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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

AGR-2 Data Qualification Report for ATR Cycle 154B

This report provides the data qualification status of Advanced Gas Reactor-2 (AGR-2) fuel irradiation experimental data from Advanced Test Reactor (ATR) Cycle 154B as recorded in the Nuclear Data Management and Analysis System (NDMAS). This is the last cycle of AGR-2 irradiation, as the test train was pulled from the ATR core during the outage portion of ATR Cycle 155A. The AGR-2 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates including new Fission Product Monitoring (FPM) downstream flows from Fission Product Monitoring System (FPMS) detectors, pressure, and moisture content), and FPMS data (release rates and release-to-birth rate ratios [R/Bs]) for each of the six capsules in the AGR-2 experiment. The final data qualification status for these data streams is determined by a Data Review Committee (DRC) comprised of AGR technical leads, Sitewide Quality Assurance (QA), and NDMAS analysts. The Data Review Committee reviewed the data acquisition process, considered whether the data met the requirements for data collection as specified in QA-approved Very High Temperature Reactor (VHTR) data collection plans, examined the results of NDMAS data testing and statistical analyses, and confirmed the qualification status of the data as given in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Assessing Low-Temperature Geothermal Play Types: Relevant Data and Play Fairway Analysis Methods

The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) is supporting the Geothermal Heating and Cooling Geospatial Datasets and Analysis project conducted by the National Renewable Energy Laboratory (NREL) as part of a broader effort to demonstrate the multi-faceted value of integrating geothermal power and geothermal heating and cooling (GHC) technologies into national decarbonization plans and community energy plans. Currently, there is a need to establish baseline low-temperature geothermal resource datasets and evaluate methods for deploying these technologies to provide the basis for supporting private sector investment. This project is focused on collecting baseline datasets, updating conceptual models, and creating Play Fairway Analysis (PFA) workflows for low-temperature (<150 degrees Celsius) geothermal resources of different geothermal play types (i.e., sedimentary basin, orogenic belts, and radiogenic geothermal play types) that could be used for geothermal heating and cooling (GHC), combined heat and power (CHP), and other geothermal direct uses (GDU) applications. Low-temperature geothermal resources are defined as reservoirs - natural or engineered - with temperatures <150 degrees Celsius. While the focus in the NREL effort is on GHC, resources at the upper end of this temperature range can also be used for small-scale power generation. This project does not include Ground Source Heat Pumps (GSHPs) technologies because they can be effectively developed almost anywhere. Low-temperature geothermal resources have not been studied as extensively as higher- to medium-temperature geothermal resources, but there is recent interest in improving understanding of these types of resources with an uptick of interest in geothermal technologies for decarbonizing heating and cooling systems. In addition, Enhanced Geothermal Systems (EGS) and other emerging technologies for exploiting petrothermal resources have opened the possibility of utilizing deep sedimentary basin systems, where porous media provide permeability and high temperatures can be reached at great depths. This project takes the approach of classifying low- temperature geothermal resources by geothermal play type (GPT). We defined and characterized three major classes of low-temperature GPT: sedimentary basins, orogenic systems, and radiogenic systems. We develop methodologies for evaluating and analyzing the potential for these resources building off the PFA approach to de-risking geothermal exploration and characterization. The proposed PFA approach for low-temperature geothermal resources includes: 1) identifying relevant data (e.g., datasets such bottom-hole temperatures from oil and gas wells, heat flow data, Quaternary faults and stress field data, geophysical data, etc.); 2) grouping and weighting of relevant datasets into PFA criteria (e.g., geological, risk, and economic criteria); 3) uncertainty quantification; 4) developing favorability or common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection; and 5) estimating electric power generation and heating potential at those locations using the GeoRePORT Resource Size Assessment Tool (RSAT). This project should facilitate future deployment of GHC, CHP, and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources. Increased deployment of GHC and GDU will help achieve national and local decarbonization goals.

15 GEOTHERMAL ENERGY↗
DOE OSTI2011

Bio-energy feedstock yields and their water quality benefits in Mississippi

Cellulosic and agricultural bio-energy crops can, under careful management, be harvested as feedstock for bio-fuels production and provide environmental benefits. However, it is required to quantify their relative advantages in feedstock production and water quality. The primary objective of this research was to evaluate potential feedstock yield and water quality benefit scenarios of bioenergy crops: Miscanthus (Miscanthus-giganteus), Switchgrass (Panicum virgatum), Johnsongrass (Sorghum halepense), Alfalfa (Medicago sativa L.), Soybean {Glycine max (L.) Merr.}, and Corn (Lea mays) in the Upper Pearl River watershed (UPRW), Mississippi using a Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated (January 1981 to December 1994) and validated (January 1995 to September 2008) using monthly measured stream flow data. The calibrated and validated model determined good to very good performance for stream flow prediction (R2 and E from 0.60 to 0.86). The RMSE values (from 14 m3 s-1 to 37 m3 s-1) were estimated at similar levels of errors during model calibration and validation. The long-term average annual potential feedstock yield as an alternative energy source was determined the greatest when growing Miscanthus grass (373,849 Mg) as followed by Alfalfa (206,077 Mg), Switchgrass (132,077 Mg), Johnsongrass (47,576 Mg), Soybean (37,814 Mg), and Corn (22,069 Mg) in the pastureland and cropland of the watershed. Model results determined that average annual sediment yield from the Miscanthus grass scenario determined the least (1.16 Mg/ha) and corn scenario the greatest (12.04 Mg/ha). The SWAT model simulated results suggested that growing Miscanthus grass in the UPRW would have the greatest potential feedstock yield and water quality benefits.

Biofuels↗
DOE OSTI2021

Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks

Subsurface permeability is a key parameter in watershed models that controls the contribution from the subsurface flow to stream flows. Since the permeability is difficult and expensive to measure directly at the spatial extent and resolution required by fully distributed watershed models, estimation through inverse modeling has had a long history in subsurface hydrology. The wide availability of stream surface flow data, compared to groundwater monitoring data, provides a new data source to infer soil and geologic properties using integrated surface and subsurface hydrologic models. As most of the existing methods have shown difficulty in dealing with highly nonlinear inverse problems, we explore the use of deep neural networks for inversion owing to their successes in mapping complex, highly nonlinear relationships. We train various deep neural network (DNN) models with different architectures to predict subsurface permeability from stream discharge hydrograph at the watershed outlet. The training data are obtained from ensemble simulations of hydrographs corresponding to an permeability ensemble using a fully-distributed, integrated surface-subsurface hydrologic model. The trained model is then applied to estimate the permeability of the real watershed using its observed hydrograph at the outlet. Our study demonstrates that the permeabilities of the soil and geologic facies that make significant contributions to the outlet discharge can be more accurately estimated from the discharge data. Their estimations are also more robust with observation errors. Compared to the traditional ensemble smoother method, DNNs show stronger performance in capturing the nonlinear relationship between permeability and stream hydrograph to accurately estimate permeability. Our study sheds new light on the value of the emerging deep learning methods in assisting integrated watershed modeling by improving parameter estimation, which will eventually reduce the uncertainty in predictive watershed models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

First STAX detector installation at the National Institute for Radioelements (IRE)

The Source Term Analysis of Xenon (STAX) project has been installing stack detectors at medical isotope production facilities to measure radioxenon emissions to investigate the effect of radioxenon releases on nuclear explosion monitoring. This paper outlines the installation of the first STAX detection system at the National Institute for Radioelements (IRE) in Fleurus, Belgium which has been operating for over three years and transferring collected data to the STAX repository. Information about the equipment installed, the data flow established, and calculations for determination of radioxenon releases from the facility are presented. Further. data quality was investigated to confirm values reported by STAX automated data processing and in a comparison of collected STAX data with data collected by IRE for regulatory reporting.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

AGC-4 Experiment Irradiation Monitoring Data Qualification Interim Report

The Graphite Technology Development Program is running a series of six experiments to quantify the effects of irradiation on nuclear grade graphite. The fourth experiment, Advanced Graphite Creep 4 (AGC 4), began with Advanced Test Reactor (ATR) cycle 157D on May 30, 2015, and has been irradiated for two cycles. The capsule was removed from the reactor after ATR cycle 158A, which ended on January 2, 2016, due to interference with another experiment. Irradiation will resume when the interfering experiment is removed from the reactor. This report documents qualification of AGC 4 experiment irradiation monitoring data for use by the Advanced Reactor Technologies (ART) Technology Development Office (TDO) Program for research and development activities required to design and license the first HTR nuclear plant. Qualified data meet the requirements for use as described in the experiment planning and quality assurance documents. Failed data do not meet the requirements and provide no useable information. Trend data may not meet all requirements, but still provide some useable information. Use of Trend data requires assessment of how any deficiencies affect a particular use of the data. All thermocouples (TCs) have functioned throughout the AGC-4 experiment. All temperature data are Qualified for use by the ART TDO Program. Argon, helium, and total gas flow data were within expected ranges and are Qualified for use by the ART TDO Program. Discharge gas line moisture values were consistently low during cycle 157D. At the start of cycle 158A, gas moisture briefly spiked to over 600 ppmv and then declined throughout the cycle. Moisture values are within the measurement range of the instrument and are Qualified for use by the ART TDO Program. Graphite creep specimens were subjected to one of three loads, 393, 491, or 589 lbf. For a brief period during cycle 157D between 12:19 on June 2, 2015 and 08:23 on June 11, 2015 the load cells were wired incorrectly resulting in missing stack load data. Missing stack loads were estimated from measured ram pressures using regression equations developed from the existing data from cycle 157D. Estimated stack loads during this period are considered to be an accurate representation of actual load applied to the stacks. These loads deviate slightly from the planned loads. This deviation does not prevent the data from being Qualified for use, but must be taken into account when analyzing the effect of load on creep. Stack displacement increased consistently throughout the first two cycles with total displacement ranging from 0.4 to 0.8 in. During ATR outages, a set of pneumatic rams raised the stacks of graphite creep specimens to ensure the specimens were not stuck within the test train. This stack raising was performed twice. All stacks were raised successfully each time. The load and displacement data are Qualified for use by the ART TDO Program.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The ARM Data System and Archive

Every observationally based research program needs a way to collect data from instruments, convert the data from its raw format into a more usable format, apply quality control, process it into higher-order data products, store the data, and make the data available to its scientific community. This data flow is illustrated pictorially in Fig. 11-1. These are the basic requirements of any scientific data system, and ARM’s data system would have to address these requirements and more. This research provides one view of the development of the ARM data system, which includes the ARM Data Archive, and some of the notable decisions that were made along the way.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

EGS-Collab Experiment 1: Time-lapse ERT Data and E4D Inversion Files for 10-24-2018 through 11-07-2018 Flow Test

This data submission includes the raw time-lapse ERT (electrical resistivity tomography) monitoring data, flow system data, operator logs, E4D (https://e4d.pnnl.gov) inversion files, and meta-data necessary to reproduce the 4D ERT inversion for the Oct. 24 through Nov. 7 2018 post-stimulation flow test in test bed 1. The tests were done at the Sanford Underground Research Facility at Homestake Mine in South Dakota.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Characterization of the initial state and QGP medium from a combined Bayesian analysis of LHC data at 2.76 and 5.02 TeV

Here, we perform a global Bayesian analysis of a modern event-by-event heavy-ion collision model and LHC data at √s = 2.76 and 5.02 TeV. After calibration, the model simultaneously describes multiplicity, transverse momentum, and flow data at both beam energies. We report new constraints on the scaling of initial-state entropy deposition and QGP transport coefficients, including a quantitative estimate of the temperature-dependent shear viscosity (η/s)( T ).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Sampling and Analysis Plan for LSL2 Underground Storage Tank Evaluation of PFAS in Soil: Protection of Groundwater

This SAP gathers all pertinent information relevant to the sampling and analysis of soil at the removal site for a former 10,000-gallon UST and reference sites in the vicinity of the excavation site. Data Quality Objectives establishes the process and steps for the acquisition of data. Data Flow Diagram establishes the decisions and next steps. Quality Assurance Project Plan establishes the quality requirements for data collection, including planning, implementation, and assessment of sampling, field measurements, and laboratory analysis. The work is being completed for DOE-SC Pacific Northwest Site Office.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Constitutive Behavior and Hot Workability of a Hot Isostatic Pressed Ti-22Al-25Nb Alloy during Hot Compression

A Ti-22Al-25Nb alloy was fabricated from prealloyed powders by hot isostatic pressing for 2 h at a temperature of 1050 °C and pressure of 100 MPa. The hot deformation behavior of the Ti-22Al-25Nb alloy was characterized by isothermal compression testing at deformation temperatures between 900 and 1060 °C and strain rates between 0.001 and 1 s{sup −1}. Based on the true stress–strain curves, a constitutive equation was constructed to describe the flow stress as a function of the strain rate and deformation temperature. Three-dimensional (3D) processing maps were developed based on dynamic material model theory using the stress flow data to identify the instability and optimization regions of the hot processing parameters. The results show that the flow stress decreases with increasing deformation temperature and decreasing strain rate, and the softening mechanisms are different under different deformation conditions. The apparent activation energies in the (α{sub 2} + β/B2 + O) and (α{sub 2} + B2) phase regions are calculated to be 865.177 and 590.661 kJ/mol, respectively, which suggests that the hot isostatic pressed (HIPed) Ti-22Al-25Nb alloy requires a high hot deformation activation energy. Combined with microstructural observations, the optimal processing domains are determined to be a temperature range of 1030-1060 °C and strain rate range of 0.01-0.1 s{sup −1} in the α{sub 2} + B2 phase region. Moreover, the results indicate that adiabatic shear bands and severe inhomogeneous deformation cause flow instability at lower temperatures (900-1005 °C) and higher strain rates (> 0.1 s{sup −1}).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Municipal Adaptation to Changing Curbside Demands: Findings from Semi-Structured Interviews with Ten U.S. Cities

Emerging mobility services (e.g. ride-hailing, e-commerce, micro-mobility, etc.), are generating novel and rapidly growing demands to use curbside space, with potentially large impacts on mobility, energy consumption, and related outcomes. This presents both opportunities and challenges to municipal agencies responsible for managing this interface between the road network and adjacent land uses, as legacy practices require updating. In this study, we employ a semi-structured interviewing approach to establish how municipalities are adapting to these new pressures on their curbside. We interviewed senior staff responsible for curbside policy of ten large U.S. municipalities, with populations ranging from ~250,000 to ~5,000,000 (and the majority of which are the central city of their metropolitan region). We document a trend of organizational restructuring to more formally include curbside management teams, with the majority of interviewees also reporting increased staffing. Respondents reported that operational failures at their curbside (e.g. demand in excess of capacity) have impacts on safety, capacity, and emergency vehicle mobility, with impacts highly concentrated spatially and temporally (e.g. late evenings in nightlife districts). We document a diversity of data flows between ride-hailing operators (e.g. Uber, Lyft) and municipalities, with some cities reporting obtaining types of data that other cities report not receiving, despite requesting such data. Finally, respondents consistently expressed a desire for new data streams and methodologies to help manage the curbside of the future. It is hoped that establishing the state of practice in this rapidly changing context will be of use to practitioners facing similar pressures as those of our interviewees.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

The Hybrid Toolkit

The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.

Davis IV, WarrenL↗
DOE OSTI2013

Developing Load Cell Monitoring on the Mock UF 6 Feed and Withdrawal System

A proof-of-concept load cell monitoring system has been developed for the Mock Feed and Withdrawal (F&W) System at Oak Ridge National Laboratory (ORNL). This system leverages industry-standard commercial off-the-shelf (COTS) hardware and software in a modular and scalable design. The Mock F&W System was designed to simulate operations at a uranium hexafluoride (UF 6 ) gas centrifuge enrichment plant F&W area. It provides a test bed for process-monitoring technologies. Water, used as a surrogate for UF 6 , is pumped from three feed tanks, through a process surge tank, and is then cut between two tails tanks and three product tanks. The weight of the each tank is continuously monitored using a load cell monitoring system. In addition to the F&W stations, large and small accountancy stations are monitored. The Mock F&W System allows ORNL to test and evaluate capabilities of industry-standard process monitoring hardware and software. A variety of commonly used weighing indicators are connected to the load cells to monitor the weight at each station. These weighing indicators are representative of the types likely found in operating facilities. A data center modeled after those currently used for international safeguards was installed to collect and manage the weight data. This data center provides a robust and flexible test bed for testing and developing software solutions. COTS software packages that leverage industry-standard communication protocols provide a data flow architecture that is modular, interoperable, and scalable. One software package provides communication drivers to collect the raw weight data from the weighing indicators. A data historian is used to store the raw data. Custom in-house algorithms have been developed using MATLAB to analyze the raw historical data and to automatically identify process information. This information includes the number of cycles completed and the mass of material transferred from stations to the process. The process information identified by the analysis is stored in a Microsoft SQL Server database. Visualization concepts have been developed that display the analyzed process information alongside visually compelling plots and animations of the raw data. The load cell monitoring system developed on the Mock F&W System was designed as a proof of concept that could be scaled to a field trial at an operating facility. This system, built with industry standard hardware and software, has allowed ORNL to develop capabilities that provide confidence in the ability to leverage existing operator load cell monitoring equipment with minimal impact on operations. The international safeguards community is evaluating the use of load cell monitoring as an additional safeguards measure; this system demonstrates a practical solution to collect, store, analyze, and visualize load cell weight data.

commercial off the shelf↗
DOE OSTI2017

Packet Capture Solutions: PcapDB Benchmark for High-Bandwidth Capture, Storage, and Searching

PcapDB stands alone when looking at the overall field of competitors, from the cost-effective COTS hardware, to the efficient utilization of disk space that enables a longer packet history. A scalable, 100GbE-enabled system that indexes every packet and indexes flow data without complicated load-balancing requirements. The Transport Layer search and indexing approach led to patent-pending flow indexing technology, providing a specialized database system specifically optimized around providing fast flow searches. While there are a plethora of options in network packet capture, there are very few that are able to effectively manage capture rates of more than 10 Gb/s, distributed capture and querying, and a responsive user interface. By far, the primary competitor in the market place is Endace and DeepSee; in addition to meeting the technical requirements we set out in this document, they provide technical support and a fully 'appliance like' system. In terms of cost, however, our experience has been that the yearly maintenance charges alone outstrip the entire hardware cost of solutions like PcapDB. Investment in cyber security research and development is a large part of what has enabled us to build the base of knowlegable workers needed to defend government resources in the rapidly evolving cyber security landscape. We believe projects like Bro, WireCap, and Farm do more than just fill temporary gaps in our capabilities. They give allow us to build the firm foundation needed to tackle the next generation of cyber challenges. PcapDB was built with loftier ambitions than simply solving the packet capture of a single lab site, but instead to provide a robust, scaleable packet capture solution to the DOE complex and beyond.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

The Hybrid Toolkit

The Hybrid Toolkit facilitates moving research algorithms into a production environment by creating useful abstractions that separate analytics developers from the intricacies of the production data formats, data flows, and result representations. The toolkit also assists developers with activities such as creating analysis feature vectors, converting between data structures, and creating data pipelines.

Davis IV, Warren L↗