Results for “Lab data'” — Page 39

DOE OSTI2018

Methods and Models for Analyzing Methane Sorption Capacity of Coal Based on Its Physicochemical Characteristics

The authors study the influence of physicochemical parameters on methane adsorption capacity of coal and offer the analytical method for the methane adsorption capacity for three-phased condition of methane. It is found that in the depth interval to 300 m below surface, methane adsorption capacity measured in lab can exceed natural gas content of coal obtained from geological exploration data by 30%, and the change in the thermodynamic condition of coal–methane system brings irreversible physicochemical consequences in terms of the altered ratios of physical states of the main components. There is no linear connection between natural gas content of a coal bed and its methane adsorption capacity with respect to occurrence depth. The application of Big Data in treatment and interpretation of large data flows is described. The theoretical data predicted using the proposed method and the experimental data on methane content of Kuzbass coal agree.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2014

K{sub S} Lambda Photoproduction On The Neutron Within The Resonance Region

We report some preliminary differential cross section results for the gammad --> K{sub S} Lambda(p) reaction using a circularly-polarized photon beam and an unpolarized LD{sub 2} target. The data was collected at the CEBAF Large Acceptance Spectrometer (CLAS) at Jefferson Lab. For this study the photon energy ranged from 1.3 to 2.53 GeV, which covers from the reaction threshold through the nucleon resonance regimes. The acceptance- and flux-corrected yields show peaks at the center-of mass energies W = 1.7 and W = 1.9 GeV. These first-time results will aid in unraveling the spectrum of non-strange excited baryons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

sas-temper

Modeling remains a considerable challenge for practitioners of SAXS and SANS because the materials being studied are not highly ordered, the length scales being studied are large, and the information content of the data is low. Data analysis is both challenging and time consuming. Novices often rely on the assistance of an expert, such as the instrument scientist who supported them at the facility where the experiment was performed, to analyze their data. The high flux provided by modern facilities makes it possible to study dozens of samples or sample conditions during a single trip. Ultimately, the high throughput of modern instruments limits access to instrument scientists. A bottleneck in the research effort results that reduces facility productivity. Sas-temper seeks to address this problem, as well as the intrinsic difficulties of being confident in non-linear least squared fitting of data, by providing tools that automate much of the manual process of initial data fitting and refinement, as well as by providing tools for characterizing the nature of the parameter space that fits the measured data. The tools provided by sas-temper help small-angle scattering practitioners transition data into results.

Heller, William [Oak Ridge National Lab. (ORNL), O↗

DOE OSTI2022

DistGANS- Distributed Generative Adversarial Neural Networks

DistGANs is a Python package to perform distributed training of conditional generative adversarial neural networks for multi-class labeled image data. DistGANs partitionins the training data according to data labels, and enhances scalability by performing a parallel training where multiple generators are concurrently trained, each one of them focusing on a single data label.

Lupo Pasini, Massimiliano [Oak Ridge National Lab.↗

DOE OSTI2025

PNNL-Predictive-Phenomics/ProteoMeter

ProteoMeter is a Python package that assists in the statistical analysis of global proteomics, protein post-translation modification (PTM), and limited proteolysis (LiP) data. It contains batch correction, normalization, and statistical testing methods, as well as functions that "roll up" peptide-level data to the single-site level. It has a robust user configuration system, allowing it to flexibly integrate different types of experiment designs. For basic usage, a simple configuration file provides the essential functionality. Advanced users have access to the entire statistical pipeline for fine-tuning analyses. Processed data is easily exported to many common spreadsheet and data-frame formats.

Rozum, Jordan [Pacific Northwest National Lab]↗

DOE OSTI2022

Utah FORGE: Results of Direct Shear Tests on Saturated Joints in Sierra White Granite

This dataset includes an Excel file with the results of direct shear tests to investigate the mechanical and geophysical response of saturated joints. Tests were conducted on induced tension-fractured Sierra White granite joints in a custom water pressurized chamber. The preparation of granite joints is summarized in the PDF file. The PDF file also includes a description of the direct shear tests, experimental procedure, and results.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Eddy Correlation Flux Measurement System (ECOR) Instrument Handbook

The eddy correlation (ECOR) flux measurement system provides in situ, half-hour measurements of the surface turbulent fluxes of momentum, sensible heat, latent heat, and carbon dioxide (CO 2 ) (and methane at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s North Slope of Alaska central facility [NSA Barrow], and at the ARM Mobile Facility (AMF) deployment at Oliktok Point). The fluxes are obtained with the eddy covariance technique, which involves correlation of the vertical wind component with the horizontal wind component, the air temperature, the water vapor density, and the CO 2 concentration. The instruments used are: a fast-response, three-dimensional (3D) wind sensor (sonic anemometer) to obtain the orthogonal wind components and the speed of sound (SOS) (used to derive the air temperature), an open-path infrared gas analyzer (IRGA) to obtain the water vapor density and the CO 2 concentration, and an open-path infrared gas analyzer (IRGA) to obtain methane density and methane flux at NSA Barrow and at the AMF deployment at Oliktok Point. The ECOR systems are deployed at the locations where other methods for surface flux measurements (e.g., energy balance Bowen ratio [EBBR] systems) are difficult to employ, primarily at the north edge of a field of crops. A surface energy balance system (SEBS) has been installed collocated with each deployed ECOR system in SGP, NSA, Tropical Western Pacific (TWP), and each of three ARM Mobile Facilities. The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. Finally, the SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Technical Documents for Gateway for Accelerated Innovation in Nuclear (GAIN)

The Gateway for Accelerated Innovation in Nuclear (GAIN) provides the nuclear energy community with access to the technical, regulatory, and financial support necessary to move new or advanced nuclear reactor designs toward commercialization. GAIN provides the nuclear community with a single point of access to the broad range of capabilities (i.e., people, facilities, materials, and data) across the U.S. Department of Energy (DOE) complex and its National Lab capabilities. The Fast Flux Test Facility (FFTF) is the most recent liquid metal reactor (LMR) to be designed, constructed, and operated by DOE. The 400-MWt sodium-cooled, fast-neutron flux reactor plant was designed for irradiation testing of nuclear reactor fuels and materials for liquid metal fast breeder reactors. Following the demise of the breeder reactor program in the United States, FFTF continued to play a key role in providing a test bed for demonstrating performance of advanced fuel designs and demonstrating operation, maintenance, and safety of advanced liquid metal reactors. The FFTF Program provides valuable information for potential follow-on reactor projects in the areas of plant system and component design, component fabrication, fuel design and performance, reactor control, prototype testing, and site construction. This report provides documents related to three important aspects of FFTF design and operation: 1) irradiation behavior of structural alloys and absorber materials, 2) thermohydraulics of rod bundles (i.e., coolant mixing), and 3) natural circulation heat transfer in the areas of modeling and validation. These technical documents are believed to be of interest to the nuclear industry and in particular to designers of new liquid metal reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System, Meet Future Demand for City Passenger and Delivery Load/Unload Spaces, and Reduce Energy Consumption

This three-year project supported by the U.S. Department of Energy Vehicle Technologies Office has the potential to radically improve the urban freight system in ways that help both the public and private sectors. Working from 2018-2021, project researchers at the University of Washington’s Urban Freight Lab and collaborators at the Pacific Northwest National Laboratory have produced key data, tested technologies in complex urban settings, developed a prototype parking availability app, and helped close major knowledge gaps. All the fruits of this project can be harnessed to help cities better understand, support and actively manage truck load/unload operations and their urban freight transport infrastructure. Project learnings and tools can be used to help make goods delivery firms more efficient by reducing miles traveled and the time it takes to complete deliveries, benefitting businesses and residents who rely on the urban freight system for supplies of goods. And, ultimately, these project learnings and tools can be used to make cities more livable by minimizing wasted travel, which, in turn, contributes to reductions in fuel consumption and emissions. Cities today are challenged to effectively and efficiently manage their infrastructure to absorb the impacts of ever-increasing e-commerce-fueled delivery demand. All delivery trucks need to park somewhere to unload and load. Yet today’s delivery drivers have no visibility on available parking until they arrive at a site, which may be full. That means they can wind up cruising for parking, which wastes time and fuel and contributes to congestion. Once drivers do find parking, the faster they can unload at the spot, the faster they free up space for other drivers, helping others avoid circling for parking. This makes the parking space—and thus the greater load/unload network—more productive. To this end, the research team successfully met the project’s three goals, developing and piloting strategies and technologies to: 1. Reduce parking-seeking behavior in the study area by 20%; 2. Reduce parcel truck dwell time (the time a truck spends in a spot to load/unload) in the study area by 30%; 3. Increase curb space, alley space and private loading bay occupancy rates in the study area. The research team met these goals by creating and piloting on Seattle streets OpenPark, a first-of-its-kind real-time and forecasting curb parking app customized for commercial delivery drivers—giving drivers the “missing link” in their commonly used routing tools that tell them how best to get to delivery locations, but not what parking is available to use when they get there. Installing in-ground sensors on commercial vehicle load zones (CVLZs) and passenger load zones (PLZs) in the 10-block study area in Seattle’s downtown neighbourhood of Belltown let researchers glean real-time curb parking data. The research team also met project goals by piloting three parcel lockers in public and private spaces open to any delivery carrier, creating a consolidated delivery hub that lets drivers complete deliveries faster and spend less time parked. Researchers collected and analysed data to produce the first empirical, robust, statistically significant results as to the impact of the lockers, and app, on on-the-ground operations. In addition to collecting and analyzing sensor and other real-time and historical data, researchers rode along with delivery drivers to confirm real-world routing and parking behavior. Researchers also surveyed building managers on their private loading bay operations to understand how to boost usage.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Near-threshold photoproduction of J/ of a proton with the CLAS12 experiment

The photo-production of vector mesons off the proton has long been established as an important tool to access the gluon content of the nucleon. In particular, the photo-production of J/Psi near the threshold energy has been related to the Gravitational Form Factors of the gluons which provide information about the mass and the force distributions in the nucleon. In this talk, I will present results on the near-threshold photoproduction of J/Psi using data taken in 2018 and 2019 by the CLAS12 detector at Jefferson Lab, with an electron beam impinging on a liquid-hydrogen target. This measurement is expected to provide direct insight on the gluons distribution inside the proton.

Chatagnon, Pierre↗

DOE OSTI2026

Least-cost Optimal Distribution Grid Expansion (LODGE): Utility Pilots

The Least-cost Optimal Distribution Grid Expansion (LODGE) model provides the optimal portfolio of distribution system upgrades—e.g., voltage regulators, feeder reconductoring, transformer upgrades and non-wires alternatives (NWA), such as strategic siting of storage and distributed generation—to interconnect distributed energy resources (DERs) and enable load growth. It can be used to assess grid infrastructure costs and explore policy and regulatory solutions for distribution planning and DER valuation.In 2025, Berkeley Lab conducted three pilot analyses to validate LODGE results with empirical utility data before the model’s first release in 2026. The pilots, done with utilities in Washington, Colorado, and New Mexico, provide examples that illustrate how the model works, what it can do, and the value of the analysis.

Heleno, Miguel↗

DOE OSTI2020

Place polarized neutron reflectivity data in bins of constant wavevector transfer

Code to place polarized neutron reflectivity into bins of constant Qz with regard for Zeeman energy change to the spin-flip channel. The code is written as a Jupyter notebook. Example data are included as separate files (spin_down.txt and spin_up.txt). As a first step, run all cells in the notebook. Opportunities are identified for users to make their own choices for analysis of the data. The code is written to be a stand-alone operation on data collected from a pulse neutron source that have been previously normalized to the wavelength dependence of the incident beam spectrum, background subtracted, etc. The constant Qz binning (this code) is the last step to perform in the analysis (reduction) workflow. This step yields the the reflectivities for the four neutron spin cross-sections. A future intention is to create a version of this code that will be one module of many in the data analysis workflow.

Fitzsimmons, Michael [Oak Ridge National Lab. (ORN↗

DOE OSTI2020

Predicting Biological Cleanliness: An Empirical Bayes Approach for Spacecraft Bioburden Accounting

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Photoproduction of scalar mesons at CLAS

A single gluon, which carries color charge, cannot exist independently outside a hadron. Lattice QCD calculations in pure SU(3), however, predict the existence of glueballs which are bound states of two or more gluons. In the real world, the challenge to identify glueballs experimentally is the fact they mix with meson states. The f0(1500) is one of several candidates for the lightest glueball, with JPC=0++. We investigate the presence of this particle in photoproduction by analyzing the reaction ?p?fJp?K0SK0Sp?2(?+??)p. This reaction was studied using data from the g12 experiment performed using the CLAS detector at Jefferson Lab. A preliminary partial wave analysis, performed on the K0SK0S invariant mass spectrum, will be presented. These results update those presented for this reaction channel at previous conferences.

Weygand, Dennis↗

DOE OSTI2024

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Performance data for an axial-flow turbine with passive adaptive blades

To support the development of simulation tools for passive adaptive turbine rotors, an experimental data set from a laboratory-scale axial-flow turbine with passive adaptive blades is provided. The 0.45-meter diameter turbine was tested in the Alice C. Tyler Flume at the University of Washington. Blade and rotor loads were measured at 1 kHz using six-axis force/torque sensors while deflection and twist at the blade tip were tracked using a high-speed camera. This data submission includes a technical report, the raw and processed experimental data, and a README file explaining the file/folder structure and where to find the processing/plotting scripts used to produce the figures in the technical report.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

Real-time kinematic (RTK) Drone-collected Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

The Southeast Texas Urban Integrated field lab’s Co-design team captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024. Aerial photos taken were through autonomous flight, and models were processed through the DroneDeploy engine. All aerial photos are in .JPG format and contained in zipped files for each area. The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point Cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset will support researchers' decision-making processes under uncertainties.

2D mapping↗

DOE OSTI2022

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗