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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Support for the Second MOSAiC Science Conference support (Final Report)

This is a final report for a conference support project. The US Department of Energy’s Atmospheric System Research Program provided funding support for the Second MOSAiC Science Conference. MOSAiC is the Multidisciplinary drifting Observatory for the Study of Arctic Climate, a yearlong, international expedition into the rapidly changing Arctic sea ice. The expedition collected measurements of the atmosphere, sea ice, and ocean to study coupled physical, chemical, and biological processes. The Second MOSAiC Science Conference provided an important opportunity to bring the MOSAiC-interested community together to discuss MOSAiC data, scientific analyses, synthesis, modeling activities, and more. Overall, the conference was a significant success and has motivated and facilitated a great deal of ongoing research. The support provide by this project was used along with support from other agencies to implement a participant support program that enabled participation in the conference by a diverse collection of researchers from many different countries and disciplines, 60% of whom were female. Most of these participants were Early Career Researchers. Participation by these researchers was vital to the overall success of the conference and has helped to build leadership and research skills for the participants that will serve both themselves and the broader scientific community in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Colorado State University (CSU) X-Band Precipitation Radar Plan Position Indicator Data Processed with Corrected Moments in Antenna Coordinates (CMAC) Value-Added Product Report

In 2010 the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility procured 3- and 5-cm wavelength radars for documenting the macrophysical, microphysical, and dynamical structure of precipitating systems. To maximize the scientific impact, ARM supported the development of an application chain to correct for various phenomena in order to retrieve the “point” values of moments of the radar spectrum and polarimetric measurements. We have now used the lessons learned from the processing of the 3- and 5-cm wavelength radars obtained by ARM to help process X-band radar data from the Surface Atmospheric Integrated Field Laboratory (SAIL) field campaign. This report details the motivation, science, and progress to date as well as charting a path forward.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Iron-starvation induces photosystem I antenna remodeling in green algae

Dunaliella salina and Dunaliella tertiolecta are extremophile, marine algae that can survive in very low Fe conditions. In this study, we used TMT-proteomics to compare the Fe starvation responses to the Fe replete responses. Samples were digested with trypsin, labeled with TMT 10-Plex, then analyzed by LC-MS/MS. Data was searched with MS-GF+ using PNNL's DMS Processing pipeline.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

2024 Standard Scenarios: A U.S. Electricity Sector Outlook

This data corresponds to the 2024 Standard Scenarios report, which contains a suite of forward-looking scenarios of the possible evolution of the U.S. electricity sector through 2050. These files contain modeled projections of the future. Although we strive to capture relevant phenomena as comprehensively as possible, the models used to create this data are unavoidably imperfect, and the future is highly uncertain. Consequentially, this data should not be the sole basis for making decisions. In addition to drawing from multiple scenarios within this set, we encourage analysts to also draw on projections from other sources, to benefit from diverse analytical frameworks and perspectives when forming their conclusions about the future of the power sector. For further discussions about the limitations of the models underlying this data, see section 1.4 of the "ReEDS Documentation" linked below. For scenario descriptions, input assumptions, and metric definitions for the data in these files, see the "2024 Standard Scenarios Report" linked below.

2050↗
DOE OSTI2026

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗
DOE OSTI2022

Graph-based featurization methods for classifying small molecule compounds

For over a decade, drug-induced liver injury (DILI) has posed significant drawbacks in the synthesis and development of drugs and remains a consequential concern. With finite success within the existing preclinical models, DILI is one of the main causes of drug withdrawal or termination from the market. Particularly, this withdrawal occurs during the late stages of drug development (Kullak-Ublick, 2017). Since DILI is difficult to diagnose and treat, it has become an obstacle in the drug production market that in turn affects clinicians, pharmaceutical companies, and consumers. We propose a method for learning features of DILI-positive drugs based on the graphical relationships and patterns they possess within a network of biological databases. We also train various statistical and machine learning models on these learned features in order to classify the drugs as DILI-positive or negative. Our methods include Random Forest, Neural networks, and logistic regression classification. We utilize labeled DILI-positive and DILI-negative datasets, which were developed by the FDA and the National center for toxicological research, as well as additional literature datasets (Thakkar, 2020) in order to validate our results and assess our featurization and model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Introducing the Video In Situ Snowfall Sensor (VISSS)

The open-source Video In Situ Snowfall Sensor (VISSS) is introduced as a novel instrument for the characterization of particle shape and size in snowfall. The VISSS consists of two cameras with LED backlights and telecentric lenses that allow accurate sizing and combine a large observation volume with relatively high pixel resolution and a design that limits wind disturbance. VISSS data products include various particle properties such as maximum extent, cross-sectional area, perimeter, complexity, and sedimentation velocity. Initial analysis shows that the VISSS provides robust statistics based on up to 10 000 unique particle observations per minute. Comparison of the VISSS with the collocated PIP (Precipitation Imaging Package) and Parsivel instruments at Hyytiälä, Finland, shows excellent agreement with the Parsivel but reveals some differences for the PIP that are likely related to PIP data processing and limitations of the PIP with respect to observing smaller particles. The open-source nature of the VISSS hardware plans, data acquisition software, and data processing libraries invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

nmrrr : A Reproducible Workflow for Binning and Visualizing NMR Spectra From Environmental Samples

Nuclear magnetic resonance (NMR) spectroscopy is a useful tool for detection and identification of molecular structural information, with increasing applications in environmental sciences. NMR instrument outputs are however heterogeneous and require extensive post-processing, creating barriers to their use and application by non-specialists. Here, we report on a new open-source R package, nmrrr, that processes and visualizes spectral data obtained from one-dimensional solution-state and solid-state NMR experiments; the package also performs relevant calculations commonly applied in natural organic matter communities, such as computing the relative abundance of various functional groups. We document the package's installation, dependencies, and functions; and provide a standard workflow for processing NMR data. This package is currently available on CRAN and GitHub, and community contributions are welcome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An evidential reasoning-based AHP approach for the selection of environmentally-friendly designs

Due to the stringent environmental regulatory requirements being imposed by cross-national bodies in recent years, manufacturers have to minimize the environmental impact of their products. Among those environmental impact evaluation tools available, Life Cycle Assessment (LCA) is often employed to quantify the product's environmental impact throughout its entire life cycle. However, owing to the requirements of expert knowledge in environmental science and vast effort for data collection in carrying out LCA, as well as the common absence of complete product information during product development processes, there is a need to develop a more suitable tool for product designers. An evidential reasoning-based approach, which aims at providing a fast-track method to perform design alternative evaluations for non-LCA experts, is therefore introduced as a new initiative to deal with the incomplete or uncertain information. The proposed approach also enables decision makers to quantitatively assess the life cycle phases and design alternatives by comparing their potential environmental impacts, thus effectively and efficiently facilitates the identification of greener designs. A case application is carried out to demonstrate the applicability of the proposed approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Concept for Cyber-Physical Consequence Process

The Department of Homeland Security’s Office of Cyber and Infrastructure Analysis (DHS/OCIA) has a mission and vision that promotes innovation as central to expanding the organization’s capability to conduct consequence analysis. To pursue such innovation, OCIA is sponsoring a seedling effort with Idaho National Laboratory (INL) to leverage data from the proposed Automated Vulnerability Assessment (AVA) capability, which the DHS Science and Technology (S&T) Directorate is developing through a separate INL effort. The first phase of this effort is to develop a process by which recognized vulnerabilities can be scored relative to importance, reflected primarily in the ability to initiate high consequence and potentially cascading events. This report documents a cyber-physical metrics process (CPMP) to tie physical impact to the malicious exploitation of cyber vulnerabilities in industrial control systems (ICS) with the potential for initiating consequence in the critical infrastructure. The scale of achieving any particular physical consequence is dependent upon the ICS Component the vulnerability exists on, the Level of Access that the exploit would allow to component function and the Physical Impact (CLAPI) to the power system that the component is tied. A modified common vulnerability scoring system (CVSS) was detailed and demonstrated for the power sector with three case studies associated with a recognized vulnerability, with significant consequence detail provided to apply the process across the power sector. A detailed table that provides background on the power system components, ICS-enabled monitoring and control, potential consequence effects, and CVSS scoring is provided. To demonstrate the applicability of the CPMP, tables are provided as examples for other sectors that include chemical, water/wastewater and oil/gas.

42 ENGINEERING↗
DOE OSTI2019

110th Anniversary: Bridging the Time and Length Scales of Process Systems with Data

Here we report on the role of data as a "bridge" connecting the different time/length scales of chemical processes in mathematical modeling and multi-scale, integrated decision making. We argue that this is a fitting role of "big data" in the chemical industry, an area that comprises complicated yet deterministic physical systems. Such systems can be described using physical and chemical laws that are generally well-understood. Accordingly, data and data analysis are less likely to provide the unexpected and/or surprising insights that they have generated in other sectors (e.g., the transactional economy, social sciences). Nevertheless, historical operating data (which are often plentiful and available at little cost) can be converted to very useful information for multi-scale mathematical modeling of chemical processes. Several examples of integration are provided, mapped on the continuum of time and length scales of process systems. Current research challenges and potential directions for future work are discussed.

42 ENGINEERING↗
DOE OSTI2015

Advanced High-Level Waste Glass Research and Development Plan

The U.S. Department of Energy Office of River Protection (ORP) has implemented an integrated program to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product quality requirements. The integrated ORP program is focused on providing a technical, science-based foundation from which key decisions can be made regarding the successful operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) facilities. The fundamental data stemming from this program will support development of advanced glass formulations, key process control models, and tactical processing strategies to ensure safe and successful operations for both the low-activity waste (LAW) and high-level waste (HLW) vitrification facilities with an appreciation toward reducing overall mission life. The purpose of this advanced HLW glass research and development plan is to identify the near-, mid-, and longer-term research and development activities required to develop and validate advanced HLW glasses and their associated models to support facility operations at WTP, including both direct feed and full pretreatment flowsheets. This plan also integrates technical support of facility operations and waste qualification activities to show the interdependence of these activities with the advanced waste glass (AWG) program to support the full WTP mission. Figure ES-1 shows these key ORP programmatic activities and their interfaces with both WTP facility operations and qualification needs. The plan is a living document that will be updated to reflect key advancements and mission strategy changes. The research outlined here is motivated by the potential for substantial economic benefits (e.g., significant increases in waste throughput and reductions in glass volumes) that will be realized when advancements in glass formulation continue and models supporting facility operations are implemented. Developing and applying advanced glass formulations will reduce the cost of Hanford tank waste management by reducing the schedule for tank waste treatment and reducing the amount of HLW glass for storage, transportation, and disposal. Additional benefits will be realized if advanced glasses are developed that demonstrate more tolerance for key components in the waste (such as Al 2 O 3 , Cr 2 O 3 , SO 3 and Na 2 O) above the currently defined WTP constraints. Tolerating these higher concentrations of key waste loading limiters may reduce the burden on (or even eliminate the need for) leaching to remove Cr and Al and washing to remove excess S and Na from the HLW fraction. Advanced glass formulations may also make direct vitrification of the HLW fraction without significant pretreatment more cost effective. Finally, the advanced glass formulation efforts seek not only to increase waste loading in glass, but also to increase glass production rate. When coupled with higher waste loading, ensuring that all of the advanced glass formulations are processable at or above the current contract processing rate leads to significant improvements in waste throughput (the amount of waste being processed per unit time),which could significantly reduce the overall WTP mission life. The integration of increased waste loading, reduced leaching/washing requirements, and improved melting rates provides a system-wide approach to improve the effectiveness of the WTP process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Modeled sub-hourly nitrate concentrations in subsurface water across a salt marsh system in Elkhorn Slough, California

Salt marshes are dynamic hydrologic systems where terrestrial groundwater, terrestrial surface water, and seawater mix due to bi-directional flows and pressure gradients. Salt marshes are known to remove excess nitrate from water thereby improving water quality in coastal systems. However, our knowledge of the short-term processes (e.g., intra-tidal) in salt marshes is limited. Further, we lack knowledge about how these short-term dynamics may change as a function of seasonality. To address this knowledge gap, we develope a sampling methodology that allowed us to continuously measure nitrate in subsurface water at three different depths across three marsh elevations at sub-hourly time steps. Here we present a data table with the results of nitrate in porewater across the three salt marsh elevations (information in the data set). We analyzed nitrate with a s::can spectrophotometer. We used the UV-Vis absorbance of the samples to calculate nitrate concentrations using a local calibration library. More information about the methodology can be found in Grande et al (2023). Seasonal and Tidal Variations in Hydrologic Inputs Drive Salt Marsh Porewater Nitrate Dynamics, Hydrological Processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Imaging of Nuclear Weapon Trainers

The Configurable Muon Tracker (CMT) is an adaptation of the existing drift tube detector commercially available from Decision Sciences International Corporation (DSIC). NSTec engineered the CMT around commercially available drift tube assemblies to make a detector that is more versatile than previous drift tube assemblies. The CMT became operational in February 2013. Traditionally, cosmic-ray muon trackers rely on near-vertical trajectory muons for imaging. Since there are scenarios where imaging using vertical trajectory muons is not practical, NSTec designed the CMT specifically for quick configurability to track muons from any trajectory. The CMT was originally designed to be changed from vertical imaging mode to horizontal imaging mode in a few hours with access to a crane or other lifting equipment. In FY14, locations for imaging weapon trainers and SNM were identified and it was determined that lifting equipment would not typically be available in experimental areas. The CMT was further modified and a portable lifting system was developed to allow reconfiguration of the CMT without access to lifting equipment at the facility. This system was first deployed at Los Alamos National Laboratory’s W-division, where several trainers were imaged in both horizontal and vertical modes. Real-time images have been compared in both modes showing that imaging can be done in both modes with the expected longer integration time for horizontal mode. Further imaging and post processing of the data is expected to continue into early FY15.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

THE SLOAN DIGITAL SKY SURVEY STRIPE 82 IMAGING DATA: DEPTH-OPTIMIZED CO-ADDS OVER 300 deg{sup 2} IN FIVE FILTERS

We present and release co-added images of the Sloan Digital Sky Survey (SDSS) Stripe 82. Stripe 82 covers an area of ∼300 deg{sup 2} on the celestial equator, and has been repeatedly scanned 70-90 times in the ugriz bands by the SDSS imaging survey. By making use of all available data in the SDSS archive, our co-added images are optimized for depth. Input single-epoch frames were properly processed and weighted based on seeing, sky transparency, and background noise before co-addition. The resultant products are co-added science images and their associated weight images that record relative weights at individual pixels. The depths of the co-adds, measured as the 5σ detection limits of the aperture (3.''2 diameter) magnitudes for point sources, are roughly 23.9, 25.1, 24.6, 24.1, and 22.8 AB magnitudes in the five bands, respectively. They are 1.9-2.2 mag deeper than the best SDSS single-epoch data. The co-added images have good image quality, with an average point-spread function FWHM of ∼1'' in the r, i, and z bands. We also release object catalogs that were made with SExtractor. These co-added products have many potential uses for studies of galaxies, quasars, and Galactic structure. We further present and release near-IR J-band images that cover ∼90 deg{sup 2} of Stripe 82. These images were obtained using the NEWFIRM camera on the NOAO 4 m Mayall telescope, and have a depth of about 20.0-20.5 Vega magnitudes (also 5σ detection limits for point sources)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Surrogate multi-fidelity data and model fusion for scientific discovery and uncertainty quantification in Earth System Models

This whitepaper addresses the Earth and Environmental Systems Sciences Division (EESSD)’s predictability challenges in modeling the integrated water cycle and data-model integration. Specifically, it focuses on reducing and characterizing the uncertainty in the representation of process models for unresolved physics, either due to model resolution or limited by the physical under standing or computational efficiency, and the use of observational data for in-situ process parameter optimization within ESM. The described methods may also be used to determine the nature of responses (e.g. strength and direction), and hence to identify critical processes that drive the overall ESM responses to perturbation in the forcing

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dynamically Downscaled (WRF) 1km, Hourly Meteorological Conditions 1987-2020. East/Taylor Watersheds

This dataset contains meteorological output from the Weather Research and Forecasting (WRF) version 3.8.1. This dataset has been created to 1) investigate hydrometeorological processes impacting the East River and water-delivery to the Critical Zone, and 2) provide meteorological forcing data for distributed Earth-science modeling applications in the East River watershed. Variables have a 1 kilometer spatial resolution and hourly temporal resolution and encompass a rectangular region encompassing the East and Taylor River watersheds, Colorado, near the town of Crested Butte. WRF was forced using Climate Forecast System Reanalysis (CFSR) lateral boundary conditions. Each .zip file contains one "water year" of data (October 1 -- September 30; i.e. water year 2017 starts October 1, 2016 and ends September 30, 2017). Each zip folder contains 12 netcdf (.nc) files containing one month of hourly data each and are approximately 250mb. Model timestamps are in UTC time.The files contain the following data variables:EAST_MASK: binary mask of the watershed regionTAYLOR_MASK: binary mask of the watershed regionGLW downwelling longwave radiation (w/m2)HR_PRCP: Hourly Precipitation Rate (mm/hr). Includes all hydrometeors (solid+liquid). HFX NoahMP LSM total grid-cell modelled sensible heat flux (w/m2) [positive towards atmosphere]LH NoahMP LSM total grid-cell modelled latent heat flux (w/m2) [positive towards atmosphere; can be converted to ET]PSFC Surface Barometric Pressure (hPa)Q2 Two-meter specific humidity (kg/kg)SWDOWN Downwelling shortwave solar radiation (w/m2)SWNORM Terrain-normal downwelling shortwave radiation (w/m2)T2 Two-meter air temperature (deg K)U10 10-m U-component of wind velocity (m/s)V10 10m V-component of wind velocity (m/s)XLAT Latitude of grid-center point XLONG Longitude of grid-center point XTIME Model timestamp, **in UTC**

54 ENVIRONMENTAL SCIENCES↗