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At least 721 records · Page 40

All sources NASA NTRS DOE OSTI

DOE OSTI2017

Quantification of Arctic Soil and Permafrost Properties Using Ground-Penetrating Radar and Electrical Resistivity Tomography Datasets

Improving understanding of Arctic ecosystem climate feedback and parameterization of models that simulate freeze-Thaw dynamics require advances in quantifying soil and snow properties. Due to the significant spatiotemporal variability of soil properties and the limited information provided by point-scale measurements (e.g., cores), geophysical methods hold potential for improving soil and permafrost characterization. In this study, we evaluate the use of a ground-penetrating radar (GPR) to estimate thaw layer thickness, snow depth, and ice-wedge characteristics in an ice-wedge-dominated tundra region near Barrow, AK, USA. To this end, we analyze GPR and point-scale measurements collected along several parallel transects at the end of the growing season and the end of frozen season. In addition, we compare the structural information extracted from the GPR data with electrical resistivity tomography (ERT) information about ice-wedge characteristics. Our study generally highlights the value of GPR data collected in the frozen season, when conditions lead to the improved GPR signal-To-noise ratio, facilitate data acquisition, and reduce acquisition-related ecosystem disturbance relative to growing season. We document for the first time that GPR data collected during the frozen season can provide reliable estimates of active layer thickness and geometry of ice wedges. We find that the ice-wedge geometry extracted from GPR data collected during the frozen season is consistent with ERT data, and that GPR data can be used to constrain the ERT inversion. Consistent with recent studies, we also find that GPR data collected during the frozen season can provide good estimates of snow thickness, and that GPR data collected during the growing season can provide reliable estimate thaw depth. As a result, our quantification of the value of the GPR and ERT data collected during growing and frozen seasons paves the way for coupled inversion of the datasets to improve understanding of permafrost variability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2019

14 SOLAR ENERGY↗

DOE OSTI2021

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2020

With continued deployment of solar across the United States, assessing the interactions of solar with the power system is an increasingly important complement to studies tracking the cost and performance of solar plants. This project focuses on the historical contribution to reliability, trends in market value, and impacts on the bulk power system of solar deployed in the U.S. through the end of 2020. The scope of this analysis includes the seven organized U.S. wholesale power markets and is based on historical hourly solar generation profiles for each individual plant larger than 1 MW or county-level aggregate profiles for smaller solar. In addition, we present a limited set of results for ten utilities that are outside of the independent system operator (ISO)/regional transmission organization (RTO) markets.

14 SOLAR ENERGY↗

NASA NTRS1984

Low altitude wind shear statistics derived from measured and FAA proposed standard wind profiles

Wind shear statistics were calculated for a simulated data set using wind profiles proposed as a standard and compared to statistics derived from measured wind profile data. Wind shear values were grouped in altitude bands of 100 ft between 100 and 1400 ft, and in wind shear increments of 0.025 kt/ft between + or - 0.600 kt/ft for the simulated data set and between + or - 0.200 kt/ft for the measured set. No values existed outside the + or - 0.200 kt/ft boundaries for the measured data. Frequency distributions, means, and standard deviations were derived for each altitude band for both data sets, and compared. Also, frequency distributions were derived for the total sample for both data sets and compared. Frequency of occurrence of a given wind shear was about the same for both data sets for wind shears, but less than + or 0.10 kt/ft, but the simulated data set had larger values outside these boundaries. Neglecting the vertical wind component did not significantly affect the statistics for these data sets. The frequency of occurrence of wind shears for the flight measured data was essentially the same for each altitude band and the total sample, but the simulated data distributions were different for each altitude band. The larger wind shears for the flight measured data were found to have short durations.

Dunham, R. E., Jr.↗

DOE OSTI2012

Transarterial Hepatic Yttrium-90 Radioembolization in Patients with Unresectable Intrahepatic Cholangiocarcinoma: Factors Associated with Prolonged Survival

Introduction: In unresectable intrahepatic cholangiocarcinoma (ICC), systemic chemotherapy often is viewed as the only option, although efficacy is limited. Radioembolization (RE) using yttrium-90 ({sup 90}Y) microspheres is an accepted therapy for patients with hepatocellular-carcinoma or metastatic liver tumors. However, there are limited data on the value of RE in patients with ICC and few data on factors influencing prognosis. The purpose of our retrospective analysis was to establish which factors influenced time-to-progression (TTP) and overall survival (OS). Methods: Patients with unresectable ICC were treated with {sup 90}Y resin-microspheres and assessed at 3-monthly intervals. Radiologic response was evaluated by using Response Criteria in Solid Tumors (RECIST). Baseline characteristics, biochemical/clinical toxicities, and response were examined for impact on TTP and OS. Results: Thirty-four treatments were administered to 33 patients without major complications. By RECIST, 12 patients had a partial response, 17 had stable disease, and 5 had progressive disease after 3 months. The median OS was 22 months posttreatment and 43.7 months postdiagnosis. Median TTP was 9.8 months. Survival and TTP were significantly prolonged in patients with ECOG 0 (vs. ECOG 1 or 2; median OS: 29.4, 10, and 5.1 months; TTP: 17.5, 6.9, and 2.4 months), tumor burden {<=}25% (OS: 26.7 vs. 6 months; TTP: 17.5 vs. 2.3 months), or tumor response (PR or SD vs. PD; OS: 35.5, 17.7 vs. 5.7 months; TTP: 31.9, 9.8 vs. 2.5 months), respectively (P < 0.001). Conclusions: Radioembolization is an effective and safe option for patients with unresectable ICC. Predictors for prolonged survival are performance status, tumor burden, and RECIST response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Utah FORGE: Neubrex Well 16B(78)-32 Fiber Optics Reports - Stimulation and Circulation, 2024

This zip file contains reports discussing the use of fiber optics during well 16B(78)-32 stimulation and circulation tests in the summer of 2024. The reports cover the collection of strain rate and temperature change data during these well events. Theory, methods, and initial data visualizations are included in the reports, highlighting the value of these data types.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Supporting Special Values in ZFP

This white paper outlines potential approaches to supporting special values in the ZFP numerical compressor without breaking backwards compatibility. Other than infinities and NaNs, special values are often used to indicate the absence of data, where no value is defined, for example by designating finite but extreme “fill values” as special. Such fill values are commonly used in earth system science, among other applications, but if left as is during compression lead to artifacts and loss of precision in nearby true values. Multiple candidate solutions that would allow ZFP to recognize special values are here proposed. Until such support is available, we also sketch available workarounds.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO 2 experiment

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov ) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO 2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO 2 and CH 4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. In order to successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following; 1. data acquisition and control system – set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system – set of hardware and software to deliver data to a central depository for storage and further processing; and 3. data management plan – set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. Finally, the approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1971

Behavior of nozzles and acoustic liners in three dimensional acoustic fields

Theoretical values of the admittances of various nozzles were computed and compared with the corresponding experimental values. The existing data reduction scheme was corrected and all available experimental data has been rechecked and corrected whenever necessary; the updated experimental admittance values are presented. An analysis associated with the frequency sensitivity of experimental admittance values was initiated and the analog-to-digital Data Reduction Program which has become operational is discussed. Fourteen nozzle tests were conducted during this report period.

Zinn, B. T.↗

NASA NTRS1982

Availability of IMP-7 and IMP-8 data for the IMS period

The relation of IMP-7 and IMP-8 data to the International Magnetospheric Study is discussed. Relevant spacecraft and experiment characteristics, and the nature and accessibility of data from each experiment, are identified. Finally the potential value of IMP data in IMS studies is illustrated with a few citations from the IMP Bibliography and with figures from a recent multiple-data-set magnetotail plasma sheet study.

King, J. H.↗

NASA NTRS2016

Scientific and Technical Assistance for the Deployment of a Flexible Airborne Spectrometer System During C-MAPExp and COMEX: COMEX Version - 1.9T

The COMEX (CO2 and MEthane eXperiment) campaign supports the mission definition of CarbonSat and HyspIRI (Hyperspectral Infrared Imager) by providing representative airborne remote sensing data ‐ MAMAP (Methane Airborne MAPper) for CarbonSat; the Airborne Visual InfraRed Imaging Spectrometer (Classic & Next Generation) AVIRIS‐C/AVIRIS‐NG for HyspIRI ‐ as well as ground-based and airborne in‐situ data. The objectives of the COMEX campaign activities are (see Campaign Implementation Plan (RD‐4)): 1. Investigate spatial/spectral resolution trade‐offs for CH4 anomaly detection and flux inversion by comparison of MAMAP‐derived emission estimates with AVIRIS/AVIRIS‐NG derived data. 2. Evaluate sun‐glint observation geometry on CH4 retrievals for marine sources. 3. Characterize the effect of Surface Spectral Reflectance (SSR) heterogeneity on trace gas retrievals of CO2 and CH4 for medium and low‐resolution spectrometry. 4. Identify benefits from joint SWIR/TIR (ShortWave InfraRed/Thermal InfraRed ) data for trace gas detection and retrieval by comparison of MAMAP and AVIRIS/AVIRIS‐NG NIR/SWIR data with MAKO (Aerospace Corp.)TIR data. The ability to derive emission source strength for a range of strong emitting targets by remote sensing will be evaluated from combined AVIRIS‐NG and MAMAP data, adding significant value to the HyspIRI campaign AVIRIS‐NG dataset. The data will be used to quantify anomalies in atmospheric CO2 and CH4 from strong local greenhouse gas sources e.g. localized industrial complexes, landfills, etc. and to derive CO2 and CH4 emissions estimates from atmospheric gradient measurements. The original campaign concept was developed by University of Bremen and BRI. The COMEX campaign is funded bilaterally by NASA and ESA (European Space Agency). Whereas NASA funds the US part of the project via a contract with Dr. Ira Leifer, BRI (Bubbleology Research International), the contribution of MAMAP to the COMEX campaign is funded by ESA within the COMEX‐E project and NASA with respect to a 50 percent contribution to the flight-related costs of flying MAMAP on a US aircraft. The Data Acquisition Report (RD‐9) describes the instrumentation used, the measurements made by the team during the COMEX campaign in May/June 2014 and August/September 2014 in California, and an initial assessment of the data quality.

Point Sources↗

NASA NTRS2021

The First Global 883 GHz Cloud Ice Survey: IceCube Level 1 Data Calibration, Processing and Analysis

Sub-millimeter (sub-mm, 200 - 1000 GHz) wavelengths contribute a unique capability to fill-in the sensitivity gap between operational visible/infrared (VIS/IR) and microwave (MW) remote sensing for atmosphere cloud ice and snow. Being able of penetrating cloud to measure cloud ice mass and microphysical properties in the middle to upper troposphere, this is a critical spectrum range for us to understand the connection between cloud ice and precipitation processes.5As the first space-borne 883 GHz radiometer, IceCube mission was NASA’s latest effort in spaceflight demonstration of a commercial sub-mm radiometer technology. Successfully launched from the International Space Station, IceCube is essentially a free-running radiometer and collected valuable 15-month measurements of atmosphere and cloud ice. This paper describes the detailed procedures for Level 1 data calibration, processing and validation. The scientific quality and values of IceCube data are then discussed, including radiative transfer model validation and evaluation, as well as the unique spatial distribution10and diurnal cycle of cloud ice that are revealed for the first time on a quasi-global scale at this frequency.

IceCube↗

NASA NTRS2021

The First Global 883 GHz Cloud Ice Survey: IceCube Level 1 Data Calibration, Processing and Analysis

Jie Gong↗

DOE OSTI2011

Summary

An effective risk assessment system is needed to address the threat posed by an active or passive insider who, acting alone or in collusion, could attempt diversion or theft of nuclear material. The material control and accountability (MC&A) system effectiveness tool (MSET) is a self-assessment or inspection tool utilizing probabilistic risk assessment (PRA) methodology to calculate the system effectiveness of a nuclear facility's material protection, control, and accountability (MPC&A) system. The MSET process is divided into four distinct and separate parts: (1) Completion of the questionnaire that assembles information about the operations of every aspect of the MPC&A system; (2) Conversion of questionnaire data into numeric values associated with risk; (3) Analysis of the numeric data utilizing the MPC&A fault tree and the SAPHIRE computer software; and (4) Self-assessment using the MSET reports to perform the effectiveness evaluation of the facility's MPC&A system. The process should lead to confirmation that mitigating features of the system effectively minimize the threat, or it could lead to the conclusion that system improvements or upgrades are necessary to achieve acceptable protection against the threat. If the need for system improvements or upgrades is indicated when the system is analyzed, MSET provides the capability to evaluate potential or actual system improvements or upgrades. A facility's MC&A system can be evaluated at a point in time. The system can be reevaluated after upgrades are implemented or after other system changes occur. The total system or specific subareas within the system can be evaluated. Areas of potential system improvement can be assessed to determine where the most beneficial and cost-effective improvements should be made. Analyses of risk importance factors show that sustainability is essential for optimal performance and reveals where performance degradation has the greatest impact on total system risk. The risk importance factors show the amount of risk reduction achievable with potential upgrades and the amount of risk reduction achieved after upgrades are completed. Applying the risk assessment tool gives support to budget prioritization by showing where budget support levels must be sustained for MC&A functions most important to risk. Results of the risk assessment are also useful in supporting funding justifications for system improvements that significantly reduce system risk. The functional model, the system risk assessment tool, and the facility evaluation questionnaire are valuable educational tools for MPC&A personnel. These educational tools provide a framework for ongoing dialogue between organizations regarding the design, development, implementation, operation, assessment, and sustainability of MPC&A systems. An organization considering the use of MSET as an analytical tool for evaluating the effectiveness of its MPC&A system will benefit from conducting a complete MSET exercise at an existing nuclear facility.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1992

Program For Logarithmic Interpolation Of Test Data

DATASPACE program establishes logarithmically increasing time interval in relaxation data. First takes logarithm of abscissa values, then uses cubic-spline interpolation routine to create evenly spaced array from log values. As result of interpolation, data increasingly spaced. Experimental data curve retained, and interpolated points reflect desired spacing. Applicable to any situation with need for increasingly spaced abscissa values in set of data. Written in FORTRAN 77.

Ledbetter, Frank E., II↗

DOE OSTI2019

KCMP Minnesota Tall Tower Ammonia Observations and Emission Estimates Dataset 2017-2018

This data set contains NH3 mixing ratios, net ecosystem NH3 exchange, and supporting information measured at a tall tower (KCMP, 244 meter) site near St. Paul, Minnesota, USA. The data include NH3 and H2O mixing ratios measured at the 100 meter level, as well as NH3 mixing ratio measured at the 56 meter level. Wind data was measured using a sonic anemometer at the 185 meter level. Also included in this data set are values of wet N and NH3 deposition from 2016 - 2018. This data was collected to improve understanding of the ammonia and reactive nitrogen budget for the region.Ammonia mixing ratios were filtered for periods when the NH3 analyzer measured anomalous (i.e. 10 mmol mol-1) water vapor mixing ratios based on comparison with the IRGA (LI7000). Further, we filtered out NH3 observations obtained during strongly condensing conditions. These periods were identified when the water vapor mixing ratio differences between the 100 m and 56 m levels were more negative than -0.5 mmol mol-1 (i.e. when the water vapor gradient was strong and directed toward the land surface). Finally, we filtered out NH3 fluxes when the atmosphere was strongly stable (i.e. when (z-d)/L exceeded a value of +4.5) and subject to decoupling from the surface fluxes. Approximately 35.1% of the hourly flux data were either missing due to instrument failure or filtered according to the above quality control procedures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Automatic Detection of Clear-Sky Periods From Irradiance Data

Recent degradation studies have illustrated the importance of considering cloud cover when calculating degradation rates, finding more reliable values when the data are restricted to clear sky periods. Several automated methods of determining clear sky periods have been previously developed, but parameterizing and testing the models has been difficult. Here, we use clear sky classifications determined from satellite data to develop an algorithm that determines clear sky periods using only measured irradiance values and modeled clear sky irradiance as inputs. This approach is tested on global horizontal irradiance (GHI) data from ground collectors at six sites across the United States and compared against independent satellite-based classifications. First, 30 separate models were optimized on each individual site at GHI data intervals of 1, 5, 10, 15, and 30 min (sampled on the first minute of the interval). The models had an average F 0.5 score of 0.949 ± 0.035 on a holdout test set. Next, optimizations were performed by aggregating data from different locations at the same interval, yielding one model per data interval. This paper yielded an average F 0.5 of 0.946 ± 0.037. A final, 'universal' optimization that was trained on data from all sites at all intervals provided an F 0.5 score of 0.943 ± 0.040. The optimizations all provide improvements on a prior, unoptimized clear sky detection algorithm that produces F 0.5 scores that average to 0.903 ± 0.067. Our paper indicates that a single algorithm can accurately classify clear sky periods across locations and data sampling intervals.

14 SOLAR ENERGY↗