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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Status of the CERBERUS Evaluation for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

Modeling & Simulation (M&S) tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers continue to improve, we are able to enhance resolution in our calculations. Therefore, the limitations of simulation capability are in the quality of data that is being used, including our ability to quantify the uncertainty and sensitivity of that data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. These experiments, along with differential measurements, can help improve the quality of nuclear data. Concerns regarding the accuracy of Cu nuclear data have been published. The large values and trend of C-E for the Zeus intermediate energy benchmark, being one of the primary examples. Furthermore, very few experiments have been designed to be sensitive to Cu (as shown in Figure 1), so an integral, critical experiment is needed to help resolve these differences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Criticality Accident Alarm System Benchmark Creation

Over the last few decades, the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Working Group has focused on gathering critical and subcritical benchmark experiment data from different facilities around the world for inclusion in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook). The compiled data can be used by criticality safety analysts to help validate their calculation tools and cross-section libraries for a variety of applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1983

Global distributions of cirrus clouds determined from SAGE data

Results are presented from analyses that use SAGE (Stratospheric Aerosol and Gas Experiment) data to determine the spatial extent and frequency of cirrus clouds over much of the earth's surface. The analyses pertain to a period of 15 months extending from February 1979 to April 1980. The results are compared with those from a climatology of ground-based cirrus cloud observations (Hahn et al., 1982). It is found that optically thick cirrus clouds are most often found in the midlatitudes and over the tropics, with distinct minima near the + or - 20 to 30 deg latitude bands. On the other hand, thin cirrus clouds occur much less often than the optically thick cirrus clouds. The comparison of the SAGE cirrus cloud results made zonally with those obtained from ocean-surface-based observations reveals general agreement. Tropospheric observational opportunities for a limb sounding satellite sensor, as evidenced by successful penetrations to 7 km, were found to occur approximately 60 percent of the time in the higher latitudes, falling to a low of 30 percent over the tropics.

Woodbury, G. E.↗
NASA NTRS1989

Scatterometer directional response during rain

Rainfall modification of directional scatterometer response from the sea surface was simulated in wind-wave tank experiments. Data show that for the range of conditions in laboratory experiments, rain enhances radar cross section for all azimuthal angles relative to wind direction. This result broadens previous measurements, which showed that scatterometer response increases with increasing rainfall for radars pointing upwind. But more to the point, the data also show that the directional dynamic-range of scatterometry diminishes rapidly as rainfall rate increases. Thus, while it may be possible to determine wind speed and direction during rain, it will require adequate system sensitivity.

Bliven, L.↗
NASA NTRS1981

A microcomputer based data acquisition system and experiment controller

A data acquisition system is described. The system monitors and records the signal strength of a radio beacon sent to Earth from a geosynchronous satellite. It acquires data from several devices such as a radar, a radiometer, and a rain gauge which monitor the meteorological conditions along the Earth space propagation path. The acquired data are stored in digital format on magnetic tape for analysis at the computer center. A detailed description of the design and operation of the system's various hardware components is given. Schematic diagrams, the theory of operation, and normal operating procedures are presented.

Ganz, M. W.↗
NASA NTRS1980

Data processing system for the Sneg-2MP experiment

The data processing system for scientific experiments on stations of the "Prognoz" type provides for the processing sequence to be broken down into a number of consecutive stages: preliminary processing, primary processing, secondary processing. The tasks of each data processing stage are examined for an experiment designed to study gamma flashes of galactic origin and solar flares lasting from several minutes to seconds in the 20 kev to 1000 kev energy range.

Gavrilova, Y. A.↗
NASA NTRS1990

Estimation of mean rain rate - Application to satellite observations

A method for the estimation of the mean area average rain rate from dependent data is developed and applied to the GARP Atlantic Tropical Experiment data. The method consists of fitting a mixed distribution, containing an atom at zero, by minimum chi-square in combination with certain time-space sampling designs. In modeling the continuous component of the mixed distribution, it is shown that the lognormal distribution provides a very close fit for the nonzero area average rainrates. A comparison with the gamma distribution shows that the lognormal distribution is a better choice as expressed by the minimum chi-square criterion. Some of the time-space sampling designs correspond to satellite sampling. The results indicate that a satellite visiting an area of about 350 x 350 sq km in the tropics approximately every 10 hours over a period can provide a rather close estimate for the mean area average rain rate.

Kedem, Benjamin↗
NASA NTRS2015

Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.

Trujillo, Anna C.↗
DOE OSTI2023

Regridding uncertainty for statistical downscaling of solar radiation

Abstract. Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM outputs from their native grids and at differing spatial resolutions to a common grid in order to be comparable to observed data and (2) bias correcting RCM data, for example via quantile mapping, for future modeling and analysis. The uncertainty associated with (1) is not always considered for downstream operations in (2). This work examines this uncertainty, which is not often made available to the user of a regridded data product. This analysis is applied to RCM solar radiation data from the NA-CORDEX (North American Coordinated Regional Climate Downscaling Experiment) data archive and observed data from the National Solar Radiation Database housed at the National Renewable Energy Lab. A case study of the mentioned methods over California is presented.

14 SOLAR ENERGY↗
DOE OSTI2023

Status of HEU-Pb in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

The Department of Energy invests tens of millions of dollars each year to develop the next generation of nuclear engineering modeling & simulation (M&S) tools. These tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers become more powerful, we are able to enhance resolution in our calculations. This improved resolution is taking us to a point where the limitations of simulation capability are in the quality of data, including our ability to quantify the uncertainty and sensitivity of the data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. Thus, M&S tools need evaluated and quality-assured experimental data for validation purposes. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross-section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. Figure 1 organizes all the benchmark evaluations that have been performed by the isotope of interest, in this case Pb, and the average neutron energy the system. Compared to other isotopes of interest for nuclear applications, there are few benchmark evaluations for Pb systems. The lack of integral measurements to determine errors in Pb cross-section data has caused the latest nuclear cross-section libraries to over/underestimate k eff compared to experimental results. Therefore, this evaluation fills an important knowledge gap in benchmark evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1976

Apollo experiment S-217 IR/radar study of Apollo data

An experiment using Earth based remote sensing radar, infrared eclipse, and color difference data to deduce surface properties not visible in Apollo photography is reported. The Earth based data provided information on the small scale (centimeter sized) blockiness and on the surface chemical composition (titanium and iron contents) of the lunar surface. These deduced surface properties complemented the new Apollo photography, leading to refined geologic interpretations of the lunar surface.

Thompson, T. W.↗
DOE OSTI2021

Vessels Irradiation Experimental Campaign

The purpose of this report is to document the neutron flux field characterization experiments and to provide experiment data to validate radiation transport models. To predict material damage, irradiation experiments expose materials to known radiation fields to correlate the exposure to damage effects. As a part of irradiation experiments, the neutron field in the experiment must be well characterized; this characterization includes effects like room return. Only the neutron component of the 252 Cf sources is considered in theses measurements and calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1973

Station Data Acquisition and Control System.

The Station Data Acquisition and Control System (STADAC), a multicomputer data handling and control system, is expected to be installed in six network stations, the first station to be established at Goddard Space Flight Center. Network control data, in the form of schedules and acquisition pointing data, flow from the Network Control Center to the stations, while station status data flow in the other direction. The system will format spacecraft telemetry data for real-time transmission of control and status data to the project operations control centers and for transmission of experiment data to the data processing facilities. The system will also schedule station equipment resources, perform prepass tests to assure data quality, and automatically set up selected station equipment.

Kiebler, J. W.↗
NASA NTRS1998

The 1985 Biomass Burning Season in South America: Satellite Remote Sensing of Fires, Smoke, and Regional Radiative Energy Budgets

Using satellite imagery, more than five million square kilometers of the forest and cerrado regions over South America are extensively studied to monitor fires and smoke during the 1985 biomass burning season. The results are characterized for four major ecosystems, namely: (1) tropical rain forest, (2) tropical broadleaf seasonal, (3) savannah/grass and seasonal woods (SGW), and (4) mild/warm/hot grass/shrub (MGS). The spatial and temporal distribution of fires are examined from two different methods using the multispectral Advanced Very High Resolution Radiometer Local Area Coverage data. Using collocated measurements from the instantaneous scanner Earth Radiation Budget Experiment data, the direct regional radiative forcing of biomass burning aerosols is computed. The results show that more than 70% of the fires occur in the MGS and SGW ecosystems due to agricultural practices. The smoke generated from biomass burning has negative instantaneous net radiative forcing values for all four major ecosystems within South America. The smoke found directly over the fires has mean net radiative forcing values ranging from -25.6 to -33.9 W m(exp -2). These results confirm that the regional net radiative impact of biomass burning is one of cooling. The spectral and broadband properties for clear-sky and smoke regions are also presented that could be used as input and/or validation for other studies attempting to model the impact of aerosols on the earth-atmosphere system. These results have important applications for future instruments from the Earth Observing System (EOS) program. Specifically, the combination of the Visible Infrared Scanner and Clouds and the Earth's Radiant Energy System (CERES) instruments from the Tropical Rainfall Measuring Mission and the combination of Moderate Resolution Imaging Spectrometer and CERES instruments from the EOS morning crossing mission could provide reliable estimates of the direct radiative forcing of aerosols on a global scale, thereby reducing the uncertainties in current global aerosol radiative forcing values.

Christopher, Sundar A.↗
DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1994

Graphing techniques for materials laboratory using Excel

Engineering technology curricula stress hands on training and laboratory practices in most of the technical courses. Laboratory reports should include analytical as well as graphical evaluation of experimental data. Experience shows that many students neither have the mathematical background nor the expertise for graphing. This paper briefly describes the procedure and data obtained from a number of experiments such as spring rate, stress concentration, endurance limit, and column buckling for a variety of materials. Then with a brief introduction to Microsoft Excel the author explains the techniques used for linear regression and logarithmic graphing.

Kundu, Nikhil K.↗
DOE OSTI2021

Metallic fuel cladding degradation model development and evaluation for BISON

Fuel cladding chemical interaction (FCCI) and coolant cladding chemical interaction (CCCI), both consume stainless-steel cladding in sodium-cooled fast reactors (SFRs), and effectively degrade cladding mechanical performance through thickness reduction. Therefore, FCCI/CCCI and corresponding cladding degradation models are essential for advanced fuel performance codes, such as BISON, to reliably predict cladding behavior in SFRs. Here, we report the development and implementation efforts for BISON's FCCI/CCCI correlations and cladding degradation models based on U.S. legacy metallic fuel data. The models were evaluated using Integral Fast Reactor (IFR) program X447/A experiment data supported by the ongoing integration project enabling coordinated application of BISON and EBR-II fuel irradiation and physics database (FIPD). Furthermore, the implemented models were demonstrated to improve BISON's capabilities of predicting cladding damage and degradation behavior that is more consistent with post-irradiation examination observations. Additionally, some limitations of current BISON modules are identified, which are to be overcome through the BISON-FIPD integration efforts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Monitoring Seasonal Shear Wave Velocity Changes in the Top 6 m at Garner Valley in Southern California With Borehole Data

Abstract Subsurface structures play important roles in seismic ground motion, crustal hydrology, stability of the built environment, and more. Constraining temporal changes of subsurface shear wave velocity ( V S ) can provide useful information to all these topics and the growing field of hydrological monitoring with seismic velocity. Using borehole records at Garner Valley, CA, we estimate seasonal subsurface V S variations from impulse response functions (IRFs) of earthquake data (2005–2018) along with IRFs and cross‐correlation of cross‐hole experiment data (2015–2018). The inferred V S variations are up to ∼25% in the top 6 m and ∼10% at 2–5 m in depth. The V S variations correlate strongly with the water table depth changes, suggesting that the changes are mostly due to fluctuations of pore pressure in the shallow material. The shallow velocity changes alter the near‐surface conditions, can affect seismic hazard estimation, and may be improperly attributed to deeper processes without careful analysis.

58 GEOSCIENCES↗