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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ultrastructural Location and Interactions of the Immunoglobulin Receptor Binding Sequence within Fibrillar Type I Collagen

Collagen type I is a major constituent of animal bodies. It is found in large quantities in tendon, bone, skin, cartilage, blood vessels, bronchi, and the lung interstitium. It is also produced and accumulates in large amounts in response to certain inflammations such as lung fibrosis. Our understanding of the molecular organization of fibrillar collagen and cellular interaction motifs, such as those involved with immune-associated molecules, continues to be refined. In this study, antibodies raised against type I collagen were used to label intact D-periodic type I collagen fibrils and observed with atomic force microscopy (AFM), and X-ray diffraction (XRD) and immunolabeling positions were observed with both methods. The antibodies bind close to the C-terminal telopeptide which verifies the location and accessibility of both the major histocompatibility complex (MHC) class I (MHCI) binding domain and C-terminal telopeptide on the outside of the collagen fibril. The close proximity of the C-telopeptide and the MHC1 domain of type I collagen to fibronectin, discoidin domain receptor (DDR), and collagenase cleavage domains likely facilitate the interaction of ligands and receptors related to cellular immunity and the collagen-based Extracellular Matrix.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Comparison of Infectious Disease Forecasting Methods across Locations, Diseases, and Time

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate adverse impacts. This study compares the performance of statistical, machine learning (ML), and deep learning (DL) approaches in forecasting infectious disease incidences across different countries and time intervals. We forecasted three diverse diseases: campylobacteriosis, typhoid, and Q-fever, using a wide variety of features (n = 46) from public datasets, e.g., landscape, climate, and socioeconomic factors. We compared autoregressive statistical models to two tree-based ML models (extreme gradient boosted trees [XGB] and random forest [RF]) and two DL models (multi-layer perceptron and encoder–decoder model). The disease models were trained on data from seven different countries at the region-level between 2009–2017. Forecasting performance of all models was assessed using mean absolute error, root mean square error, and Poisson deviance across Australia, Israel, and the United States for the months of January through August of 2018. The overall model results were compared across diseases as well as various data splits, including country, regions with highest and lowest cases, and the forecasted months out (i.e., nowcasting, short-term, and long-term forecasting). Overall, the XGB models performed the best for all diseases and, in general, tree-based ML models performed the best when looking at data splits. There were a few instances where the statistical or DL models had minutely smaller error metrics for specific subsets of typhoid, which is a disease with very low case counts. Feature importance per disease was measured by using four tree-based ML models (i.e., XGB and RF with and without region name as a feature). The most important feature groups included previous case counts, region name, population counts and density, mortality causes of neonatal to under 5 years of age, sanitation factors, and elevation. This study demonstrates the power of ML approaches to incorporate a wide range of factors to forecast various diseases, regardless of location, more accurately than traditional statistical approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Systemwide Considerations for Electrification of Transportation in Islands and Remote Locations

Electric vehicles (EVs) represent an important socio-economic development opportunity for islands and remote locations because they can lead to reduced fuel imports, electricity storage, grid services, and environmental and health benefits. This paper presents an overview of opportunities, challenges, and examples of EVs in islands and remote power systems, and is meant to provide background to researchers, utilities, energy offices, and other stakeholders interested in the impacts of electrification of transportation. The impact of uncontrolled EV charging on the electric grid operation is discussed, as well as several mitigation strategies. Of particular importance in many islands and remote systems is taking advantage of local resources by combining renewable energy and EV charging. Policy and economic issues are presented, with emphasis on the need for an overarching energy policy to guide the strategies for EVs growth. The key conclusion of this paper is that an orderly transition to EVs, one that maximizes benefits while addressing the challenges, requires careful analysis and comprehensive planning.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Influence of covariance of aerosol and meteorology on co-located precipitating and non-precipitating clouds over the Indo-Gangetic Plain

Aerosol–cloud–precipitation interaction (ACPI) plays a pivotal role in the global and regional water cycle and the earth's energy budget; however, it remains highly uncertain due to the different underlying physical mechanisms. Therefore, this study aims to systematically analyze the effects of aerosols and meteorological factors on ACPI in the co-located precipitating clouds (PCs) and non-precipitating clouds (NPCs) in winter and summer seasons by employing the long-term (2001–2021) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) coupled with the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-II datasets over the Indo-Gangetic Plain (IGP). The results exhibit a decadal increase in aerosol optical depth (AOD) over Lahore (5.2 %), Delhi (9 %), Kanpur (10.7 %), and Gandhi College (22.7 %) and a decrease over Karachi (-1.9 %) and Jaipur (-0.5 %). The most stable meteorology with high values of lower-tropospheric stability (LTS) is found in both seasons over Karachi. In the summer season, the occurrence frequency of clouds is high (74 %) over Gandhi College, 60 % of which are PCs. Conversely, the lowest number of PCs is found over Karachi. Similarly, in the winter season, the frequency of cloud occurrence is low over Karachi and high over Lahore and Gandhi College. The analysis of cloud top pressure (CTP) and cloud optical thickness (COT) indicates high values of cloud fraction (CF) for thick and high-level clouds over all study areas except Karachi. The microphysical properties such as cloud effective radius (CER) and cloud droplet number concentration (CDNC) bear high values (CER ≳ 15 µm and CDNC ≳ 50 cm -3 ) for both NPCs and PCs in summer. The AOD–CER correlation is good (weak) for PCs (NPCs) in winter. Similarly, the sensitivity value of the first indirect effect (FIE) is high (ranging from 0.2 ± 0.13 to 0.3 ± 0.01 in winter and from 0.19 ± 0.03 to 0.32 ± 0.05 in summer) for PCs and low for NPCs. The sensitivity value for the second indirect effect (SIE) is relatively higher (such as 0.6 ± 0.14 in winter and 0.4 ± 0.04 in summer) than FIE. Sensitivity values of the aerosol-cloud interaction (ACI) are low (i.e., -0.06 ± 0.09) for PCs in summer. Furthermore, the precipitation rate (PR) exhibits high values in the summer season, primarily due to the significant contribution from optically thick clouds with lower CDNC (≲ 50 cm -3 ) and larger CER and the intermediate contribution from optically thick clouds with higher CDNC ( ≳ 50 cm -3 ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Electric Grid Visualization: Hourly Renewable Generation, Load, Unserved Load, and Locational Marginal Prices during a Heatwave

Visualization of hourly solar and wind generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018, 2058, and 2098. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided.

Climate Change↗
DOE OSTI2025

CERF Visualization: Projected locations of new natural gas combined cycle power plants (with recirculating cooling) in Wyoming, USA (2020-2050)

Visualization of CERF outputs for years 2030-2050 in 5-year time steps for a region in Wyoming, USA. This visualization was built using a custom CesiumJS application. The region of interest was zoomed into and then the app shows the layered application of natural gas combined cycle power plants (with recirculating cooling) suitability criteria, show the siting for each year in planform, simulates the selection of a site using Net Locational Cost, and then zooms into to show a single functional gas plant and simulates its connection to the grid.

CERF↗
DOE OSTI2025

Electric Grid Visualization: Hourly Generation, Load, Unserved Load, and Locational Marginal Prices during a 2018 Heatwave

Visualization of hourly generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided as well as a county-level choropleth map of temperature.

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2020

Electrically conductive proppant and methods for detecting, locating and characterizing the electrically conductive proppant

Electrically conductive proppants and methods for detecting, locating, and characterizing same are provided. The electrically conductive proppant can include a substantially uniform coating of an electrically conductive material having a thickness of at least 500 nm. The method can include injecting a hydraulic fluid into a wellbore extending into a subterranean formation at a rate and pressure sufficient to open a fracture therein, injecting into the fracture a fluid containing the electrically conductive proppant, electrically energizing the earth at or near the fracture, and measuring three dimensional (x, y, and z) components of electric and magnetic field responses at a surface of the earth or in an adjacent wellbore.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Locating node of named data elements in coordination namespace

An approach is disclosed that locates a named data element by a local node. A name corresponding to the named data element is received, the named data element exists in a Coordination Namespace allocated in a memory area that is distributed amongst a set of nodes that include the local node and remote nodes. A predicted node identifier is received and then the named data element is requested from the predicted node based on the predicted node identifier.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Transforming Energy through Computational Excellence. Exascale Computing: Combustion; Simulating Effects of Fuel Injection Location in Supersonic Jet Engines

Computational tractable simulations using an adaptive-mesh-refinement solverfor compressible reacting flows help researchers understand how variations in fuel injection location within the supersonic flow cavity impacts combustion efficiency. By identifying the important physical determinants of the combustion processes, this study shows a promising pathway to improving flame stability and combustion efficiency, as well as reducing emissions.

adaptive mesh refinement↗
DOE OSTI2021

Electrically conductive proppant and methods for detecting, locating and characterizing the electrically conductive proppant

Electrically conductive proppants and methods for detecting, locating, and characterizing same are provided. The electrically conductive proppant can include a substantially uniform coating of an electrically conductive material having a thickness of at least 500 nm. The method can include injecting a hydraulic fluid into a wellbore extending into a subterranean formation at a rate and pressure sufficient to open a fracture therein, injecting into the fracture a fluid containing the electrically conductive proppant, electrically energizing the earth at or near the fracture, and measuring three dimensional (x, y, and z) components of electric and magnetic field responses at a surface of the earth or in an adjacent wellbore.

Cannan, Chad↗
DOE OSTI2022

An Acoustic Transmitter with Intelligent ON/OFF Mechanisms and Quasi-location Awareness

We successfully demonstrated an acoustic transmitter with intelligent ON/OFF mechanisms and quasi-location awareness. The prototype transmitter has (1) the ability (radio frequency-enabled ON/OFF) to turn the tag on and off when it passes through a passive integrated transponder antenna and (2) the ability to detect significant salinity changes (i.e. from freshwater to sea water and vice versa) and turn itself off and on, respectively. Such a device would greatly enhance the capabilities of the acoustic telemetry-based fish tracking systems.

Deng, Zhiqun↗
DOE OSTI2024

Downscaling Synthetic Populations to Realistic Residential Locations

High-fidelity pattern of life (PoL) models require realistic origin points for predictive trip modeling. This paper develops and demonstrates a reproducible method using open data to match synthetic populations generated from census surveys to plausible residential locations (building footprints) based on housing attributes. This approach presents promise over extant methods based on housing density, particularly in small neighborhood areas with heterogeneous land-use.

Tuccillo, Joe↗
DOE OSTI2023

Charging location selection of an incoming electric vehicle for large EV depot infrastructure

As the use of renewable energy resources increases within charging infrastructures, the risk that charging an additional load within the charging infrastructure will create a violation of the applicable grid code also increases. In an embodiment, a charging location is selected for an incoming load based on a load flow analysis, to thereby mitigate the risk of a violation. This selection process may also account for the charging schedule of the load and the capacity of available charging stations (e.g., fast charging vs. slow charging).

Hafiz, Faeza↗
DOE OSTI2024

Locating Equitable Solar Opportunities by Census Tract: A Guide to the Screening Tool for Equitable Adoption and Deployment of Solar (STEADy Solar)

The Screening Tool for Equitable Adoption and DeploYment of Solar (STEADy Solar) is a database and mapping tool that indicates locations that may be eligible for the Investment Tax Credit bonus adders defined in the 2022 Inflation Reduction Act (IRA). The tool combines publicly available information on demographics, solar technical potential, solar economics (modeled net present value), building counts by use-type, and eligibility for tax credit adders. It can be used by states, municipalities, community-based organizations, developers, and researchers to identify sites where solar projects may be economical and where federal incentives may be available to support equitable adoption of solar. This report describes the STEADy dataset and presents high level insights from the data.

census tract↗
DOE OSTI2024

From Resilient and Ready to Used and Useful: Managing Temporal and Locational Uncertainty in Electrification, DER Adoption, and Climate Adaptation

Grid planning decisions involve weighing risks against benefits. The best decisions will facilitate development of electrical infrastructure that minimizes risk and maximizes benefits. With the rapidly evolving energy landscape, today's planner must discern new loads and demand cycles; embrace the operational complexity of climate risk; revise settled standards; and anticipate and manage the system impacts of distributed energy resource (DER) adoption. Only by managing the combined uncertainty of these dynamic processes can a planner hope to make effective decisions. Our analysis focuses on the management of temporal and locational uncertainty, and particularly on the risks presented to customers by the mismanagement of the factors that are the sources of these uncertainties.

climate↗