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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

JPSS-1 VIIRS Version 2 At-Launch Relative Spectral Response Characterization and Performance

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Chris Moeller↗
NASA NTRS1988

User's manual for EZPLOT version 5.5: A FORTRAN program for 2-dimensional graphic display of data

EZPLOT is a computer applications program that converts data resident on a file into a plot displayed on the screen of a graphics terminal. This program generates either time history or x-y plots in response to commands entered interactively from a terminal keyboard. Plot parameters consist of a single independent parameter and from one to eight dependent parameters. Various line patterns, symbol shapes, axis scales, text labels, and data modification techniques are available. This user's manual describes EZPLOT as it is implemented on the Ames Research Center, Dryden Research Facility ELXSI computer using DI-3000 graphics software tools.

Garbinski, Charles↗
NASA NTRS1999

A Variable Resolution Stretched Grid Data Assimilation System for Regional Studies and Applications

The variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM, has been developed and tested. The area/region of interest used in experiments is a rectangle over the U.S. with -60 km horizontal resolution and 70 layers extending from the surface to 0.1 hPa. The forecast error statistics has been reassessed for finer regional resolution. The experiments are performed for winter and summer seasons. The SG-GCM and SG-DAS experiments show that a definite down-scaling takes place over the area of interest. The SG-DAS is capable of reproducing regional mesoscale patterns and diagnostics that are not produced by coarser uniform resolution runs. The SG-DAS fields and diagnostics are used for regional forecasting, new instrument impact studies, and for validation of regional climate simulation experiments.

Fox-Rabinovitz, Michael S.↗
NASA NTRS2007

Numerical Modeling of Propellant Boil-Off in a Cryogenic Storage Tank

A numerical model to predict boil-off of stored propellant in large spherical cryogenic tanks has been developed. Accurate prediction of tank boil-off rates for different thermal insulation systems was the goal of this collaboration effort. The Generalized Fluid System Simulation Program, integrating flow analysis and conjugate heat transfer for solving complex fluid system problems, was used to create the model. Calculation of tank boil-off rate requires simultaneous simulation of heat transfer processes among liquid propellant, vapor ullage space, and tank structure. The reference tank for the boil-off model was the 850,000 gallon liquid hydrogen tank at Launch Complex 39B (LC- 39B) at Kennedy Space Center, which is under study for future infrastructure improvements to support the Constellation program. The methodology employed in the numerical model was validated using a sub-scale model and tank. Experimental test data from a 1/15th scale version of the LC-39B tank using both liquid hydrogen and liquid nitrogen were used to anchor the analytical predictions of the sub-scale model. Favorable correlations between sub-scale model and experimental test data have provided confidence in full-scale tank boil-off predictions. These methods are now being used in the preliminary design for other cases including future launch vehicles

Majumdar, A. K.↗
NASA NTRS2006

Power User Interface

Power User Interface 5.0 (PUI) is a system of middleware, written for expert users in the Earth-science community, PUI enables expedited ordering of data granules on the basis of specific granule-identifying information that the users already know or can assemble. PUI also enables expert users to perform quick searches for orderablegranule information for use in preparing orders. PUI 5.0 is available in two versions (note: PUI 6.0 has command-line mode only): a Web-based application program and a UNIX command-line- mode client program. Both versions include modules that perform data-granule-ordering functions in conjunction with external systems. The Web-based version works with Earth Observing System Clearing House (ECHO) metadata catalog and order-entry services and with an open-source order-service broker server component, called the Mercury Shopping Cart, that is provided separately by Oak Ridge National Laboratory through the Department of Energy. The command-line version works with the ECHO metadata and order-entry process service. Both versions of PUI ultimately use ECHO to process an order to be sent to a data provider. Ordered data are provided through means outside the PUI software system.

Pfister, Robin↗
DOE OSTI2026

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗
DOE OSTI2025

Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database

The Carbon Storage Technical Viability Approach (CS TVA) Data Availability Results Database v1.0 is the output of a data availability assessment workflow that was developed by NETL to create a tool for spatial data availability assessment. This results database is the output of the first version of the workflow performed on the data with the CS TVA Database v2.0.

carbon storage↗
NASA NTRS2002

Evaluation of Improvements to the TRMM Microwave Rain Algorithm

Improvements made to the Version 5 TRMM passive microwave rain retrieval algorithm (2A-12) are evaluated using independent data. Surface rain rate estimates from the Version 5 TRMM TMI (2A-12), PR (2A-25) and TMI/PR Combined (2B-31) algorithms and ground-based radar estimates for selected coincident subset datasets in 1998 over Melbourne and Kwajalein show varying degrees of agreement. The surface rain rates are then classified into convective and stratiform rain types over ocean, land, and coastal areas for more detailed comparisons to the ground radar measurements. These comparisons lead to a better understanding of the relative performances of the current TRMM rain algorithms. For example, at Melbourne more than 80% of the radar-derived rainfall is classified as convective rain. Convective rain from the TRMM rain algorithms is less than that from ground radar measurements, while TRMM stratiform rain is much greater. Rain area coverage from 2A-12 is also in reasonable agreement with ground radar measurements, with about 25% more over ocean and 25% less over land and coastal areas. Retrieved rain rates from the improved (Version 6) 2A-12 algorithm will be compared to 2A-25, 2B-31, and ground-based radar measurements to evaluate the impact of improvements to 2A-12 in Version 6. An important improvement to the Version 6 2A-12 algorithm is the retrieval of Q1/Q2 (latent heating/drying) profiles in addition to the surface rain rate and hydrometeor profiles. In order to ascertain the credibility of the new products, retrieved Q1/Q2 profiles are compared to independent ground-based estimates. Analyses of dual-Doppler radar data in conjunction with coincident rawinsonde data yield estimates of the vertical distributions of diabatic heating/drying at high horizontal resolution for selected cases over the Kwajalein and LBA field sites. The estimated vertical heating/drying structures appear to be reasonable. Comparisons of Q1/Q2 profiles from Version 6 2A-12 and the ground-based estimates are in progress. Retrieved Q1/Q2 structures will also be compared to MM5 hurricane simulations for selected cases. The results of these intercomparisons will be presented at the conference.

Yang, Song↗
NASA NTRS1985

Measurement of SIFT operating system overhead

The overhead of the software implemented fault tolerance (SIFT) operating system was measured. Several versions of the operating system evolved. Each version represents different strategies employed to improve the measured performance. Three of these versions are analyzed. The internal data structures of the operating systems are discussed. The overhead of the SIFT operating system was found to be of two types: vote overhead and executive task overhead. Both types of overhead were found to be significant in all versions of the system. Improvements substantially reduced this overhead; even with these improvements, the operating system consumed well over 50% of the available processing time.

Palumbo, D. L.↗
NASA NTRS2001

Global Surface Solar Energy Anomalies Including El Nino and La Nina Years

This paper synthesizes past events in an attempt to define the general magnitude, duration, and location of large surface solar anomalies over the globe. Surface solar energy values are mostly a function of solar zenith angle, cloud conditions, column atmospheric water vapor, aerosols, and surface albedo. For this study, solar and meteorological parameters for the 10-yr period July 1983 through June 1993 are used. These data were generated as part of the Release 3 Surface meteorology and Solar Energy (SSE) activity under the NASA Earth Science Enterprise (ESE) effort. Release 3 SSE uses upgraded input data and methods relative to previous releases. Cloud conditions are based on recent NASA Version-D International Satellite Cloud Climatology Project (ISCCP) global satellite radiation and cloud data. Meteorological inputs are from Version-I Goddard Earth Observing System (GEOS) reanalysis data that uses both weather station and satellite information. Aerosol transmission for different regions and seasons are for an 'average' year based on historic solar energy data from over 1000 ground sites courtesy of Natural Resources Canada (NRCan). These data are input to a new Langley Parameterized Shortwave Algorithm (LPSA) that calculates surface albedo and surface solar energy. That algorithm is an upgraded version of the 'Staylor' algorithm. Calculations are performed for a 280X280 km equal-area grid system over the globe based on 3-hourly input data. A bi-linear interpolation process is used to estimate data output values on a 1 X 1 degree grid system over the globe. Maximum anomalies are examined relative to El Nino and La Nina events in the tropical Pacific Ocean. Maximum year-to-year anomalies over the globe are provided for a 10-year period. The data may assist in the design of systems with increased reliability. It may also allow for better planning for emergency assistance during some atypical events.

Whitlock, C. H.↗
NASA NTRS2003

Total Ozone from the Ozone Monitoring System (OMI) using TOMS and DOAS Methods

The Ozone Monitoring Instrument (OMI) is the Dutch-Finnish contribution to NASA's EOS-Aura satellite scheduled for launch in January 2004. OMI is an imaging spectrometer that will measure the back-scattered Solar radiance in the wavelength range of 270 to 500 nm. The instrument provides near global coverage in one day with a spatial resolution of 13x24 square kilometers. OMI is a new instrument, with a heritage from TOMS, SBW, GOME, GOMOS and SCIAMACHY. OMI'S unique capabilities for measuring important trace gases and aerosols with a small footprint and daily global coverage, in conjunction with the other Aura instruments, will make a major contribution to our understanding of stratospheric and tropospheric chemistry and climate change. OMI will provide data continuity with the 23-year ozone record of TOMS. There are three ozone products planned for OMI: total column ozone, ozone profile and tropospheric column ozone. We are developing two different algorithms for total column ozone: one similar to the algorithm currently being used to process the TOMS data, and the other an improved version of the differential optical absorption spectroscopy (DOAS) method, which has been applied to GOME and SCIAMACHY data. The main reasons for starting with two algorithms for total ozone have to do with heritage and past experience; our long-term goal is to combine the two to develop a more accurate and reliable total ozone product for OMI. We will compare the performance of these two algorithms by applying both of them to the GOME data. We will examine where and how the results differ, and use the extensive TOMS-Dobson comparison studies to assess the performance of the DOAS algorithm.

Veefkind, J. P.↗
DOE OSTI2024

CO2-Locate: A Dynamic Database and Tool for Accessing National Oil and Gas Well Data to Inform Carbon Storage Projects

The CO2-Locate Database is a growing compilation of publicly available wellbore resources that have been merged based on common attributes across data sources with an attribute schema developed to be consistent across disparate resources, reduce data gaps, and eliminate record redundancy. The first version of CO2-Locate has been published to Energy Data eXchange (EDX) and includes the integrated public wells dataset as well as additional geospatial summary layers of key wellbore characteristics to protect proprietary resources. Additionally, the CO2-Locate database has been deployed into a web application, enabling easy access, data filtering capabilities, and visualization of U.S. wellbore infrastructure by stakeholders to inform injection site selection and risk assessments.

Dyer, Alec S. [NETL Site Support Contractor, Natio↗
NASA NTRS2004

Accuracy and Precision in the Southern Hemisphere Additional Ozonesondes (SHADOZ) Dataset in Light of the JOSIE-2000 Results

Since 1998 the Southern Hemisphere ADditional OZonesondes (SHADOZ) project has provided over 2000 ozone profiles over eleven southern hemisphere tropical and subtropical stations. Balloon-borne electrochemical concentration cell (ECC) ozonesondes are used to measure ozone. The data are archived at: &ttp://croc.gsfc.nasa.gov/shadoz>. In analysis of ozonesonde imprecision within the SHADOZ dataset, Thompson et al. [JGR, 108,8238,20031 we pointed out that variations in ozonesonde technique (sensor solution strength, instrument manufacturer, data processing) could lead to station-to-station biases within the SHADOZ dataset. Imprecisions and accuracy in the SHADOZ dataset are examined in light of new data. First, SHADOZ total ozone column amounts are compared to version 8 TOMS (2004 release). As for TOMS version 7, satellite total ozone is usually higher than the integrated column amount from the sounding. Discrepancies between the sonde and satellite datasets decline two percentage points on average, compared to version 7 TOMS offsets. Second, the SHADOZ station data are compared to results of chamber simulations (JOSE-2000, Juelich Ozonesonde Intercomparison Experiment) in which the various SHADOZ techniques were evaluated. The range of JOSE column deviations from a standard instrument (-10%) in the chamber resembles that of the SHADOZ station data. It appears that some systematic variations in the SHADOZ ozone record are accounted for by differences in solution strength, data processing and instrument type (manufacturer).

Witte, Jacquelyn C.↗
NASA NTRS1996

Parallel NPARC: Implementation and Performance

Version 3 of the NPARC Navier-Stokes code includes support for large-grain (block level) parallelism using explicit message passing between a heterogeneous collection of computers. This capability has the potential for significant performance gains, depending upon the block data distribution. The parallel implementation uses a master/worker arrangement of processes. The master process assigns blocks to workers, controls worker actions, and provides remote file access for the workers. The processes communicate via explicit message passing using an interface library which provides portability to a number of message passing libraries, such as PVM (Parallel Virtual Machine). A Bourne shell script is used to simplify the task of selecting hosts, starting processes, retrieving remote files, and terminating a computation. This script also provides a simple form of fault tolerance. An analysis of the computational performance of NPARC is presented, using data sets from an F/A-18 inlet study and a Rocket Based Combined Cycle Engine analysis. Parallel speedup and overall computational efficiency were obtained for various NPARC run parameters on a cluster of IBM RS6000 workstations. The data show that although NPARC performance compares favorably with the estimated potential parallelism, typical data sets used with previous versions of NPARC will often need to be reblocked for optimum parallel performance. In one of the cases studied, reblocking increased peak parallel speedup from 3.2 to 11.8.

Townsend, S. E.↗
NASA NTRS1999

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Keppenne, C. L.↗
DOE OSTI2022

Six Machine-Learning Methods for Predicting Hospital-Stay Duration for Patients with Sepsis: A Comparative Study

Sepsis is a life-threatening medical condition that, if not treated promptly, can result in tissue damage, organ failure, and death. According to the Centers for Disease Control, about 270,000 individuals die of sepsis in the US each year. Further, sepsis expenditures accounted for 13% of total US hospital costs in 2013, totaling more than $24 billion. Our project objectives were to determine if Machine Learning algorithms could reliably predict hospital stay duration for patients with sepsis. The data set we used has been de-identified and is freely available through the BupaR package. The data includes 1050 cases, 15214 events, and 16 types of actions related to sepsis patient care. First, we used process mining to determine how long each patient was in the hospital. Using BupaR’s functions, we created several process model graphs. These process models depict the movement of patients at a hospital and provide duration data for each patent case. Second, we identified outlier data and created two dataset versions: one with and one without outliers. We then applied the following analysis methods: Linear Regression, Random Forest, K-Nearest Neighbors, Neural Networks, XGBoost, and lightGBM. We compared the model validations for the six machine learning models using the same data-splitting method. We found that the XGBoost model had the best prediction accuracy of 73.9 percent for cases with outliers, and 79 percent for cases without outliers. We also found that the lightGBM model had the lowest mean absolute error between prediction and actual duration in days with 3.66 days for the case with outliers, and 2.4 days for the case without outliers. These two models outperformed the other four models. This work will be enhanced in the future by exploring new prediction algorithms and comparing them with the results of this study.

Chen, Lingtao↗
NASA NTRS2014

On the Sizes of the North Atlantic Basin Tropical Cyclones Based on 34- and 64-kt Wind Radii Data, 2004-2013

At end of the 2012 hurricane season the National Hurricane Center retired the original HURDAT dataset and replaced it with the newer version HURDAT2, which reformatted the original data and included additional information, in particular, estimates of the 34-, 50, and 64-kt wind radii for the interval 2004-2013. During the brief 10-year interval, some 164 tropical cyclones are noted to have formed in the North Atlantic basin, with 77 becoming hurricanes. Hurricane Sandy (2012) stands out as being the largest individual storm that occurred in the North Atlantic basin during the 2004 -2013 timeframe, both in terms of its 34- and 64-kt wind radii and wind areas, having maximum 34- and 64-kt wind radii, maximum wind areas, and average wind areas each more than 2 standard deviations larger than the corresponding means. In terms of the largest yearly total 34-kt wind area (i.e., the sum of all individual storm 34-kt wind areas during the year), the year 2010 stands out as being the largest (about 423 × 10(exp 6) nmi(exp 2)), compared to the mean of about 174 × 10(exp 6) nmi(exp 2)), surpassing the year 2005 (353 x 10(exp 6) nmi(exp 2)) that had the largest number of individual storms (28). However, in terms of the largest yearly total 64-kt wind area, the year 2005 was the largest (about 9 × 10(exp 6) nmi(exp 2)), compared to the mean of about 3 × 106 nmi(exp 2)). Interesting is that the ratio of total 64-kt wind area to total 34-kt wind area has decreased over time, from 0.034 in 2004 to 0.008 in 2013.

Wilson, Robert M.↗
DOE OSTI2025

MCNP® Code Version 6.3.1 Release Notes

The Monte Carlo N-Particle® (MCNP® ) code is a general-purpose, continuous-energy, generalized-geometry, time-dependent, radiation transport code developed by the MCNP development team. MCNP calculations provide predictive capabilities that can replace expensive or impossible-to-perform experiments. Specific application problems include simulations of experimental diagnostics, intrinsic radiation, radiation detection and measurement, criticality safety, nuclear threat reduction and response, radiation health protection, nuclear weapons effects, and nuclear forensics. This MCNP code, version 6.3.1, follows the MCNP6.3.0 version. Since the release of MCNP6.3.0, a variety of bug fixes and code enhancements have been completed for MCNP6.3.1. A few new features have also been added to this release to support both ongoing research and the release of the latest ENDF/B-VIII.1 nuclear data library. The MCNP code, version 6.3.1, theory and user input information is documented in MCNP® Code Version 6.3.1 Theory & User Manual, the build guidance for various platforms is documented in MCNP® Code Version 6.3.1 Build Guide, and the verification and validation testing for various application benchmark test suites is documented in MCNP® Code Version 6.3.1 Verification & Validation Testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗