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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Use Case Realization Report: UCR-03.02.08 Compares Events

This architecturally significant use case describes how the Analyst compares events to determine how similar events were constructed. The Analyst compares waveforms from comparison events by visually inspecting an overlay of the waveforms to determine if the events are from a similar source. The Analyst searches for comparison events or creates agglomerative hierarchical clusters of waveforms from events and determines that the events are from a similar source if the correlation coefficient is above a selected threshold. This use case is architecturally significant due to the introduction of the capability to compare events within an operational context.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Computational Approach for Improving Three-Dimensional Sub-Surface Earth Structure for Regional Earthquake Hazard Simulations in the San Francisco Bay Area

In our Exascale Computing Project (ECP) we seek to simulate earthquake ground motions at much higher frequency than is currently possible. Previous simulations in the SFBA were limited to 0.5-1 Hz or lower (Aagaard et al. 2008, 2010), while we have recently simulated the response to 5 Hz. In order to improve confidence in simulated ground motions, we must accurately represent the three-dimensional (3D) sub-surface material properties that govern seismic wave propagation over a broad region. We are currently focusing on the San Francisco Bay Area (SFBA) with a Cartesian domain of size 120 x 80 x 35 km, but this area will be expanded to cover a larger domain. Currently, the United States Geologic Survey (USGS) has a 3D model of the SFBA for seismic simulations. However, this model suffers from two serious shortcomings relative to our application: 1) it does not fit most of the available low frequency (< 1 Hz) seismic waveforms from moderate (magnitude M 3.5-5.0) earthquakes; and 2) it is represented with much lower resolution than necessary for the high frequency simulations (> 5 Hz) we seek to perform. The current model will serve as a starting model for full waveform tomography based on 3D sensitivity kernels. This report serves as the deliverable for our ECP FY2017 Quarter 4 milestone to FY 2018 “Computational approach to developing model updates”. We summarize the current state of 3D seismic simulations in the SFBA and demonstrate the performance of the USGS 3D model for a few selected paths. We show the available open-source waveform data sets for model updates, based on moderate earthquakes recorded in the region. We present a plan for improving the 3D model utilizing the available data and further development of our SW4 application. We project how the model could be improved and present options for further improvements focused on the shallow geotechnical layers using dense passive recordings of ambient and human-induced noise.

58 GEOSCIENCES↗
DOE OSTI2018

Seismic Analysis of Spatio-Temporal Fracture Generation During EGS Resource Development

This DOE GTO funded project was a collaborative effort between Array Information Technology and the University of California at Berkeley. The project goal is to improve technology to assess in-situ stress magnitude and orientation, kinematic fracture parameters, rupture size, rupture orientation as well as temporal changes and volumetric distribution of the injected fluid during Enhanced Geothermal System (EGS) resource development. The project leveraged high-frequency seismic data recorded by the LBNL 34-station permanent geophone network and seismic broadband data recorded by a temporary 33-station seismometer network that operated in The Geysers during the injection phase of the DOE GTO funded EGS demonstration project at the well Prati-32. The operation of the broadband network with high station density and good azimuthal coverage to monitor the injection phase produced an unprecedented dataset that is typically unavailable for EGS operations. The two datasets offer the advantages of studying the parameters under investigation over a broader frequency band and the higher sensitivity of the broadband seismometers resulted in a richer dataset with a lower magnitude of completeness. Moment tensor (MT) inversion have been employed to develop a catalog of earthquake source solutions including moment tensor and finite source rupture area. This resulted in a 168-event waveform-based seismic moment tensor catalog for events 0.7≤Mw≤3.9 based on a semi-automated moment tensor analysis technique. The MT solutions were used for in-situ stress estimation during the EGS injection phases. We found an approximate 15-degree counterclockwise rotation of the least compressive stress sigma-3, and a rotation of the maximum compressive stress sigma-1 toward the vertical as the injected volume of water increased. We developed a rupture-area magnitude scaling relationship of The Geysers earthquakes obtained from finite-source inversion for fault slip that reveals a very high correlation to published results. Based on the rupture area-magnitude relationship we mapped Mw from the LBNL earthquake catalog to estimate the activated fracture area, its location and orientation within the injection volume of Prati-32. The double-difference Wadati (DDW) technique was applied to high-accuracy P- and S-wave differential travel times derived from waveform cross correlation to image fluid saturation in the subsurface based on Vp/Vs-ratio. The recently developed technique has been applied to estimate temporal changes of fluid distribution in fault zones and in volcanic regions but not yet in engineered geo-reservoirs. The improvement of the technology includes high-resolution waveform cross correlation applied to the high-quality datasets with lower magnitude of completeness resulting in a higher number of recorded events. The improvement allowed to estimate both, the spatial and temporal distribution of injected fluids and the state of the injected fluid during reservoir stimulation. Results of the DDW analysis revealed the development of an injection-derived steam plume during the early injection phase, particularly in the northern part of the Prati-32 study area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Do large and small earthquakes start alike? Rupture determinism and earthquake early warning

Do earthquakes large and small begin alike, or are there systematic differences in the nucleation or early rupture process that determine the final earthquake size? This question of rupture determinism is one of the outstanding challenges in earthquake physics, and has significant implications for earthquake early warning systems, which rely on the ability to rapidly estimate earthquake magnitudes based on small snapshots of waveform data. Here I examine the question of rupture determinism using a massive dataset of strong-motion acceleration waveforms from M4-9 earthquakes occurring near Japan over the past 20 years. We analyze the time-evolution of peak displacement from more than 130,000 strong-motion waveforms, finding no significant evidence for deterministic rupture in our dataset. We then use these observations to develop a rigorous Bayesian framework for calculating time-dependent uncertainties in earthquake early warning systems like ShakeAlert, which is currently undergoing testing for the western United States. This work forms the basis for future data-driven studies designed to improve methodology used real-time geophysical hazard assessments.

58 GEOSCIENCES↗
DOE OSTI2016

Characterizing Photometric Flicker

The focus of this study is simply to report on the commercial availability and performance of emerging flicker meters. Commercial-meter measurements and calculations were compared against those generated by a photoelectric characterization system developed by the Pacific Northwest National Laboratory (PNNL). The results and analysis show that the three commercially available flicker meters evaluated for this study measured light-intensity waveforms and calculated essential flicker-performance characteristics and metrics similarly, both to each other and to the reference meter chosen as an accuracy benchmark. Some differences in performance were found, however, when measurements were taken of light-intensity waveforms with significant high-frequency content – greater than the dominant 120 Hz found in many products at full output. Such conditions may be found in light sources that employ pulse-width modulation to achieve their target light output (e.g., intensity or color). If the meter was not appropriately configured (e.g., sampling frequency was too low), or if proper configuration was not possible given meter constraints (e.g., maximum number of available data points), then the waveform characteristics were not accurately captured, often resulting in the calculation of flicker metrics that deviated significantly from the reference.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Applications of seismic threshold monitoring at an Antarctic glacier [Slides]

Geophysical waveforms collected from Arctic regions provides data required for monitoring global security targets. Some seismic instruments deployed on Scandinavian and Greenlandic sites provide waveform data, but these installations include specific challenges: Sea ice and glacial ice generates waveform interference; Meltwater generates narrowband interference, resembling tonal noise.

58 GEOSCIENCES↗
DOE OSTI2021

Open Source Fault-tolerant Grid Frequency Measurement for Solar Inverters

The Discrete Fourier transform (DFT) based measurement algorithms are one of the most common measurement algorithms for grid parameter estimation such as rms, phase angle, frequency. Over the past few years, many DFT based algorithms have been developed to enhance its measurement accuracy under steady-state and/or dynamic grid conditions. For example, an adaptive band-pass filter utilizing exponential modulation filter has been proposed to reduce measurement errors at the presence of large frequency deviations. Measurement accuracy of different algorithms including FIR filter, extended Kalman filtering (EKF), and enhanced DFT method have been compared in detail under different grid conditions. Two artificial signals that have 90-degree phase difference were constructed by the Clarke transformation to address the frequency spectrum leakage of DFT. A multi-module approach was developed to enhance both steady-state and dynamic measurement accuracies, in which each module was developed to eliminate some specific errors. Besides DFT-based measurement algorithms, some signal model-based algorithms have been developed to further improve the accuracy under dynamic conditions. However, a key drawback of the state-of-the-art algorithms is that they cannot perform measurements accurately during system transient faults. In the Blue Cut Fire event, there was a phase angle jump of about 26 degrees in the voltage waveform during the transient fault. The phase angle jump fault will cause waveform discontinuity, and these algorithms will fail to provide reliable measurements during this period because they typically assume the waveform to be measured is continuous, no matter what method (DFT, PLL, EKF, FIR, or Taylor WLS) is used for estimation. In fact, the measurement errors during the system transient faults like phase-jump is not required in the IEEE Standard. As a result, although a measurement instrument can pass the strict IEEE Standard, it could still be the source of the problem in the future if we have similar system transient faults, which could happen again. Therefore, developing the fault-tolerant measurement technology is the key to solve the problem.

14 SOLAR ENERGY↗
DOE OSTI2019

SRF Cavity Fault Classification Using Machine Learning At CEBAF

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is the first large high power CW recirculating electron accelerator to make use of SRF accelerating structures. The structures are configured in two anti-parallel linacs connected by arcs. Each linac consists of twenty C20/C50 cryomodules each containing eight 5-cell cavities and five C100 upgrade cryomodules each containing eight 7-cell cavities. Accurately classifying the source of cavity faults is critical for improving accelerator performance. A cavity fault triggers a waveform acquisition process where 17 waveform records sampled at 5 kHz are recorded for each of the 8 cavities in the affected cryomodule. The waveform record length is sufficiently long for transient microphonic effects to be observable. This data combined with archived signals sampled at 10 Hz are used to classify faults. Significant time is required for a subject matter expert to analyze and identify the intra-cavity signatures of imminent faults. This paper describes a path forward that utilizes machine learning for automatic fault classification. Post-training identification of the physical origins of faults are discussed, as are potential machine-trained model-free implementations of trip avoidance procedures. These methods should provide new insights into cavity fault mechanisms and facilitate intelligent optimization of cryomodule performance

Solopova, A.↗
DOE OSTI2023

A case study of denoising microseismic data in the Farnsworth, TX CO 2 EOR site

As geologic carbon sequestration projects begin to be funded with a higher degree of frequency, microseismic monitoring will become more necessary to establish caprock integrity and induced seismicity risk. The Farnsworth, TX site, which hosts enhanced oil recovery operations, provides an ideal laboratory to test essential components of microseismic monitoring such as surface station placement, denoising, and different autopicker methods. We find that despite careful optimization, the surface station placement at the Farnsworth site was insufficient given the high level of background noise from the industrial operations at the oil field. Thus, we use only borehole geophone data in our processing. Two denoising techniques were examined: the DeepDenoiser and the continuous wavelet transform. The continuous wavelet transform was shown to be a valuable tool in converting between raw waveforms to processed denoised waveforms for microseismic monitoring. In the case of the noisy waveforms, only ten detections are found, compared with 90 in the denoised data for a two-hour window. The DeepDenoiser suffered from the fact that the training data was regional earthquake data. In addition, the PhaseNet machine-learning autopicker was applied to both the noisy and the denoised data, and this algorithm detected thousands of more arrivals in the data denoised with the continuous wavelet transform technique.

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↗
DOE OSTI2024

Seismic Signal Detection on International Monitoring System 3-Component Stations using PhaseNet

In this report we discuss training a deep learning seismic signal detection model on 3-component stations from the International Monitoring System (IMS) using the PhaseNet architecture. Using 14 years of associated signals from the International Data Centre’s (IDC) Late Event Bulletin (LEB), we auto-curated training data consisting of signal windows containing associated arrivals, and noise windows that contain no LEB-associated signals. We trained several models using different waveform window durations (30 seconds and 100 seconds), with and without bandpass filtering. We evaluated the effectiveness of our models using associated signals from the Unconstrained Global Event Bulletin (UGEB) and found that several of our models outperformed the signal detections from the IDC’s Selected Event List 3 (SEL3) arrival table. The SEL3 bulletin evaluated on the UGEB dataset with 100-second waveform windows registered a precision and recall of .15 and .48, respectively, versus .19 and .59 for our filtered-data model. For the 30-second waveform window dataset, the SEL3 bulletin achieved a precision and recall of .31 and .47, respectively, versus .32 and .60 for our filtered-data model. Finally, our models detected signals from all source-to-receiver distances, suggesting it is feasible to use a single PhaseNet model for the IMS network.

58 GEOSCIENCES↗
DOE OSTI2025

Remote Instrumentation and Data Acquisition

This poster outlines the development and implementation of a remote data acquisition system for waveform analysis using a Rohde & Schwarz oscilloscope. The project involved capturing waveform data, and transferring it to a local machine for visualization and analysis. The core logic was developed in C++ with a focus on object oriented programming and the use of polymorphism so the main application can interact with any instrument without knowing its exact type, simplifying the overall logic and making it easier to add or swap out components without changing the rest of the codebase.. The system issues Standard Commands for Programmable Instruments (SCPI) via a socket connection and parses the oscilloscope s ASCII waveform data. The C++ application was containerized using Docker for ease of portability, and reproducibility. Emphasis was placed on secure networking practices, error handling, and effective data capture. The report describes the technical steps taken, challenges encountered, and future work, providing insight into the practical integration of hardware interfacing with remote computational environments.

Parikh, Jaymil [Illinois U., Urbana]↗
DOE OSTI2023

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

What the Flicker is going on here? Temporal Light Modulation in Automotive Lighting

Temporal light modulation (TLM), colloquially known as “flicker,” is once again an issue in almost all lighting applications, due to widespread adoption of LED and OLED sources and their driving electronics. A subset of LED/OLED lighting systems delivers problematic TLM, often in specific types of residential, commercial, outdoor, and vehicular lighting. Dashboard displays, touchscreens, marker lights, taillights, daytime running lights, interior lighting, etc. frequently use PWM circuits to achieve different luminances for different times of day and user visual adaptation levels. The resulting TLM waveforms and viewing conditions can result in distraction and disorientation, nausea, cognitive effects, and serious health consequences in some populations, occurring with or without the driver, passenger, or pedestrian consciously “seeing” the flicker. There are three visual responses to TLM: direct flicker, the stroboscopic effect, and phantom array effect (also called the “beads effect”). Metrics for the first two have limitations in both calculation and application. The phantom array effect has no established visibility measure at all, and this is the effect most associated with vehicular flicker because of the widespread use of PWM. Conventional wisdom from the recent past, especially concerning acceptable driver frequency ranges, needs to be reconsidered and replaced with improved guidelines to protect health and comfort. Four principal TLM waveform characteristics affect TLM visibility: frequency, modulation depth, duty cycle, and waveshape. This paper proposes much higher frequency operation if PWM control cannot be avoided; but it may be possible to modify the four principal waveform characteristics together in order to achieve reduced TLM visibility and improved health and comfort.

flicker, TLM, temporal light modulation, automotiv↗
DOE OSTI2022

Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)

Abstract. Arctic rain on snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack from rain and increased melt, there was a 4-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a 6-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of the CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows that the rain and refreeze were significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice

Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0° (nadir) and 50°. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A Bunch Compression Method for Free Electron Lasers that Avoids Parasitic Compressions

Virtually all existing high energy (>few MeV) linac-driven FELs compress the electron bunch length though the use of off-crest acceleration on the rising side of the RF waveform followed by transport through a magnetic chicane. This approach has at least three flaws: 1) it is difficult to correct aberrations--particularly RF curvature, 2) rising side acceleration exacerbates space charge-induced distortion of the longitudinal phase space, and 3) all achromatic "negative compaction" compressors create parasitic compression during the final compression process, increasing the CSR-induced emittance growth. One can avoid these deficiencies by using acceleration on the falling side of the RF waveform and a compressor with M 56 >0. This approach offers multiple advantages: 1) It is readily achieved in beam lines supporting simple schemes for aberration compensation, 2) Longitudinal space charge (LSC)-induced phase space distortion tends, on the falling side of the RF waveform, to enhance the chirp, and 3) Compressors with M 56 >0 can be configured to avoid spurious over-compression. We will discuss this bunch compression scheme in detail and give results of a successful beam test in April 2012 using the JLab UV Demo FEL

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Gamma ray spectroscopy employing divalent europium-doped alkaline earth halides and digital readout for accurate histogramming

According to one embodiment, a scintillator radiation detector system includes a scintillator, and a processing device for processing pulse traces corresponding to light pulses from the scintillator, where the processing device is configured to: process each pulse trace over at least two temporal windows and to use pulse digitization to improve energy resolution of the system. According to another embodiment, a scintillator radiation detector system includes a processing device configured to: fit digitized scintillation waveforms to an algorithm, perform a direct integration of fit parameters, process multiple integration windows for each digitized scintillation waveform to determine a correction factor, and apply the correction factor to each digitized scintillation waveform.

36 MATERIALS SCIENCE↗