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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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This tool provides interfaces for ingesting real-time unit commitment data (e.g., from a grid operator's control room energy management system) and calculating system inertia estimates based on the H-constant method, before relaying those estimates to customizable visualization or logging outputs.
These data are from Bandopadhyay et al., "Soil microbial ecology and microbiome-metabolite linkages improve understanding of ecosystem states along terrestrial-aquatic interfaces". This study aims to understand the soil microbial ecology along terrestrial-aquatic interfaces of a freshwater and estuarine region and how it relates to organic matter. We analyzed soil microbial (16S rRNA gene) and organic matter (Fourier-transform ion cyclotron resonance mass spectrometry, FTICR-MS) composition from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie (freshwater) and Chesapeake Bay (estuarine) regions. This dataset includes 16S rRNA gene amplicon data (only processed file types included here) and organic matter composition from FTICR-MS data (raw and processed files included here) from upland (forested), transition (stressed forest), and wetland positions at three sites in each of the Lake Erie and Chesapeake Bay regions. These sites are part of the COMPASS-FME project (https://compass.pnnl.gov/FME/COMPASSFME). File formats and software needed to access files: 16S rRNA gene amplicon data: These files follow the format reported here https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format#updates-in-v1.0.1. As per this format, there are four file types reported: 1. Taxon tables (also called sequence-by-sample or OTU (operational taxonomic unit)/ESV (exact sequence variant) tables) : available in a .txt file format and accessible using TextEdit or MS Excel. 2. Representative sequences (also called consensus sequences) : available in a .fasta format and accessible using TextEdit. 3. Sequencing metadata : available in a MS Excel workbook file format and CSV file format 4. Bioinformatic metadata : available in a MS Excel workbook file format and CSV file format FTICR-MS data: 1. Raw data converted to a processed file with intensities of the peaks in the given samples : available in a MS Excel CSV file format 2. Processed file used in analyses and visualizations (appended as icr_long_) : available in a MS Excel CSV file format 3. Metadata file for ICR features (appended as icr_meta) : available in a MS Excel CSV file format
The ideal design and operation of small hydropower plants is a complex optimization problem with economic, social, and environmental objectives. The waterSHED (Water Allocation Tool Enabling Rapid Small Hydropower Environmental Design) model is a user-friendly tool that allows hydropower stakeholders to model the trade-offs among these objectives using the Standard Modular Hydropower (SMH) framework. The SMH framework employs modular technologies that can be represented as blackbox objects and combined within a river to create a hydropower facility. For a given site, the waterSHED model aims to determine which modules should be placed in a facility and how those modules should be operated. This user guide describes how to use the graphical user interface and related functionalities. This document also summarizes the background research and mathematical formulations that are explained indepth in the accompanying doctoral dissertation. This model is an early step toward a new hydropower design process that employs standardization and modularity to reduce costs, development timelines, and challenges regarding social and environmental mitigation measures for low-head, small hydropower development. The waterSHED model is a Python application that will require the ability to download a GitHub repository, import the necessary packages, and run a set of Python script files using an integrated development environment. The script produces a graphical user interface to coordinate inputs, simulate operation, and visualize results, so no coding experience is needed once the script is running. Additionally, the waterSHED Workbook is a Microsoft Excel file that works with the Python script to facilitate data entry
The NNSA Seismic Cooperation Program (SCP) sponsored Stephen Myers (LLNL), Michael Begnaud (LANL), Brian Young (SNL) and Istvan Bondar (Research Center for Astronomy and Earth Sciences, Hungary) to serve as a presenters/trainers at the “NDC Capacity Building Workshop and Regional Seismic Travel Time (RSTT) in combination with Data Sharing and Integration Training” September 4-8 2022 in Muscat, Oman (See Appendix A for the agenda). The workshop and training (workshop from here forward) was organized by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) Provisional Technical Secretariat (PTS). The first half of the week was devoted to NDC workshop activities, and the second half was devoted to RSTT training. Fifty-five participants from 27 countries and the CTBTO-PTS attended the 5-day workshop (See Appendix B for list of participants and countries of origin). Presentations from the PTS described the International Monitoring System (IMS), International Data Centre (IDC) products, and metrics of regional data utilization. Contributed presentations from each country’s scientists included descriptions of regional and national networks, methods of data analysis, and needs for material and technical assistance. Training included an overview of the RSTT method and instruction on how to locate seismic events with the iLoc program, which utilizes RSTT travel times to reduce bias in event location estimates. Methods of seismic tomography and the need for a high-quality tomographic set, including seismological “ground truth”, were emphasized. Seismological “ground truth” or “GT” is a term that has come to mean both events with known location and events with well-characterized locations that are estimated using seismological data, typically with epicenter accuracy of 5 km or better. Notably, the instructional platform has migrated from UNIX shell scripts to Jupyter Notebooks. Jupyter Notebooks have the advantage being more visually intuitive, including display of graphics within the notebook. Each notebook includes every processing step that participants need to reproduce the entire exercise.
We perform a search for galaxy–galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains ~520 million astronomical sources covering ~4000 deg 2 of the southern sky to a 5σ point–source depth of g = 24.3, r= 23.9, i = 23.3, and z = 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ~11 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap (b > 10 deg) and southern celestial hemisphere (decl. < 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.
Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.
Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.
A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.
Virtual reality for biomolecular electrostatics UnityMol-APBS (NIH iEdison No. 0685901-19-0009, Grant No. GM069702) Visualization of molecular electrostatics on a two-dimensional screen greatly diminishes the associated depth component. Using a virtual world to explore molecular electrostatics allows researchers to be immersed within their data.
Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.
The objectives of this project were to develop new sample environments, measurement methodologies and associated modeling tools for characterizing the structural response to arbitrarily complex processing flows using small angle scattering, and to apply these new tools for understanding the fundamental physics governing the structuring of anisotropic particulate and polymeric materials under flow histories and conditions relevant to industrial processing flows. The research resulted in the development and implementation of a new sample environment, the fluidic four roll mill (FFoRM), for in situ small angle neutron and X-ray scattering (SANS/SAXS) measurements. These measurements are capable of generating large data sets that “fingerprint” how a complex fluid responds to a wide range of flow histories involving time variations in deformation type and rate. New modeling tools were developed to extract detailed microstructural information from such data sets, including orientation distribution functions and interparticle correlation functions, as well as reduced-order parametric descriptors of these high-dimensional functions that can be used to readily map, visualize and interpret a fluid’s structural response to its flow history. These new tools were applied to a range of model materials involving elongated particle suspensions in order to provide new insights into the physics of how flow couples with orientational and structural order in complex flows, particularly under non-dilute conditions for which no accurate theories currently exist. Using these investigations, we elucidated a number of new insights into the fundamental phenomena driving such process-structure-property relationships. These findings provide guidance for the further development of rheological models, and ultimately can inform the rational and model-based design of flow processes to achieve optimized orientational ordering that is key to the properties and function of a wide range of energy-relevant materials.
The Material Recovery & Recycle group (AMPP-4) Tank Tracking Tools are Microsoft Excel-based tools used to visualize the liquid levels in the tanks used by teams within AMPP-4. The tools rely on reports generated by the Tracking Hydrogen Accumulation in Aqueous Operations spreadsheet to provide daily data of the volume occupied by radioactive liquid waste (RLW). This set-up allows for rapid-response in viewing historical (from October 2024) and current data in thermometer-type charts.
Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.
Group II introns are ubiquitous self-splicing ribozymes and retrotransposable elements evolutionarily and chemically related to the eukaryotic spliceosome, with potential applications as gene-editing tools. Recent biochemical and structural data have captured the intron in multiple conformations at different stages of catalysis. Here, we employ enzymatic assays, X-ray crystallography, and molecular simulations to resolve the spatiotemporal location and function of conformational changes occurring between the first and the second step of splicing. We show that the first residue of the highly-conserved catalytic triad is protonated upon 5’-splice-site scission, promoting a reversible structural rearrangement of the active site (toggling). Protonation and active site dynamics induced by the first step of splicing facilitate the progression to the second step. Our insights into the mechanism of group II intron splicing parallels functional data on the spliceosome, thus reinforcing the notion that these evolutionarily-related molecular machines share the same enzymatic strategy.
Molten salt infiltration in the pore network of nuclear graphite may cause unwanted changes to graphite's local structure and mechanical and thermal properties. A detailed and comprehensive understanding of molten salt intrusion (distribution across sample cross section and penetration depth) is needed to assess its effects. Here, in this work, we report on an improved methodology for the use of neutron imaging (computed tomography) to evaluate salt penetration and distribution of a wide range of graphite grades with diverse microstructures. Neutron tomography data were acquired on the same graphite sample before and after salt intrusion; the 3D reconstructed volumes were digitally co-registered and subtracted. The difference in neutron attenuation coefficient represents direct visualization of FLiNaK (LiF–NaF–KF) salt distribution in the salt-impregnated graphite samples. This improved methodology was applied to investigate the effect of exposure times (12 h and 336 h) and of graphite microstructure when exposed to FLiNaK at 750 °C and 3 bar (gauge) pressure, starting from flowing argon at near atmospheric pressure. The results show that medium-grained and fine-grained graphites evolve to equilibrium at significantly different rates: fast salt uptake in medium-grained graphites produces salt deposits throughout the volume of graphite specimens, whereas salt infiltration in fine-grained graphites is much slower and limited to exposed surfaces.
Recent progress in gas dynamic virtual nozzle (GDVN) technologies in combination with high-brilliance synchrotron and X-ray free-electron lasers (XFELs) has allowed the visualization of protein dynamics in crystallo by mixing macromolecular protein crystals with a substrate using tunable mixing times on the order of milliseconds to seconds prior to serial X-ray diffraction data collection. This has become the method of choice for high-resolution structure determination of intermediate states. However, such experiments require large counts of crystals of proper sizes for high-resolution data collection, and premium beam times for screening efforts. Cryogenic microcrystal electron diffraction (MicroED) represents a complementary technique that may be a more accessible avenue for time-resolved nanocrystallography compared with serial X-ray diffraction experiments. MicroED can produce full diffraction datasets from just a few submicrometre-thick crystals, and the approach is more readily accessible, requiring standard cryogenic transmission electron microscopy (TEM) equipment available at many universities and institutes. Cryogenic MicroED, like other forms of cryo-EM, begins with rapidly freezing biological material on electron microscopy grids. In the case of MicroED, micro- to nano-crystals (<500 nm thick) are deposited onto electron microscopy grids and plunge-frozen for subsequent electron diffraction data collection. Here, we have incorporated GDVN technology developed originally for XFEL experiments into the freezing process as a first step towards time-resolved studies. We describe the limited deposition efficiency of the model MicroED protein proteinase K on TEM grids using GDVNs, preceding sample vitrification and successful MicroED data collection. We discuss both the initial results from such experiments and the methodological challenges in developing this approach into a reliable workflow for millisecond-to-second time-resolved structural studies of macromolecules. Our results promise a strategy to deposit crystals on grids using GDVNs and determine high-resolution structures by MicroED, constituting a first step towards development of time-resolved MicroED experiments.
GRAVI (GRid Analysis and Visualization Interface) is a web application for viewing and analyzing nodal Production Cost Model (PCM) and Capacity Expansion Model (CEM) simulations. The web application provides the ability to animate geospatially coupled timeseries data in an agnostic way regardless of the underlying simulation tool used to generate the data. GRAVI also provides capabilities to animate non-geospatial data relevant to a PCM or CEM model. Furthermore, this web application can be tailored as an real-time operational tool to better understand a live grid.
The dashboard is a useful tool for early-stage building design decision-making and communication, as it can help users quickly compare the energy and non-energy related performance of various automated, integrated facade systems using a library of pre-computed data. Users can explore the impacts of various design choices by selecting different facade glazing and shading systems, facade control strategies, and lighting control strategies across multiple climate zones. The dashboard instantly visualizes key metrics, including energy usage in HVAC and lighting, peak cooling and heating load, and daylight availability, allowing immediate trade-off analysis to optimize building efficiency and comfort.