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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Comparison of Data Quality of NOAA's ISIS and SURFRAD Networks to NREL's SRRL-BMS

This report provides analyses of broadband solar radiometric data quality for the National Oceanic and Atmospheric Administration's Integrated Surface Irradiance Study and Surface Radiation Budget Network (SURFRAD) solar measurement networks. The data quality of these networks is compared to that of the National Renewable Energy Laboratory's Solar Radiation Research Laboratory Baseline Measurement System (SRRL-BMS) native data resolutions and hourly averages of the data from the years 2002 through 2013. This report describes the solar radiometric data quality testing and flagging procedures and the method used to determine and tabulate data quality statistics. Monthly data quality statistics for each network were plotted by year against the statistics for the SRRL-BMS. Some of the plots are presented in the body of the report, but most are in the appendix. These plots indicate that the overall solar radiometric data quality of the SURFRAD network is superior to that of the Integrated Surface Irradiance Study network and can be comparable to SRRL-BMS.

14 SOLAR ENERGY↗
DOE OSTI2018

Test Problems for Programmed Burn [Slides]

This document presents updated FLAG results for the Kenamond programmed burn test problems. Problem definition, exact solutions for constant detonation velocity, and FLAG results using a Huygens solution are provided in Kenamond’s “Lund High Explosive Programmed Burn Model in the FLAG Code” LA-UR-09-08297. FLAG results using Line-of-Sight (LOS) preconditioning of the Huygens solution are presented in Kenamond’s “Line-of-Sight (LOS) High Explosive Programmed Burn Model in the FLAG Code” LA-UR-09-08296. FLAG has an old, serial, uniform-grid “mapped” 2D DSD solver and a new, inline, parallel, conformal mesh 2D/3D DSD solver. These solvers will be exercised with flat Dn-Kappa relations to facilitate comparison with analytic solutions. The remaining slides document FLAG results with 1) Huygens, 2) Huygens with LOS, 3) old DSD, and 4) new DSD. By design, these geometries are coarsely meshed. Plotting error with respect to the analytic solutions reveals sensitivities to element type, element aspect ratio, boundary conditions, detonator timing, and discontinuous detonation velocity. In all plots of this document, color is absolute error relative to the exact solution. In all plots of this document, contours are burntime isochrones of the numerical solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Design and implementation of a data analysis pipeline for paper spray ionization mass spectrometry of UO 2 Cl 2

Ambient mass spectrometry is an emerging characterization method for nuclear materials analysis. SRNL has recently acquired a new JEOL AccuTOF™-DART® LP 4G with a Filter Spray™ front end sample injection system, to develop new methods for ambient mass spectrometry of uranium analytes. Preliminary measurements of uranium-containing samples have demonstrated a need to rapidly evaluate large datasets generated with tailored data analysis scripts. To address this gap a data analysis pipeline written in R within the R Studio environment has been developed. The pipeline comprises a series of processing steps where the data are ingested, analyte peaks of interest are extracted, subsequent ratio and normalization calculations are performed, and results are presented in a series of graphical plots. In detail, the data files containing up to several hundred chronological spectra of a single sample in netCDF format were first extracted into RStudio. Then, initial 3D plots of the data were created in respect to the time, intensity, and mass to charge domains. These graphics serve as an initial easily visualized survey of instrument data. Next, a .csv format file containing the names, masses, and abundances of isotopes of interest were ingested into RStudio and were used to automatically collect intensity values at the mass value. Uranium isotope ratios were plotted against gadolinium isotope ratios (gadolinium was used as an internal standard) and assessed for ion beam stability and intensity. The spectra were filtered by applying a threshold intensity for the 158GdO+ mass channel. A Monte Carlo experiment was performed by creating a theoretical distribution of the data in order to determine the ratio of the uranium isotopes. The results show that the developed data analysis pipeline successfully filters high quality data from overall poor quality runs. Our results also support the idea that paper spray ionization mass spectrometry can be used for both detection and quantification of trace amounts of uranium compounds.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Consortium for Advanced Sorghum Phenomics (CASP). Final report

The goal of CASP was to accelerate breeding of biomass sorghum [Sorghum bicolor (L.) Moench] by identifying genotypes exhibiting high yield under well-watered, pre- or post-drought and/or salinity-stress conditions. We did this by combining high-throughput, non-invasive drone phenotyping with genomics and molecular profiling. Field-based phenotyping utilized a multi-modal sensor suite of LiDAR, multispectral cameras, and thermal cameras mounted on a commercial drone to detect traits required for yield prediction and selection of drought and saline tolerant lines of sorghum. Traits of interest included plant height (PH), leaf area index (LAI), wet biomass (BMW), and biomass at 65% moisture (BM65) and were measured from emergence to harvest on a weekly basis over three growing seasons. The final output were measurements of traits on a plot-by-plot basis, identified by the plot ID used by the Proprietary data processing software enabled raw field data to be turned into plant traits and delivered to the PNNL and JGI within the same workday.

09 BIOMASS FUELS↗
DOE OSTI2019

Brief Guide on Outputting Custom Variables in SABLE

Although SABLE supports a wide variety of variable outputs as a default, the code currently does not readily support outputs of custom variables via the 'plot variables' feature in its input file. Workarounds to this issue exist (such as using `spy'), but the distinct convenience and advantage that the 'plot variables' feature provides, such as easy output of results in .exo file format, disappear. The user may explore the source code to correct this issue, but due to the ongoing nature of code building and complexity of the code spanning multiple languages and layers, exploration and correction of the code can be prohibitively difficult. In this memo, a short guide to modify the code to output desired custom variables via 'plot variables' is listed along with an example variable that evaluates the velocity profile before remapping (VELOCITY PREMAP).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Application of a machine learning algorithm (XGBoost) to offline RHIC luminosity optimization

The operation parameter optimization in 2020 RHIC low energy run is difficult. First, the RHIC luminosity is affected by many RHIC operation parameters, as well as affected by many Low Energy RHIC electron Cooling (LEReC) operation parameters. Second, the luminosity signal in this run is noisy and not sensitive to these parameter changes, especially when these parameters are very close to their optimized values. It is not easy to distinguish the effects of one parameter from all other operation parameters separately. Therefore, it is difficult to optimize the luminosity by varying these parameters one by one. To find a way for luminosity optimization, we analyze some operation parameters via a machine learning algorithm - XGBoost. After constructing a black-box surrogate model from XGBoost and plotting their partial dependency plots (PDF) and SHAP value plots for different operation parameters, we can find the effects of an individual parameter on the RHIC luminosity and optimize it accordingly.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Data set for Conventional Rib Turbulators for SCO2 Turbine Internal Cooling

This data set accompanies NETL Internal Report DOE/NETL-2021/2758. M. Searle, D. Straub, and J. Black, “Conventional Rib Turbulators For SCO2 Turbine Internal Cooling,” National Energy Technology Laboratory, Morgantown, June 28, 2021. The "Configuration" tab details the test configuration geometry and nominal set points. The "Exp point data" tab reports the thermal performance at the midpoint of the Wilson plot. The "Wilson plot data" tab are all Wilson resistance plots reported in the present work.

42 ENGINEERING↗
DOE OSTI2022

Classification of Orbits in Poincare Maps Using Machine Learning

Poincare plots, also called Poincare maps, are used by plasma physicists to understand the behavior of magnetically confined plasma in numerical simulations of a tokamak. These plots are created by the intersection of field lines with a two-dimensional poloidal plane that is perpendicular to the axis of the torus representing the tokamak. A plot is composed of multiple orbits, each created by a different field line as it goes around the torus. Each orbit can have one of four distinct shapes, or classes, that indicate changes in the topology of the magnetic fields confining the plasma. Given the (x, y) coordinates of the points that form an orbit, the analysis task is to assign a class to the orbit, a task that appears ideally suited for a machine learning approach. In this paper, we describe how we overcame two major challenges in solving this problem - creating a high-quality training set, with few mislabeled orbits, and converting the coordinates of the points into features that are discriminating, despite the variation within the orbits of a class and the apparent similarities between orbits of different classes. Our automated approach is not only more objective and accurate than visual classification, but is also less tedious, making it easier for plasma physicists to analyze the topology of magnetic fields from numerical simulations of the tokamak.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Neural MUSE Analysis

Researchers at Oak Ridge National Laboratory (ORNL) created data as part of the MUSE (Multi-Agency Urban Search Experiment Detector and Algorithm Test Bed) project simulating illicit nuclear materials located in various buildings along a road. In the simulation, a truck containing a radiation detector drives down the road gathering listmode data (counting the and energy of incident gamma radiation). Building materials, source shielding, driving speed, truck direction, truck location on the road, source type, and source placement are all varied between runs of the data set. This data was created using deterministic neutron transport and Monte Carlo methods through a combination of SCALE, MAVRIC, MCNP, and GADRAS. As part of a follow-on NA-22 project, two Kaggle competitions were created to determine the best algorithms for finding and identifying gamma sources in this simulated urban environment. The winning algorithm was neural network-based and had a test accuracy of 76.4% accuracy for source identification. This work seeks to build upon this work and improve the results through the application of novel machine learning techniques. As a first step, the data was classified by a simple Convolutional Neural Network (CNN) To accomplish this, the data was first preprocessed into “waterfall plots.” These plots are composed of energy vs count plots that are stacked vertically to show progression in time. The horizontal axis indicating the particle energy incorporated user defined bin spacing with options for in linear-, logarithmic-, square root-, and user-spaced bins. The z or color dimension showed the number of counts corresponding the energy-time combination. This data was then used to generate more data, by generating a local estimate of the mean of the distribution for a bin and then randomly re-sampling that bin from a Poisson distribution. Once all of this data was generated, it was fed into a well-known CNN architecture, ResNet50. The output layer of this model was removed and replaced with layers corresponding to the shape desired isotope outputs. The provided training data was used to train the classifier and the remaining testing data was used to evaluate the model. Results are soon to be forthcoming.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Effects of hurricane disturbance and increased temperature on carbon cycling and storage of a Puerto Rican forest: a mechanistic investigation of above- and belowground processes (Final Technical Report)

The overall goal of the Tropical Responses for Altered Climate Experiment (TRACE) is to assess the effects of increasing temperature on tropical plant and soil carbon fluxes and storage as the forest recovers from major hurricane disturbance that occurred in September 2017. Ultimately, we aimed to reduce uncertainty and increase confidence with which tropical forests are represented in Earth System models to make more accurate global forecasts of future climate. We focused on both above- and belowground processes and explored temperature controls over critical aspects of carbon and nutrient cycling for tropical plants, soil, and microbes. TRACE is located in a wet tropical forest in the Luquillo Experimental Forest close to the USDA Forest Service Sabana Field Research Station in Luquillo, Puerto Rico. The warming treatment consists of six 4.7 m diameter plots. Three of the plots receive infrared warming and three have the same infrastructure but are not warmed (using ‘dummy’ heaters). Each plot was monitored from 2018-2023 to investigate two major questions: 1) Are there legacy effects of prior warming on forest recovery following hurricane disturbance? 2) Will the trajectory of forest recovery following disturbance be affected by warmer temperatures? Concurrent soil incubation experiments were conducted to enable more controlled mechanistic investigations of temperature response on microbial function. In sum, our goal was to use this novel climate manipulation experiment (the only of its kind in any tropical forest) and once-in-a-lifetime chance to assess how temperature and hurricane disturbance interact to affect coupled biogeochemical cycling in a tropical forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

EDXplorer: A Utility for APA Analysis

The automated particle analysis (APA) method of scanning electron microscopy (SEM) energy dispersive X-ray spectroscopy (EDS/EDX) is a useful tool for analyzing the elemental and morphological data of particulate samples. Often, such datasets have many thousands of particles, and it can be difficult to sift through the data to find meaningful trends. EDXplorer is a software utility for processing APA data. They enable the user to easily load data and determine the important components and aspects of the datasets using a powerful and versatile library of data plotting functions, mainly centered around scatter plots and histograms. These programs are intended to fill a void in the data processing of data from certain instruments, where often the user must rely on their own code or other software that is not user-friendly. EDXplorer is intended as a general plotting utility for browsing through data and discovering data trends.

Moseley, Duncan [ORNL] (ORCID:0000000343518347)↗
DOE OSTI2017

Point Cloud Based Approach to Stem Width Extraction of Sorghum

A revolution in the field of genomics has produced vast amounts of data and furthered our understanding of the genotypephenotype map, but is currently constrained by manually intensive or limited phenotype data collection. We propose an algorithm to estimate stem width, a key characteristic used for biomass potential evaluation, from 3D point cloud data collected by a robot equipped with a depth sensor in a single pass in a standard field. The algorithm applies a two step alignment to register point clouds in different frames, a Frangi filter to identify stemlike objects in the point cloud and an orientation based filter to segment out and refine individual stems for width estimation. Individually, detected stems which are split due to occlusions are merged and then registered with previously found stems in previous camera frames in order to track temporally. We then refine the estimates to produce an accurate histogram of width estimates per plot. Since the plants in each plot are genetically identical, distributions of the stem width per plot can be useful in identifying genetically superior sorghum for biofuels.

09 BIOMASS FUELS↗
DOE OSTI2018

SPRUCE Bog Surface Elevation Assessments with SPRUCE Elevation Transect Instrument, Marcell Experimental Forest, Minnesota, 2013-2025

This data set reports plot-specific bog surface elevation measurements collected with the SPRUCE Elevation Transect (SET) instrument at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. The SET instrument is a modified version of the Cahoon et al. (2002) surface elevation table instrument. The device is mounted to fixed stands that are anchored in deep sediments, making it capable of identifying subtle changes in bog surface elevation over time. Measurements are reported as absolute elevation in meters above mean sea level (amsl) for two locations in each of the SPRUCE experimental treatment plots and additional ambient boardwalk plots: 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20 and 21. Measurements were collected from June 2013 through September 2025 (2013-06-02 to 2025-09-08). Changes in bog surface elevation may indicate alterations in the carbon and water cycles due to changing environmental conditions. This data set contains one data file in comma separate (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

SPRUCE Phospholipid Fatty Acid (PLFA) Abundances, August 2021-June 2022

This data set provides the results for phospholipid fatty acid analysis (PLFA) of peat samples collected from ambient plots in the SPRUCE experiment site, with experimental plot samples still being processed. The samples used to generate this data set were collected on 2021-08-23 and 2022-06-21. This data set includes abundances for groups of lipids indicating total biomass, fungi, Gram-positive bacteria, Gram-negative bacteria, actinomycetes, and anaerobic bacteria. This data set contains one file in comma separate (*.csv) format. Samples: On each sampling date, cores extending to 200 cm were collected and subsampled at 10 cm intervals from 0 and 100 cm and 25 cm intervals below 100 cm depth in Plot 7 and 21. During the lipid extraction procedure, samples were pooled into the following depth increments in order to obtain sufficient material to achieve adequate lipid yield: 0-10, 10-20, 20-30, 30-50, 50-100, and 100-150, and 150-200 cm.

actinomycetes↗
DOE OSTI2023

SPRUCE Anaerobic oxidation of methane mitigates net methane production and responds to long-term experimental warming in a northern bog: Supporting data

This data set contains measurements of anaerobic oxidation of methane (AOM), net methane (CH4) production, carbon dioxide (CO2) production, and gross CH4 production measurements from the SPRUCE experiment (Hanson et al. 2017). CH4 is greenhouse gas with 45 times the sustained global warming potential of CO2 over 100 years, which may have significant implications on global climate change. The process of AOM plays a large role in the extent of CH4 emissions from wetland environments like those at the SPRUCE experiment site. This study conducted two on different dates. In experiment 1, net CH4 and CO2 production were measured with a gas chromatograph through the peat profile at in situ temperatures of the SPRUCE plots four times from May to October, 2016 (2016-05 to 2016-10). Two treatments were examined, a Porewater Treatment that was a 1:1 volumetric peat:porewater slurry and a No Porewater Treatment that was field-moist peat with no porewater added. Additionally, net CH4 production were measured at frequent intervals (from 4 hr to 9 d) in peat from selected SPRUCE plots from soil collected on October 16, 2016 (2016-10-16). Samples were collected from the SPRUCE plots, immediately made anaerobic, and transported to the University of Oregon for rate measurements within several days of collection. In experiment 2, AOM, net CH4 production, CO2 production, and gross CH4 production were measured through the peat profile at in situ field temperatures once from samples collected in July, 2021 (2021-07). The same two porewater treatments were examined. AOM was measured with a 13CH4 tracer method using a Picarro G2201-i analyzer for isotopic CO2/CH4 quantification with a small stable isotope module attached. This data set contains three data files in comma separate (*.csv) format. This data set is associated with the following publication: Barney, M, AM Hopple, LL Gregory, JK Keller, and SD Bridgham. 2024. Anaerobic oxidation of methane mitigates net methane production and responds to long-term experimental warming in a northern bog. Soil Biology and Biochemistry, 190, 109316. https://doi.org/10.1016/j.soilbio.2024.109316.

SPRUCE Experiment, Marcell Experimental Forest, Me↗
DOE OSTI2019

Legacy effects of long-term CO2 enrichment on plant biomass recovery from fire seven years after return to ambient CO2 levels1

We sought to determine if elevated CO2 resulted in long-lasting changes to plant structure and function, particularly disturbance response patterns. Minimal legacy effects were observed 1 yr after the termination of a previous long-term experiment; however, those observations were based on 1 yr of data and only focused on fine root growth, herbivory, and arthropod diversity. We examined above- and belowground biomass inside the footprints of chambers from a former long-term elevated CO2 experiment in a scrub-oak community 7 yr after CO2 enrichment ceased and 2 yr after fire. Aboveground biomass was 40.6% higher in the previously elevated plots compared with ambient plots, suggesting that there are legacy effects in the form of more rapid aboveground recovery from fire on previously elevated CO2 plots. Belowground biomass exhibited minimal change since the historic CO2 enrichment, suggesting that differences were a result of the original treatment. After disturbance, regrowth occurs via sprouting from large belowground structures; thus changes in aboveground recovery are likely due to changes to belowground biomass caused by altered atmospheric CO2. Elevated CO2 has significantly affected disturbance recovery patterns in this community. These changes have the potential to alter plant carbon allocation patterns in frequently disturbed systems.

Plant Sciences↗
DOE OSTI2016

SPRUCE Whole Ecosystems Warming (WEW) Environmental Data Beginning August 2015

This data set provides a record of the half-hourly averages of automated environmental data collected for 12 SPRUCE plots (4, 6, 7, 8, 10, 11, 13, 16, 17, 19, 20, and 21) beginning during deep peat heating (DPH) and continuing throughout the whole ecosystem warming (WEW) manipulations for the SPRUCE Project (Hanson et al. 2017). In August 2015, WEW was initiated at 5 warming levels (+0, +2.25 +4.5, +6.75 and +9 °C) with 2 plots per warming level. DPH measurements were underway before the initiation of WEW heating treatments and both are expected to operate through 2025. This current version includes data from 2014 through 2024. This data set includes 15 data files provided in comma separated (*.csv) format: 12 individual data files for each of the monitored SPRUCE plots, two data files corresponding to figures from Hanson et al. (2017) that support key analyses of the performance of the WEW systems, and one data file containing snow and ice depths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Belowground Response to Drought in a Tropical Forest Soil. II. Change in Microbial Function Impacts Carbon Composition

Climate model projections for tropical regions show clear perturbation of precipitation patterns leading to increased frequency and severity of drought in some regions. Previous work has shown declining soil moisture to be a strong driver of changes in microbial trait distribution, however, the feedback of any shift in functional potential on ecosystem properties related to carbon cycling are poorly understood. Here we show that drought-induced changes in microbial functional diversity and activity shape, and are in turn shaped by, the composition of dissolved and soil-associated carbon. We also demonstrate that a shift in microbial functional traits that favor the production of hygroscopic compounds alter the efflux of carbon dioxide following soil rewetting. Under drought the composition of the dissolved organic carbon pool changed in a manner consistent with a microbial metabolic response. We hypothesize that this microbial ecophysiological response to changing soil moisture elevates the intracellular carbon demand stimulating extracellular enzyme production, that prompts the observed decline in more complex carbon compounds (e.g., cellulose and lignin). Furthermore, a metabolic response to drought appeared to condition (biologically and physically) the soil, notably through the production of polysaccharides, particularly in experimental plots that had been pre-exposed to a short-term drought. This hysteretic response, in addition to an observed drought-related decline in phosphorus concentration, may have been responsible for a comparatively modest CO 2 efflux following wet-up in drought plots relative to control plots.

54 ENVIRONMENTAL SCIENCES↗