, and suggest practical ML strategies for high-frequency waveform seismology.

58 GEOSCIENCES↗
DOE OSTI2023

How Dynamic Time Warping Can Assist Conventional Cross-correlation

Waveform cross-correlation is a sensitive phase-matched filtering technique that can detect seismic events for nuclear explosion monitoring. However, there are outstanding challenges with correlation detectors, most notably a direct dependence on the completeness of the waveform template library. To ameliorate these challenges, we investigate how dynamic time warping (DTW) may make waveform correlation more robust. DTW analyzes the differences between two time series and attempts to “warp” one time series relative to another in a recursive manner. We apply DTW to synthetic earthquake and recorded explosion templates to expand the capability of correlation detectors. We explore what conditions (e.g., source, station distance, frequency bands) and/or DTW algorithms generate stronger correlation scores. We show that DTW performs well on noisy signals and can dramatically improve the cross-correlation coefficient between a template and data-stream waveform. We conclude with recommendations on how to utilize DTW in nuclear monitoring detection.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Method of achieving ultra-wideband true-time-delay beam steering for active electronically scanned arrays

The various embodiments presented herein relate to beam steering an array antenna by modifying intermediate frequency (IF) waveforms prior to conversion to RF signals. For each channel, a direct digital synthesis (DDS) component can be utilized to generate a waveform or modify amplitude, timing and phase of a waveform relative to another waveform, whereby the generation/modification can be performed prior to the IF input port of a mixer on each channel. A local oscillator (LO) signal can be utilized to commonly drive each of the mixers. After conversion at the RF output port of each of the mixers, each RF signal can be transmitted by a respective antenna element in the antenna array. Initiation of transmission of each RF signal can be performed simultaneously at each antenna. The process can be reversed during receive whereby timing, amplitude, and phase of the received can be modified digitally post ADC conversion.

Loui, Hung↗
DOE OSTI2017

Combined radar and telemetry system

A combined radar and telemetry system is described. The combined radar and telemetry system includes a processing unit that executes instructions, where the instructions define a radar waveform and a telemetry waveform. The processor outputs a digital baseband signal based upon the instructions, where the digital baseband signal is based upon the radar waveform and the telemetry waveform. A radar and telemetry circuit transmits, simultaneously, a radar signal and telemetry signal based upon the digital baseband signal.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Converter topologies for common mode voltage reduction

An inverter includes a three-winding transformer, a DC-AC inverter electrically coupled to the first winding of the transformer, a cycloconverter electrically coupled to the second winding of the transformer, and an active filter electrically coupled to the third winding of the transformer. The DC-AC inverter is adapted to convert the input DC waveform to an AC waveform delivered to the transformer at the first winding. The cycloconverter is adapted to convert an AC waveform received at the second winding of the transformer to the output AC waveform having a grid frequency of the AC grid. The active filter is adapted to sink and source power with one or more energy storage devices based on a mismatch in power between the DC source and the AC grid. At least two of the DC-AC inverter, the cycloconverter, or the active filter are electrically coupled via a common reference electrical interconnect.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Gas stream analysis using voltage-current time differential operation of electrochemical sensors

A method for analysis of a gas stream. The method includes identifying an affected region of an affected waveform signal corresponding to at least one characteristic of the gas stream. The method also includes calculating a voltage-current time differential between the affected region of the affected waveform signal and a corresponding region of an original waveform signal. The affected region and the corresponding region of the waveform signals have a sensitivity specific to the at least one characteristic of the gas stream. The method also includes generating a value for the at least one characteristic of the gas stream based on the calculated voltage-current time differential.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Converter topologies and control

An inverter includes a transformer that includes a first winding, a second winding, and a third winding, a DC-AC inverter electrically coupled to the first winding of the transformer, a cycloconverter electrically coupled to the second winding of the transformer, an active filter electrically coupled to the third winding of the transformer. The DC-AC inverter is adapted to convert the input DC waveform to an AC waveform delivered to the transformer at the first winding. The cycloconverter is adapted to convert an AC waveform received at the second winding of the transformer to the output AC waveform having a grid frequency of the AC grid. The active filter is adapted to sink and source power with one or more energy storage devices based on a mismatch in power between the DC source and the AC grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Context-dependent piano music transcription with convolutional sparse coding

The present disclosure presents a novel approach to automatic transcription of piano music in a context-dependent setting. Embodiments described herein may employ an efficient algorithm for convolutional sparse coding to approximate a music waveform as a summation of piano note waveforms convolved with associated temporal activations. The piano note waveforms may be pre-recorded for a particular piano that is to be transcribed and may optionally be pre-recorded in the specific environment where the piano performance is to be performed. During transcription, the note waveforms may be fixed and associated temporal activations may be estimated and post-processed to obtain the pitch and onset transcription. Experiments have shown that embodiments of the disclosure significantly outperform state-of-the-art music transcription methods trained in the same context-dependent setting, in both transcription accuracy and time precision, in various scenarios including synthetic, anechoic, noisy, and reverberant environments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

System and method for instantaneous power decomposition and estimation

A system disaggregates and estimates power consumption of electric loads powered by a single electrical outlet. The system includes a processor having a routine; a current sensor cooperating with the processor to measure samples for one line cycle of an aggregated current waveform for the electric loads powered by the single electrical outlet; and a voltage sensor cooperating with the processor to measure samples for the one line cycle of a voltage waveform for the electric loads powered by the single electrical outlet. The processor routine transfers the measured samples for the one line cycle of the aggregated current waveform and the voltage waveform into an aggregated voltage-current trajectory for the single electrical outlet, and provides an instantaneous decomposition of power consumption for a plurality of different categories of the electric loads from the aggregated voltage-current trajectory for the one line cycle.

Yang, Yi↗
DOE OSTI2019

Method and system for estimating a rotor position with a notch filter

A motor has a rotor that rotates in response to one or more alternating current input signals. A position sensor is adapted to generate a substantially saw-tooth waveform indicative of a position of the rotor. A primary processing module or data processor is capable of providing position data and speed data for the rotor based on the substantially saw-tooth waveform. A notch filter can reject one or more selected frequency components in the substantially saw-tooth waveform to reduce distortion off the substantially saw-tooth waveform that would otherwise tend to cause inaccuracy in the provided position data and speed data.

Li, Dan↗
DOE OSTI2022

Harmonic combiner and divider

The harmonic combiner and divider efficiently combines multiple harmonic signals onto a common transmission line. Combined harmonic signals can be used to generate fast, high-fidelity arbitrary waveforms by superimposing the harmonics described in their Fourier series. Fast arbitrary waveforms have applications in communications, radar, and can be used for manipulating and controlling charged particle beams. The harmonic combiner and divider also efficiently divides fast arbitrary waveforms into their constituent harmonics and provides an efficient mechanism for waveform analysis and for multi-channel communications.

Roberts, Brock Franklin↗