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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Characterization of D-T Generator Neutron Flux Spectrum for Cyclic Neutron Activation Analysis Experiments

Improving nuclear data for short-lived fission product yields will further our fundamental understanding of fission, which is needed across various scientific fields and applications. One method of attaining the needed product yield data is through cyclic neutron activation, which allows a target to be irradiated in a neutron environment and then transported for counting of the radionuclides produced, typically via g spectroscopy. Recently, such a system has been constructed and commissioned at Pacific Northwest National Laboratory. Targets are shuttled between the head of a D-T neutron generator and a counting station with a transit time of 2 seconds. As part of the characterization of this system, the neutron flux was studied using two activation targets. The neutron flux from the deuterium-tritium fusion generator was determined to be 9.95(33) x10^8 n/cm2-s with a peak energy of 14.9 MeV and a spread of approximately 4 decades between the epithermal and 14 MeV peak group flux.

cyclic neutron activation, gamma-ray spectroscopy,↗
DOE OSTI2013

DTS Raw Data Guelph, Ontario Canada

Unprocessed active distributed temperature sensing (DTS) data from 3 boreholes in the Guelph, ON Canada region. Data from borehole 1 was collected during a fluid injection while data from boreholes 2 and 3 were collected under natural gradient conditions in a lined borehole. The column labels/headers (in the first row) define the time since start of measurement in seconds and the row labels/headers (in the first column) are the object IDs that are defined in the metadata. Each object ID is a sampling location whose exact location is defined in the metadata file. Data in each cell are temperature in Celsius at time and sampling location as defined above.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

NARSTO.ORG: Historical NARSTO Program Assessments and Website Contents, 1995-2010

This package contains the Historical NARSTO Program Assessments and Website Content. NARSTO was a public/private partnership dedicated to improving management of air quality in North America. It was established on February 13, 1995 when representatives of Canada, the United States, and Mexico signed the NARSTO Charter in a ceremony at the White House. (Originally North American Research Strategy for Tropospheric Ozone.) The NARSTO organization, having met the goals of its 1995 charter, was disbanded as of December 31, 2010. Since its founding, NARSTO has completed four major scientific Assessments of critical air quality management issues. NARSTO maintained the Quality Systems Science Center and the NARSTO Data Archive for storing data from NARSTO Affiliated Research Activities and making these data available to the scientific community. NARSTO also facilitated activities, such as the Reactivity Research Working Group, which provide critical reviews of the state of the science in areas of interest to air quality policy makers. NARSTO worked to improve collaboration between the air-quality and health-sciences research communities, to advance understanding of the scientific issues involved in effecting a multi-pollutant/multi-media approach to air quality management, and to increase understanding of the linkages between air quality and climate change.The NARSTO assessments and narsto.org website content are available at this data archive and may be downloaded in one .zip file. Data from NARSTO sponsored field campaigns will remain available through the Permanent Data Archive maintained by the NASA Langley Research Center Atmospheric Science Data Center (https://asdc.larc.nasa.gov/project/NARSTO).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2019

Recovery of Buried Discrete Radioactive Objects by Channel-Specific Analysis of Gamma Scan Data - 19110

During radiological clean-up activities, gamma scan survey data collected from across an industrial site revealed spatially varying concentrations in radioactivity related to naturally occurring soil constituents or dissimilar fill materials that may have been placed at the site. A three-step process was developed to assess the data in order to identify radiation anomalies that most likely could represent small, buried discrete radioactive objects (ROs). The three-step process consists of: (1) define the radiological composition of the site isotopically, (2) spatially parse the data into more homogeneous subgroupings based on the site's radiological composition, and (3) perform analysis of the data subgroupings to identify statistical and spatial population outliers (i.e., radiation anomalies) that otherwise may be masked by the overall variation in the data. Using this process, locations containing buried low-specific activity ROs or higher activity ROs whose radiation is attenuated by soil can be identified and investigated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Crystal structure and activity studies of the C11 cysteine peptidase from Parabacteroides merdae in the human gut microbiome

Clan CD cysteine peptidases, a structurally related group of peptidases that include mammalian caspases, exhibit a wide range of important functions, along with a variety of specificities and activation mechanisms. However, for the clostripain family (denoted C11), little is currently known. Here, we describe the first crystal structure of a C11 protein from the human gut bacterium, Parabacteroides merdae (PmC11), determined to 1.7-Å resolution. PmC11 is a monomeric cysteine peptidase that comprises an extended caspase-like α/β/α sandwich and an unusual C-terminal domain. It shares core structural elements with clan CD cysteine peptidases but otherwise structurally differs from the other families in the clan. These studies also revealed a well ordered break in the polypeptide chain at Lys 147 , resulting in a large conformational rearrangement close to the active site. Biochemical and kinetic analysis revealed Lys 147 to be an intramolecular processing site at which cleavage is required for full activation of the enzyme, suggesting an autoinhibitory mechanism for self-preservation. PmC11 has an acidic binding pocket and a preference for basic substrates, and accepts substrates with Arg and Lys in P1 and does not require Ca 2+ for activity. Altogether, these data provide insights into the mechanism and activity of PmC11 and a detailed framework for studies on C11 peptidases from other phylogenetic kingdoms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Image-domain DAS 3D VSP elastic transmission tomography

SUMMARY Full-wavefield elastic imaging of active-source seismic data acquired by downhole receivers commonly offers higher-resolution subsurface images in the vicinity of a borehole compared to conventional surface seismic data sets, which can lack higher-frequency wavefield components due to longer travel paths and increased attenuation. An increasingly used approach for downhole acquisition is vertical seismic profiling (VSP), which has become more attractive when coupled with distributed acoustic sensing (DAS) using optical fibres installed in wells. The main difficulty for generating high-quality images with full-wavefield imaging tools for DAS VSP data, though, is the need for an accurate velocity model. To build plausible velocity models using active-source DAS VSP data, we adopt a 3-D image-domain elastic transmission tomography technique, originally developed for surface-recorded passive (microseismic) data, by exchanging the source and receiver positions (i.e. reciprocity) to mimic a passive-seismic surface monitoring scenario. The inversion approach exploits various images for each source constructed through time-reverse imaging (TRI) of downgoing P- and S-wave first-arrival waveforms. The TRI process uses the kinetic term of the (extended) PS energy imaging condition that exhibits sufficient sensitivity to velocity model errors. The method automatically updates the P- and S-wave velocity models to optimize image focusing via adjoint-state inversion. We illustrate the efficacy of the adopted elastic inversion technique using an active-source DAS 3-D VSP field data set acquired in the North Slope of Alaska. The numerical experiments demonstrate that the inverted elastic velocity models can be further used in full-wavefield acoustic/elastic imaging algorithms to obtain accurate subsurface images.

Oren, Can (ORCID:000000019534265X)↗
DOE OSTI2025

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

MISIP: a data standard for the reuse and reproducibility of any stable isotope probing-derived nucleic acid sequence and experiment

DNA/RNA-stable isotope probing (SIP) is a powerful tool to link in situ microbial activity to sequencing data. Every SIP dataset captures distinct information about microbial community metabolism, process rates, and population dynamics, offering valuable insights for a wide range of research questions. Data reuse maximizes the information derived from the labor and resource-intensive SIP approaches. Yet, a review of publicly available SIP sequencing metadata showed that critical information necessary for reproducibility and reuse was often missing. Here, we outline the Minimum Information for any Stable Isotope Probing Sequence (MISIP) according to the Minimum Information for any (x) Sequence (MIxS) framework and include examples of MISIP reporting for common SIP experiments. Our objectives are to expand the capacity of MIxS to accommodate SIP-specific metadata and guide SIP users in metadata collection when planning and reporting an experiment. The MISIP standard requires 5 metadata fields—isotope, isotopolog, isotopolog label, labeling approach, and gradient position—and recommends several fields that represent best practices in acquiring and reporting SIP sequencing data (e.g., gradient density and nucleic acid amount). The standard is intended to be used in concert with other MIxS checklists to comprehensively describe the origin of sequence data, such as for marker genes (MISIP-MIMARKS) or metagenomes (MISIP-MIMS), in combination with metadata required by an environmental extension (e.g., soil). The adoption of the proposed data standard will improve the reuse of any sequence derived from a SIP experiment and, by extension, deepen understanding of in situ biogeochemical processes and microbial ecology.

Simpson, Abigayle↗
DOE OSTI2016

Accelerating Energy Efficiency in Indian Data Centers. Final Report for Phase I Activities

This report documents Phase 1 of the “Accelerating Energy Efficiency in Indian Data Centers” initiative to support the development of an energy efficiency policy framework for Indian data centers. The initiative is being led by the Confederation of Indian Industry (CII), in collaboration with Lawrence Berkeley National Laboratory (LBNL)-U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy, and under the guidance of Bureau of Energy Efficiency (BEE). It is also part of the larger Power and Energy Efficiency Working Group of the US-India Bilateral Energy Dialogue. The initiative consists of two phases: Phase 1 (November 2014 – September 2015) and Phase 2 (October 2015 – September 2016).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Large emissions of CO2 and CH4 due to active-layer warming in Arctic tundra: Supporting Data

Climate warming may accelerate decomposition of Arctic soil carbon, but few controlled experiments have manipulated the entire active layer. To determine surface-atmosphere fluxes of carbon dioxide and methane under anticipated end-of-century warming, we used heating rods to warm soil (by 3.8 °C) to the depth of permafrost in polygonal tundra over two growing seasons at the Barrow Environmental Observatory in Utqiaġvik (formerly Barrow), Alaska. This data product includes supporting data for the companion paper entitled "Large emissions of CO2 and CH4 due to active-layer warming in Arctic tundra", published in Nature Communications by Torn et al. This data package contains seven data files in csv format with corresponding data dictionaries and file-level metadata, describing vegetation biomass dry weight ("Utqiagvik_Vegetation_Biomass_2014.csv"), radiocarbon measurements of respired carbon dioxide ("Utqiagvik_Radiocarbon_2015_2016.csv"), surface-atmosphere fluxes of carbon dioxide and methane and associated soil temperature ("Utqiagvik_Fluxes_Temperature_2015_2016.csv"), and soil temperature measurements averaged every 15-min and 1-hr for 2015 and 2016 ("Utqiagvik_Temperature_15min_2015.csv", "Utqiagvik_Temperature_15min_2016.csv", "Utqiagvik_Temperature_1hr_2015.csv", "Utqiagvik_Temperature_1hr_2016.csv"). There are no specific software requirements to use these data. UIC Science Native Corporation facilitated our scientific research on the Barrow Environmental Observatory, which is Iñupiat land.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 OSTI2024

pyEGAF: Modernization of the EGAF database

One of the most comprehensive resources for thermal neutron-capture data is the Evaluated Gamma-ray Activation File (EGAF), containing data from prompt gamma activation analysis measurements carried out at the Budapest Research Reactor for 245 isotopes. Although these valuable datasets have been freely available for many years, the outdated and cryptic adopted format makes it difficult to utilize the data and it is not generally suitable for modern computational technologies. Furthermore, to help overcome these challenges, we have converted the datasets into an open standard JSON format. Additionally, we have developed a Python implementation of an open-source software package, pyEGAF, designed to interact with the JSON data structures for general purpose access, manipulation, and rapid assessment of the capture-gamma data in EGAF.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

CACTI Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed a large number of instruments to a region nearby the Sierra de Córdobas mountains in Argentina as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign (1). During this campaign, four radars were installed at a site outside of Villa Yacanto as shown in Figure 1. As part of a post-campaign effort to improve the usability of these data, a significant activity was undertaken towards the calibration, correction, and improvement of the data quality of these radar datastreams. This process in ARM nomenclature is referred to as generating a “b1” datastream. While these “b1” standards may imply different corrections or standards for various ARM instruments, for radars it refers to a datastream that has been calibrated (and cross-calibrated), including a serious effort to deliver the highest-quality (well-characterized) data possible. This report details (i) the status/quality of the original “a1” (raw) data, (ii) the corrections and calibrations that are applied to generate these b1 datastreams, (iii) the details of the applied algorithms and how radar offset/calibration numbers were determined for the eventual corrections, and (iv) the new and flexible plug-in-based processing system designed during CACTI for radar b1 activities (current, future) that interfaces with ARM’s Data Integrator (ADI) and high-performance computing (HPC) system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities

Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term of condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMs cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve ice water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional ice water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud ice water contents in support of cloud modeling activities. The approach of the study is to expand a (surface) point measurement to an (satellite) area measurement. That is, the study takes the advantage of the high quality cloud measurements (particularly cloud radar and microwave radiometer measurements) at the point of the ARM sites. We use the cloud ice water characteristics derived from the point measurement to guide/constrain a satellite retrieval algorithm, then use the satellite algorithm to derive the 3-D cloud ice water distributions within an 10° (latitude) x 10° (longitude) area. During the research period, we have developed, validated and improved our cloud ice water retrievals, and have produced and archived at ARM website as a PI-product of the 3-D cloud ice water contents using combined satellite high-frequency microwave and surface radar observations for SGP March 2000 IOP and TWP-ICE 2006 IOP over 10 deg. x 10 deg. area centered at ARM SGP central facility and Darwin sites. We have also worked on validation of the 3-D ice water product by CloudSat data, synergy with visible/infrared cloud ice water retrievals for better results at low ice water conditions, and created a long-term (several years) of ice water climatology in 10 x 10 deg. area of ARM SGP and TWP sites and then compared it with GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development of an Activation Analysis Methodology to Support the Disposal of the High Flux Isotope Reactor Metal Pool Waste

During operation and maintenance of the High Flux Isotope Reactor (HFIR), metal waste from reactor components is generated. Due to space limitations in the pool fuel storage, it is necessary to remove the waste and send it to off-site disposal. Most of this waste was in the reactor and is radioactive through neutron activation. Prior to shipping and disposal at a waste disposal facility, the radiological activity of the waste must be determined. Therefore, a conservative methodology to characterize the radiological activity of the waste must be performed. The methodology used was based on being able to determine a conservative overall activity and radionuclide inventory based on radiological survey data and neutron activation products for the materials present.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Analyzing shear band formation with high resolution X-ray diffraction

Localization of crystallographic slip into shear bands during uniaxial compression of a copper single crystal is studied using very far-field high-energy diffraction microscopy (vff-HEDM). Diffracted intensity was collected in-situ as the crystal deformed using a unique mobile detector stage that provided access to multiple diffraction peaks with high-angular resolution. From the diffraction data, single crystal orientation pole figures (SCPFs) were generated and are used to track the evolution of the distribution of lattice orientation that develops as slip localizes. To aid the identification of 'signatures' of shear band formation and analyze the SCPF data, a model of slip-driven lattice reorientation within shear bands is introduced. Confidence is built in conclusions drawn from the SCPF data about the character of internal slip localization through comparisons with strain fields on the sample surface measured simultaneously using digital image correlation. From the diffraction data, we find that the active slip direction and slip plane are not directly aligned with the orientation of the shear bands that formed. In fact, by extracting the underlying slip system activity from the SCPF data, we show that intersecting shear bands measured on the surface of the sample arise from slip primarily on the same underlying single slip system. These new vff-HEDM results raise significant questions on the use of surface measurements for slip system activity estimation. (C) 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

36 MATERIALS SCIENCE↗
DOE OSTI2010

Annual Hanford Seismic Report for Fiscal Year 2010

The Hanford Seismic Assessment Program (HSAP) provides an uninterrupted collection of high-quality raw and processed seismic data from the Hanford Seismic Network for the U.S. Department of Energy and its contractors. The HSAP is responsible for locating and identifying sources of seismic activity and monitoring changes in the historical pattern of seismic activity at the Hanford Site. The data are compiled, archived, and published for use by the Hanford Site for waste management, natural phenomena hazards assessments, and engineering design and construction. In addition, the HSAP works with the Hanford Site Emergency Services Organization to provide assistance in the event of a significant earthquake on the Hanford Site. The Hanford Seismic Network and the Eastern Washington Regional Network consist of 44 individual sensor sites and 15 radio relay sites maintained by the Hanford Seismic Assessment Team. During FY 2010, the Hanford Seismic Network recorded 873 triggers on the seismometer system, which included 259 seismic events in the southeast Washington area and an additional 324 regional and teleseismic events. There were 210 events determined to be local earthquakes relevant to the Hanford Site. One hundred and fifty-five earthquakes were detected in the vicinity of Wooded Island, located about eight miles north of Richland just west of the Columbia River. The Wooded Island events recorded this fiscal year were a continuation of the swarm events observed during fiscal year 2009 and reported in previous quarterly and annual reports (Rohay et al. 2009a, 2009b, 2009c, 2010a, 2010b, and 2010c). Most events were considered minor (coda-length magnitude [Mc] less than 1.0) with the largest event recorded on February 4, 2010 (3.0Mc). The estimated depths of the Wooded Island events are shallow (averaging approximately 1.5 km deep) placing the swarm within the Columbia River Basalt Group. Based upon the last two quarters (Q3 and Q4) data, activity at the Wooded Island area swarm has largely subsided. Pacific Northwest National Laboratory will continue to monitor for activity at this location. The highest-magnitude events (3.0Mc) were recorded on February 4, 2010 within the Wooded Island swarm (depth 2.4 km) and May 8, 2010 on or near the Saddle Mountain anticline (depth 3.0 km). This latter event is not considered unusual in that earthquakes have been previously recorded at this location, for example, in October 2006 (Rohay et al. 2007). With regard to the depth distribution, 173 earthquakes were located at shallow depths (less than 4 km, most likely in the Columbia River basalts), 18 earthquakes were located at intermediate depths (between 4 and 9 km, most likely in the pre-basalt sediments), and 19 earthquakes were located at depths greater than 9 km, within the crystalline basement. Geographically, 178 earthquakes were located in known swarm areas, 4 earthquakes occurred on or near a geologic structure (Saddle Mountain anticline), and 28 earthquakes were classified as random events. The Hanford Strong Motion Accelerometer (SMA) network was triggered several times by the Wooded Island swarm events and the events located on or near the Saddle Mountain anticline. The maximum acceleration value recorded by the SMA network during fiscal year 2010 occurred February 4, 2010 (Wooded Island swarm event), approximately 2 times lower than the reportable action level for Hanford facilities (2% g) with no action required.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Materials Characterization, Prediction and Control Project: Summary Report on Data Analytics Framework

This report summarizes the activities performed under the data analytics Vertex in the Materials Characterization, Prediction and Control Project funded under laboratory directed research and development at Pacific Northwest National Laboratory. The data analytics Vertex developed models for associating global or local process parameters, microstructural features, and performance properties of friction-stir-processed 316L stainless steel plates. Statistical, machine learning, and deep learning models, as well as generative artificial intelligence approaches, were used to develop the associations between the process-structure-property data streams. These associations formed the basis for predicting global properties of parts manufactured under different process envelopes, providing a basis for predicting performance using data driven as well as physics-informed and physics-constrained approaches. Additionally, the associations were used to predict local process parameters and microstructural features of the product, predictive relationships that have the potential to form the basis of a control framework that could eventually modulate a friction-stir process to maintain product quality.

316L stainless steel↗