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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Breakthrough Listen Search for Intelligent Life: A 3.95–8.00 GHz Search for Radio Technosignatures in the Restricted Earth Transit Zone

We report on a search for artificial narrowband signals of 20 stars within the restricted Earth Transit Zone (rETZ) as a part of the ten-year Breakthrough Listen (BL) search for extraterrestrial intelligence (ETI). The rETZ is the region of the sky from which an observer would see Earth transit the Sun with an impact parameter of less than 0.5. This region of the sky is geometrically unique, providing a potential way for an ETI to discover the solar system. The targets were nearby (7–143 pc) and the search covered an electromagnetic frequency range of 3.95–8.00 GHz. We used the Robert C. Byrd Green Bank Telescope to perform these observations with the standard BL data recorder. We searched these data for artificial narrowband (∼Hz) signals with Doppler drift rates of ±20 Hz s{sup −1}. We find no evidence for radio technosignatures from ETI in our observations. The observing campaign would have allowed for detections of emissions that were 10{sup −3} to 0.88 times as powerful as the signaling capability of the Arecibo radar transmitter. We conclude that at least 0.6% of the systems in the rETZ within 150 pc do not possess the type of transmitters searched in this survey. To our knowledge, this is the first targeted search for ETI of the rETZ. All data used in this paper are publicly available via the BL Public Data Archive (http://seti.berkeley.edu/bldr2).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

System and method of managing large data files

Disclosed are systems and software that provide a high-performance, extensible file format and web API for remote data access and a visual interface for data viewing, query, and analysis. The described system can support storage of raw spectroscopic data such as neural recording data, MSI data, metadata, and derived analyses in a single, self-describing format that may be compatible by a large range of analysis software.

Bowen, Benjamin P.↗
DOE OSTI2024

Characterization of a CMOS camera based film digitization platform for gated x-ray imaging diagnostics at the National Ignition Facility

Hardened gated x-ray detectors use photographic film as the data recording medium due to its low sensitivity to the high-yield neutron environments at the National Ignition Facility (NIF). The photographic film is digitized with a Photometric Data Systems (PDS) microdensitometer, which measures the film’s optical density. The PDS scanner is able to measure a dynamic range of 0–5 OD; however, raster scanning the film is time consuming and maintenance of the instrument is challenging due to legacy technology. Since film usage at NIF is expected to continue in the foreseeable future, a digitization platform that is faster and more maintainable would benefit the NIF’s current and future operations. Here, this work presents the characterization of the digital transitions (DT) atom, a CMOS camera-based digitization platform that records film data in a single image capture very quickly and has widely available user support. The preliminary results suggest that the DT atom is able to reconstruct exposures accurately enough to be a competitive alternative to the PDS Scanner.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

EV-ELM (Electric Vehicle Policies with the Energy Language Model) [SWR-25-156]

Electric Vehicle Policies with the Energy Language Model (EV-ELM) leverages previous work using Large Language Models (LLMs) to find, download, and parse policy information related to energy infrastructure. In this application, we use LLMs to find policy documents related to the permitting and installation of electric vehicle charging infrastructure. This software contains the code to find, download, and parse these documents, while a related data record in the Open Energy Data Initiative (OEDI) will include the resulting output dataset that can be used for downstream analysis. The EV-ELM repository contains code for the EV-ELM project, which focuses on retrieving and processing EV permitting processes using large language models. The project is composed of two pipelines: (1) a web scraping pipeline for discovering and downloading EV permitting documents, and (2) a document parsing and extraction pipeline that processes the downloaded files to produce structured data. The web scraping pipeline is designed to extract relevant information from various websites, while the document parsing pipeline processes and analyzes the extracted documents to derive meaningful insights. Both pipelines depend on the NLR elm repository, which provides essential tools and functionalities for handling and processing the data. The web scraping pipeline is a modified version of the ordinance_gpt example within the elm repository. It has been adapted to fit the specific requirements of the EV-ELM project, ensuring that it effectively captures and processes the necessary information related to EV permitting.

Olson, Reid [National Laboratory of the Rockies (N↗
DOE OSTI2025

Rapid and Temporary Deployment of Fiber-Optic Arrays to Measure Surface Chemical Explosion Series with Distributed Acoustic Sensing

Rapid and temporary distributed acoustic sensing (DAS) deployments are crucial for accurately capturing the seismic wavefield following major events, such as earthquakes, or in anticipation of known events of interest, such as chemical explosions. We provide an overview of two DAS campaigns conducted in May and October 2024 to record the seismoacoustic waves generated by two series of surface chemical explosions in New Mexico, United States, involving 1- and 10-ton trinitrotoluene-equivalent charges. In both campaigns, we deployed approximately 2 km of fiber-optic cables in a dry riverbed, about 12 km east of the explosion sites. For the October campaign, seven geophones and two anemometers were collocated with the fiber. We describe the field deployments and present preliminary results from the recorded signals. Specifically, we cross analyze the data recorded in May and October, validate the DAS data with geophone measurements, and highlight the benefits of burying fibers to reduce wind noise and improve signal-to-noise ratios. This study demonstrates the potential of DAS to record the seismoacoustic waves generated by surface chemical explosions of varying sizes at distances of approximately 10 km from the source.

58 GEOSCIENCES↗
DOE OSTI2021

White Rabbit Time Synchronization for Radiation Detector Readout Electronics

As radiation detector arrays in nuclear physics applications become larger and physically more separated, the time synchronization and trigger distribution between many channels of detector readout electronics become more challenging. Clocks and triggers are traditionally distributed through dedicated cabling, but newer methods such as the IEEE 1588 Precision Time Protocol and White Rabbit allow clock synchronization through the exchange of timing messages over Ethernet. Consequently, we report here the use of White Rabbit in a new detector readout module, the Pixie-Net XL. Herein, the White Rabbit core, data capture from multiple digitizing channels, and subsequent pulse processing for pulse height and constant fraction timing are implemented in a Kintex 7 FPGA. The detector data records include White Rabbit time stamps and are transmitted to storage through the White Rabbit core's gigabit Ethernet data path or a slower diagnostic/control link using an embedded Zynq processor. The performance is characterized by time-of-flight style measurements and by time correlation of high energy background events from cosmic showers in detectors separated by longer distances. Software for the Zynq processor can implement "software triggering", for example to limit recording of data to events where a minimum number of channels from multiple modules detect radiation at the same time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Idaho National Laboratory Data Acquisition And Processing System

The INLDAS data acquisition and processing system is designed to develop prototype measurements and real-time processing techniques. The INLDAS hardware and firmware currently consists of National Instruments • NI-DAQmx 14.1 • cDAQ-9184 • 9205 • 9211 INLDAS can perform of standard data acquisition functions as well as novel functions and real-time processing algorithms. There are 3 acquisition modes to choose from: • Continuous mode runs when the user hits start, processing data and logging it to file • SWTrigger mode waits for one or more predefined triggers before acquiring data. It will buffer data as well, so it can record data that happened shortly before the trigger • Wakeup mode waits on predefined timers. When a time goes off, it acquires a preset amount of data There are also 3 Data Processing Modes • Normal mode does no processing besides the rolling average • FFT Mode Performs an FFT on incoming data every time the time window has elapsed • STFFT mode

Smith, JamesA↗
DOE OSTI2020

Measurement of J/ψ production in association with a W± boson with pp data at 8 TeV

A measurement of the production of a prompt J/ψ meson in association with a W ± boson with W± → μν and J/ψ → μ + μ - is presented for J/ψ transverse momenta in the range 8.5–150 GeV and rapidity |y J/ψ | < 2.1 using ATLAS data recorded in 2012 at the LHC. The data were taken at a proton-proton centre-of-mass energy of $\sqrt{s}$ = 8 TeV and correspond to an integrated luminosity of 20.3 fb -1 . The ratio of the prompt J/ψ plus W ± cross-section to the inclusive W ± cross-section is presented as a differential measurement as a function of J/ψ transverse momenta and compared with theoretical predictions using different double-parton-scattering cross-sections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Demonstration of INCC6 for advanced list-mode data acquisition and analysis using ALMM

The International Neutron Coincidence Counting (INCC) software plays an important role in nuclear safeguards and nuclear material control and accounting (NMC&A) measurements. While the current version, INCC5, represents the traditional standard utilized by inspectorates as well as facilities and practitioners alongside shift register hardware, LANL has recently developed an upgraded version of the software, INCC6. INCC6 offers the same analysis tools as INCC5 while adding new capabilities including acquisition and analysis of list-mode data, recording and storage of list-mode data files, and an expanded set of advanced analysis tools that make use of the additional information available from list-mode data. Here, this paper presents the first demonstration of data acquisition and analysis using INCC6 and the Advanced List Mode Multiplicity Module (ALMM). The capability of INCC6 to perform live list-mode data acquisition and analysis is demonstrated for a variety of neutron sources with a range of neutron emission rates relevant for practical applications and validated against the results obtained with INCC5 and traditional shift register hardware. Advanced list-mode analysis tools introduced by INCC6, such as time-interval and coincidence matrix analysis, are also demonstrated. Finally, the capability of INCC6 to analyze list-mode data files is tested and validated against traditional shift register results using INCC5.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Luminosity determination using Z boson production at the CMS experiment

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton–proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13 TeV. Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20 pb –1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Climatology Perspective of Sensitive Regimes and Active Regions of Aerosol Indirect Effect for Cirrus Clouds over the Global Oceans

Long-term satellite climate data records (CDRs) of clouds and aerosols are used to investigate the aerosol indirect effect (AIE) of cirrus clouds over the global oceans from a climatology perspective. Our study focuses on identifying the sensitive regimes and active regions where AIE signatures easily manifest themselves in the sense of the long-term average of cloud and aerosol variables. The aerosol index (AIX) regimes of AIX < 0.18 and 0.18 < AIX < 0.46 are respectively identified as the sensitive regimes for negative and positive aerosol albedos and lifetime effects of cirrus clouds. Relative humidity first decreases (along with upward motions) and then reverses to increase (along with downward motions) in the first regime of negative aerosol albedo and lifetime effects. Relatively wet and strong upward motions are the favorable meteorological conditions for the second regime of positive aerosol albedo and lifetime effects. Two swath regions extending from 15°N to 30°N over the east coastal oceans of China and the USA are the active regions of positive aerosol albedo effects. Positive aerosol lifetime effects are only active or easy to manifest in the regions where a positive aerosol albedo effect is active. The results based on the long-term averaged satellite observations are valuable for the evaluation and improvement of aerosol-cloud interactions for cirrus clouds in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A database of battery materials auto-generated using ChemDataExtractor

A database of battery materials is presented which comprises a total of 292,313 data records, with 214,617 unique chemical-property data relations between 17,354 unique chemicals and up to five material properties: capacity, voltage, conductivity, Coulombic efficiency and energy. 117,403 data are multivariate on a property where it is the dependent variable in part of a data series. The database was auto-generated by mining text from 229,061 academic papers using the chemistry-aware natural language processing toolkit, ChemDataExtractor version 1.5, which was modified for the specific domain of batteries. The collected data can be used as a representative overview of battery material information that is contained within text of scientific papers. Public availability of these data will also enable battery materials design and prediction via data-science methods. To the best of our knowledge, this is the first auto-generated database of battery materials extracted from a relatively large number of scientific papers. We also provide a Graphical User Interface (GUI) to aid the use of this database.

25 ENERGY STORAGE↗
DOE OSTI2020

Inverting infrasound data for the seismoacoustic source time functions and surface spall at the Source Physics Experiments Phase II: Dry Alluvium Geology

This report presents the infrasound data recorded as part of the Source Physics Experiment - Phase 2, Dry Alluvium Geology. This experiment, also known colloquially as DAG, consisted of four underground chemical explosions at the Nevada National Security Site. We focus our analysis on only the fourth explosion (DAG-4) as we determined that this was the only event that produced clear source-generated infrasound energy as recorded by the DAG sensors. We analyze the data using two inversion methods. The first method is designed to estimate the point-source seismoacoustic source time functions, and the second inversion method is designed to estimate the first-order characteristics (e.g. horizontal dimensions and maximum amplitude) of the actual spall surface. For both analysis methods, we are able to fit the data reasonably well, with various assumptions of the source model. The estimated seismoacoustic source appears to be a combination of a buried, isotropic explosion with a maximum amplitude of ~2 x 10 9 Nm and a vertically oriented force, applied to the Earth's surface with a maximum amplitude of 4 x 10 7 N. We use the vertically oriented force to simulate surface spall. The estimated spall surface has an approximate radius of ~40 m with a maximum acceleration magnitude in the range of 0.8 to 1.5 m/s/s. These estimates are approximately similar to the measured surface acceleration at the site.

58 GEOSCIENCES↗
DOE OSTI2023

Acoustic Research under the Source Physics Experiment

The Source Physics Experiment series is a long-term research and development (R&D) effort under the U.S. Department of Energy’s National Nuclear Security Administration focused on improving the physical understanding of how chemical explosions generate seismoacoustic signals. Beginning in 2011, a series of subsurface chemical explosions in two different and highly contrasting geologies were conducted at the Nevada National Security Site in Nevada, USA with the objective of improving simulation and modeling approaches to explosion identification, yield estimation and other monitoring applications. The two executed phases of the series provide new explosion signature source data from a wide range of geophysical diagnostic equipment; recorded data from the test series is now openly available to the broader seismoacoustic community. This manuscript details the executed test series, deployed seismoacoustic networks, and summarizes major scientific achievements utilizing recorded signatures from the explosive tests.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

A Differentiable Hydrology Approach for Modeling With Time-Varying Parameters

In the analysis of observational data with mathematical models, it is often desirable to let one or more model parameters vary with time to account for changing environmental conditions or to offer more flexibility. A standard approach for dynamic models is to allow for the number of parameters to grow as a function of time, leading to a high-dimensional inference problem for long data records. We propose using Hamiltonian Monte Carlo, a gradient-based Markov chain Monte Carlo (MCMC) method, to perform Bayesian inference for time-varying parameters (TVP) in hydrology models. As derivatives of model error functions with regard to parameters are not available in closed form, we implemented the GR4J rainfall-runoff models in Theano/PyMC3, and Jax/NumPyro, allowing for the application of automatic differentiation techniques. A simulation experiment assessing the viability of these methods for recovering underlying temporal variation in parameters indicates that a discrete Gaussian random walk-based prior appears to be best suited across a range of scenarios while the continuous-time Gaussian process compares relatively poorly. In an analysis of 20 years of daily real-world streamflow records from the Model Parameter Estimation Experiment (MOPEX) hydrology data set with increasing data sparsity and at multiple temporal resolutions, we find that TVP inference with gradient-based MCMC is a flexible and reliable approach for analyzing hydrology models with dynamic parameter sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

NIR fluorescence lifetime macroscopic imaging with a time-gated SPAD camera

The performance of SwissSPAD2 (SS2), a large scale, widefield time-gated CMOS SPAD imager developed for fluorescence lifetime imaging, has recently been described in the context of visible range and fluorescence lifetime imaging microscopy (FLIM) of dyes with lifetimes in the 2.5 – 4 ns range. Here, we explore its capabilities in the NIR regime relevant for small animal imaging, where its sensitivity is lower and typical NIR fluorescent dye lifetimes are much shorter (1 ns or less). We carry out this study in a simple macroscopic imaging setup based on a compact NIR picosecond pulsed laser, an engineered diffuser-based illumination optics, and NIR optimized imaging lens suitable for well-plate or small animal imaging. Because laser repetition rates can vary between models, but the synchronization signal frequency accepted by SS2 is fixed to 20 MHz, we first checked that a simple frequency-division scheme enables data recording for different laser repetition rates. Next, we acquired data using different time gate widths, including gates with duration longer than the laser period, and analyzed the resulting data using both standard nonlinear least-square fit (NLSF) and phasor analysis. We show that the fixed synchronization rate and large gate widths characterizing SS2 (10 ns and over) are not an obstacle to accurately extracting lifetime in the 1 ns range and to distinguishing between close lifetimes. As a result, SS2 and similar very large gated SPAD imagers appear as a versatile alternative to other widefield time-resolved detectors for NIR fluorescence lifetime imaging, including preclinical molecular applications.

FLIM↗
DOE OSTI2024

Machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado and New Mexico

Temporally continuous snow depth estimates are vital for understanding changing snow patterns in the Arctic and impacts on permafrost. We trained random forest machine learning models to predict snow depth from temperature data recorded at or just below the ground surface. Training data was collected at the Teller 27 Watershed and Kougarok 64 Hillslope during the 2021 - 2022 water year on the Seward Peninsula, Alaska using distributed temperature profiling (DTP) systems. We then applied this model to other sites where ground surface or shallow soil temperature data was available for at least one water year (see Related Datasets). Many of these temperature measurements were collocated with snow depth observations. Ground surface temperature (i.e. snow-ground interface temperature) is easy to measure using small, cheap and easy-to-deploy temperature sensors such as iButtons and TinyTags, and such measurements have previously been used to calculate a variety of snow metrics (e.g. snow onset date). However, this is the first study to estimate snow depth directly from ground surface temperature data. The present dataset contains one *.csv file which includes machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado, and New Mexico and one *.kml file including the locations of sites with snow depth predictions. No training data predictions are included in the *.csv file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗