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NASA NTRS1983

The use of linear feature detection to investigate thematic mapper data performance and processing

The geometric and radiometric characteristics of thematic mapper data through analysis of linear features in the data are investigated. The particular aspects considered are: (1) thematic mapper ground IFOV; (2) radiometric contrast between linear features and background; (3) precision of system geometric correction; (4) band-to-band registration; and (5) potential utility of TM data for linear feature detection especially as compared to MSS data. It is shown that TM data may be used to estimate TM pixel size and to illustrate band-band mis-registration. Further, the geometry and radiometry of the data are sufficiently precise to allow accurate estimation of the widths of linear features. In optimum conditions features one quarter of a pixel in width may be accurately measured. These results have considerable potential for applications for hydrological and topographic mapping.

Gurney, C. M.↗

DOE OSTI2017

Streamlining and Transparently Automating Complex Waste Determinations at Los Alamos National Laboratory - 17286

Environmental programs at Los Alamos National Laboratory (LANL) generate a large amount of sampling activities that can result in waste that needs to be characterized and properly disposed. Since 2011, sampling results are managed in the cloud-based Environmental Information Management (EIM) database, which contains over 16 million current and historical data records. In many cases, the database's analytical records are used to characterize and dispose waste from environmental operations. Three factors contribute to streamlining of the waste disposition operations: (1) if possible, use of the existing analytical data for waste characterization to avoid additional laboratory analysis; (2) reduction in time spent on data evaluation for various waste acceptance criteria; and (3) choice of the proper and least expensive disposal alternative. Use of the existing analytical data, when allowed by law, creates some paradoxical problems: when chemical analysis is requested with the purpose of characterizing waste, it creates only 100 to 400 analytical records. However, use of exiting analytical data at LANL may lead to evaluation of tens of thousands of analytical records, with many records for each single analyte. This occurs because data were collected for environmental characterization and not waste characterization. To streamline data analysis for waste disposition using existing data, LANL has created a Waste Data Summary (WDS) module in the site's EIM database. Recognizing that waste determination is performed by groups outside the environmental program at LANL, the WDS allows for logically guided data selection for a specific waste determination (solids, liquids, radiological, etc.) and reduces potentially thousands of rows of data into simple formatted data reports that are easy to comprehend and process. This allows the waste evaluators to review data using multiple approaches to make their own determination on the most appropriate disposal method. There are four basic principles of WDS operation: (1) The highest detected analytical result is evaluated for the selected samples (or the lowest undetected result if there are no detected results); (2) All approved disposal pathways are evaluated; (3) Any failures of the Waste Acceptance Criteria are visibly highlighted to focus the attention of the evaluator; and (4) The decision of the disposal path is left to the trained waste evaluator (WDS does not choose or suggest any disposal paths). The summary results are presented as the set of short data reports. These reports can be divided into two groups: general comparison reports and disposal pathway specific forms. The general comparison forms show all Resource Conservation and Recovery Act (RCRA) analytes with pass/fail evaluation and with preference for toxicity characteristic leaching procedure (TCLP) results (or 20x rule) for solid samples, the potential RCRA hazard codes assignment for detected analytes, and all rad results. The detected chemical and radioactivity results are compared to the background values and to Soil Screening and Soil Action limits (SSL/SAL limits). Disposal pathway specific forms follow Waste Acceptance Criteria requirements for all disposal pathways available at LANL. The programming of the WDS tries to maximize existing data by analyte substitutions (like using gross alpha for necessary alpha emitting isotopes) or by making calculations when analytical results do not agree with legal requirements (like total chlordane in the RCRA regulations, which is most often analyzed and reported as individual isomers). All forms may be annotated by the waste evaluator to provide additional information to support decision making. Upon final decision of a disposal path, the complete dataset used in the evaluation and the WDS forms with annotations is 'frozen' as an un-editable PDF export to document the data used in the waste disposal determination. The streamlined process results in less work for waste evaluators and reduces overall labor and analytical costs. By comparison, a full review of a 10,000 record parent dataset may take a waste evaluator over a week to review, whereas with the WDS module, the task can be accomplished in less than one hour with clear, reproducible results. These results can be reviewed and checked at any time by quality assurance personnel, thus ensuring transparency in the decision making process. LANL believes this approach has broad applicability to other sites where waste determination is based on review of existing data collected for more generalized environmental purposes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Partitioning evapotranspiration based on the concept of underlying water use efficiency

Evapotranspiration (ET) is dominated by transpiration (T) in the terrestrial water cycle. However, continuous measurement of transpiration is still difficult, and the effect of vegetation on ET partitioning is unclear. The concept of underlying water use efficiency (uWUE) was used to develop a new method for ET partitioning by assuming that the maximum, or the potential uWUE is related to T while the averaged or apparent uWUE is related to ET. T/ET was thus estimated as the ratio of the apparent over the potential uWUE using half-hourly flux data from 17 AmeriFlux sites. The estimated potential uWUE was shown to be essentially constant for 14 of the 17 sites, and was broadly consistent with the uWUE evaluated at the leaf scale. The annual T/ET was the highest for croplands, i.e., 0.69 for corn and 0.62 for soybean, followed by grasslands (0.60) and evergreen needle leaf forests (0.56), and was the lowest for deciduous broadleaf forests (0.52). The enhanced vegetation index (EVI) was shown to be significantly correlated with T/ET and could explain about 75% of the variation in T/ET among the 71 site-years. The coefficients of determination between EVI and T/ET were 0.84 and 0.82 for corn and soybean, respectively, and 0.77 for deciduous broadleaf forests and grasslands, but only 0.37 for evergreen needle leaf forests. This ET partitioning method is sound in principle and simple to apply in practice, and would enhance the value and role of global FLUXNET in estimating T/ET variations and monitoring ecosystem dynamics.

42 ENGINEERING↗

DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Classifying and analyzing small-angle scattering data using weighted k nearest neighbors machine learning techniques

A consistent challenge for both new and expert practitioners of small-angle scattering (SAS) lies in determining how to analyze the data, given the limited information content of said data and the large number of models that can be employed. Machine learning (ML) methods are powerful tools for classifying data that have found diverse applications in many fields of science. Here, ML methods are applied to the problem of classifying SAS data for the most appropriate model to use for data analysis. The approach employed is built around the method of weighted k nearest neighbors (wKNN), and utilizes a subset of the models implemented in the SasView package (https://www.sasview.org/) for generating a well defined set of training and testing data. The prediction rate of the wKNN method implemented here using a subset of SasView models is reasonably good for many of the models, but has difficulty with others, notably those based on spherical structures. A novel expansion of the wKNN method was also developed, which uses Gaussian processes to produce local surrogate models for the classification, and this significantly improves the classification accuracy. Further, by integrating a stochastic gradient descent method during post-processing, it is possible to leverage the local surrogate model both to classify the SAS data with high accuracy and to predict the structural parameters that best describe the data. The linking of data classification and model fitting has the potential to facilitate the translation of measured data into results for both novice and expert practitioners of SAS.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1980

SCATHA SSPM charging response: NASCAP predictions compared with data

Models for the satellite surface potential monitor (SSPM) units constructed in the NASCAP code and the results of comparing predictions to surface voltage and baseplate current data are reported. Several peculiarities in the test data are noted. Preliminary results from space simulations of a SCATHA model with environments representative of the day 87, 1979, eclipse injection event are presented, and their implications for predicting space response are discussed.

Purvis, C. K.↗

NASA NTRS1983

Aeroelastic loads prediction for an arrow wing. Task 2: Evaluation of semi-empirical methods

The development and evaluation of a semi empirical method to predict pressure distributions on a deformed wing by using an experimental data base in addition to a linear potential flow solution is described. The experimental data accounts for the effects of aeroelasticity by relating the pressures to a parameter which is influenced by the deflected shape. Several parameters were examined before the net leading edge suction coefficient was selected as the best.

Wery, A. C.↗

NASA NTRS1984

Severe storm initiation and development from satellite infrared imagery and Rawinsonde data

The geographical distribution of potential temperatures, mixing ratio, and streamlines of flow patterns at 850, 700, and 500 mb heights are used to understand the prestorm convection and the horizontal convergence of moisture. From the analysis of 21 tornadoes the following conclusions are reached: (1) Strong horizontal convergence of moisture appeared at the 850, 700, and 500 mb levels in the area 12 hours before the storm formation; (2) An abundantly moist atmosphere below 3 km (700 mb) becomes convectively unstable during the time period between 12 and 24 hours before the initiation of the severe storms; (3) Strong winds veering with height with direction parallel to the movement of a dryline, surface fronts, etc; (4) During a 36-hour period, a tropopause height in the areas of interest is lowest at the time of tornadic cloud formation; (5) A train of gravity waves is detected before and during the cloud formation period. Rapid-scan infrared imagery provides near real-time information on the life cycle of the storm which can be summarized as follows: (1) Enhanced convection produced an overshooting cloud top penetrating above the tropopause, making the mass density of the overshooting cloud much greater than the mass density of the surrounding air; (2) The overshooting cloud top collapsed at the end of the mature stage of the cloud development; (3) The tornado touchdown followed the collapse of the overshooting cloud top.

Hung, R. J.↗

NASA NTRS1985

Geophysical Interpretation of Venus Gravity Data

The subsurface distribution of Venus was investigated through the analysis of the data from Pioneer Venus Orbiter (PVO). In particular, the Doppler tracking data were used to map the gravitational potential. These were compared to the topographic data from the PVO radar (ORAD). In order to obtain an unbiased comparison, the topography data obtained from the PVO-ORAD were filtered to introduce distortions which are the same as those of the gravity models. Both the gravity and filtered topography maps are derived by two stage processes with a common second stage. In the first stage, the topography was used to calculate a corresponding spacecraft acceleration under the assumptions that the topography has a uniform given density and no compensation. In the second stage, the acceleration measures found in the first stage were passed through a linear inverter to yield maps of gravity and topography. Because these maps are the result of the same inversion process, they contain the same distortion; a comparison between them is unbiased to first order.

Reasenberg, R. D.↗

NASA NTRS1985

Geophysical interpretation of Venus gravity data

The investigation of the subsurface mass distribution of Venus through the analysis of the data from Pioneer Venus Orbiter (PVO) is presented. The Doppler tracking data was used to map the gravitational potential, which was compared to the topographic data from the PVO radar (ORAD). In order to obtain an unbiased comparison, the topography obtained from the PVO-ORAD was filtered to introduce distortions which are the same as those of our gravity models. The last major software package that was required in order to determine the spectral admittance Z (lambda) was used. This package solves the forward problem: given the topography and its density, and assuming no compensation, find the resulting spacecraft acceleration along a given nominal trajectory. The filtered topography is obtained by processing these accelerations in the same way (i.e., with the same geophysical inverter) as the Doppler-rate data that we use to estimate the gravity maps.

Reasenberg, R. D.↗

NASA NTRS1989

TranAir and Euler computations of a generic fighter including comparisons with experimental data

The TranAir full-potential code and the FLO57 Euler code were used to calculate transonic flow solutions over two configurations of a generic fighter model. The results were computed at Mach numbers of 0.60 and 0.80 for angles of attack between 0 and 12 deg for TranAir and between 4 and 20 deg for FLO57. Due to the fact that TranAir solves the full-potential equations for transonic flow, TranAir is only accurate to about alpha = 8 deg, at which point the experimental results show the formation of a vortex at the leading edge. Euler results show good agreement with experimental results until vortex breakdown occurs in the solutions.

Goodsell, Aga M.↗

NASA NTRS1994

The moist available energy of a conditionally unstable atmosphere. Part 2: Further analysis of GATE data

The generalized convective available potential energy (GCAPE) observed during GARP Atlantic Tropical Experiment (GATE) has been analyzed using the Lagrangian algorithm of Lorenz, as modified by Randall and Wang. The effects of ice are included and are discussed in an Appendix. A high positive correlation is found between the rate of GCAPE production by large-scale processes and the observed precipitation rate, and a negative correlation between the GCAPE itself and the precipitation rate. The observed time rate of change of the GCAPE is much smaller than the rate of GCAPE production by large-scale processes.

Wang, Junyi↗

NASA NTRS1993

Three-Dimensional Reconstruction of Asteroids from Radar Observations

A program of research has recently been initiated under the NASA Innovative Research Program to develop and test techniques for reconstructing the three-dimensional shapes of asteroids from ground-based radar observations. Presently, no methods exist to do this and the full scientific potential of current radar data sets lies untapped. The situation will become even more pronounced in approximately two years when the upgraded Arecibo radar system becomes capable of regularly producing asteroid data sets with very fine spatial resolution and high signal-to-noise ratios. If successful, the proposed research will significantly increase our knowledge of these objects. The potential and limitations of the techniques developed will be rigorously tested in a series of computer simulations and optical scattering experiments with scale models.

Hudson, Scott↗

NASA NTRS2007

Uncertainty Analysis of Historical Hurricane Data

An analysis of variance (ANOVA) study was conducted for historical hurricane data dating back to 1851 that was obtained from the U. S. Department of Commerce National Oceanic and Atmospheric Administration (NOAA). The data set was chosen because it is a large, publicly available collection of information, exhibiting great variability which has made the forecasting of future states, from current and previous states, difficult. The availability of substantial, high-fidelity validation data, however, made for an excellent uncertainty assessment study. Several factors (independent variables) were identified from the data set, which could potentially influence the track and intensity of the storms. The values of these factors, along with the values of responses of interest (dependent variables) were extracted from the data base, and provided to a commercial software package for processing via the ANOVA technique. The primary goal of the study was to document the ANOVA modeling uncertainty and predictive errors in making predictions about hurricane location and intensity 24 to 120 hours beyond known conditions, as reported by the data set. A secondary goal was to expose the ANOVA technique to a broader community within NASA. The independent factors considered to have an influence on the hurricane track included the current and starting longitudes and latitudes (measured in degrees), and current and starting maximum sustained wind speeds (measured in knots), and the storm starting date, its current duration from its first appearance, and the current year fraction of each reading, all measured in years. The year fraction and starting date were included in order to attempt to account for long duration cyclic behaviors, such as seasonal weather patterns, and years in which the sea or atmosphere were unusually warm or cold. The effect of short duration weather patterns and ocean conditions could not be examined with the current data set. The responses analyzed were the storm latitude, longitude and intensity, as recorded in the data set, 24 or 120 hours beyond the current state. Several ANOVA modeling schemes were examined. Two forms of validation were used: 1) comparison with official hurricane prediction performance metrics and 2) cases studies conducted on hurricanes from the 2005 season, which were not included within the model construction and ANOVA assessment. In general, the ANOVA technique did not perform as well as the established official prediction performance metrics published by NOAA; still, the technique did remarkably well in this demonstration with a difficult data set and could probably be made to perform better with more knowledge of hurricane development and dynamics applied to the problem. The technique provides a repeatable prediction process that eliminates the need for judgment in the forecast.

Green, Lawrence L.↗

DOE OSTI2013

National Geothermal Data System (NGDS) Geothermal Data: Community Requirements and Information Engineering

To satisfy the critical need for geothermal data to advance geothermal energy as a viable renewable energy contender, the U.S. Department of Energy is investing in the development of the National Geothermal Data System (NGDS). This paper outlines efforts among geothermal data providers nationwide to supply cutting edge geo-informatics. NGDS geothermal data acquisition, delivery, and methodology are discussed. In particular, this paper addresses the various types of data required to effectively assess geothermal energy potential and why simple links to existing data are insufficient. To create a platform for ready access by all geothermal stakeholders, the NGDS includes a work plan that addresses data assets and resources of interest to users, a survey of data providers, data content models, and how data will be exchanged and promoted, as well as lessons learned within the geothermal community.

15 GEOTHERMAL ENERGY↗

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.↗

DOE OSTI2022

Consolidated Hydropower Data Repository: Value and Opportunities

Hydropower is one of several types of generating assets that provides energy, capacity, and services to electric power systems. It does so under rubrics and objectives—market driven and regulated, internal and external to asset and fleet owners—that address reliability, cost, price, and, increasingly, flexibility of output. The aggregation of data from multiple hydropower units can provide insights into asset operations and maintenance practices and needs and assist in meeting hydropower objectives. This paper examines the concept and potential benefits of aggregating hydropower asset data—primarily supervisory control and data acquisition (SCADA) information—with examples of insights developed from data aggregated by the Hydropower Research Institute (HRI). Data aggregation as discussed herein, and as implemented by the HRI, extends beyond multiple units in a powerhouse and beyond multiple hydropower facilities in an electric utility fleet or river system. Examples of research and analytics from such aggregated datasets range from unit load dependency analyses to modeling sensor measurements to detect and diagnose anomalies in assets. These examples showed the benefits of utilizing the entire dataset for insights into how the sensor layout of a single unit or set of units compares to the hydropower industry overall. Such insights include whether additional sensors are needed to complete analyses or to make decisions. In addition, utilizing multiple sensors of the same kind within a unit can provide an indication of possible current or upcoming problems with equipment. Although other analyses are possible, their use requires the development of complex models and, potentially, access to types of data that are currently not included with the example dataset used in this study. However, the examples studied herein confirmed the value of data aggregation in the fleet and unit contexts, and the value extends beyond multiple units in a powerhouse and beyond multiple hydropower facilities in an electric utility fleet or river system. The assessments also provided insights into potential extensions to the data aggregation concept that could further add to their value to the hydropower community, and these are included in this document as a set of recommendations.

13 HYDRO ENERGY↗

DOE OSTI2025

Global Simulations Suggest Biomass Burning Aerosol Emissions From Grassland Fires Could Be Important Ice Nucleating Particles

Ice nucleating particles (INP) capable of nucleating ice crystals via immersion freezing at temperatures above approximately −35°C may strongly influence cloud glaciation, with implications for global precipitation and climate feedback. In addition to mineral dust, soil dust, and marine organics, laboratory and field measurements suggest biomass burning aerosols (BBA) can act as immersion-mode INP between around −30°C and −15°C. However, the contribution of BBA to the global INP budget remains poorly understood due to poor knowledge of which fuels yield INPs, uncertainties in global coverage of those fuels, and unknown size distributions of the INPs in the BBA. Nonetheless, with some understanding of these uncertainties from sensitivity studies, the relative importance of ice nucleation activity of BBA compared to other INP sources can be quantified. In this work, we investigate the potential global importance of BBA as INP using a global aerosol-climate model, specifically the UK Met Office Unified Model (UM). We evaluate the model using field campaign data sets. We examine potential uncertainties in fuel types and particle sizes on BBA-based INP concentrations. Averaged over June–September between 15°S and 50°S, BBA is a more important INP than dust and marine INP about 30% of the time at altitudes with temperatures between −30°C and −20°C. Our simulations therefore suggest BBA INPs may be at least as important as mineral dust and marine INP over the atmospheric regions and seasons where grassland fires are frequent.

Gohil, Kanishk [Carnegie Mellon University, Pittsb↗