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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Electron density and energetic particle precipitation observed during the eclipse of 26 February 1979

Electron density profiles and energetic particle fluxes are obtained based on data collected by two rockets launched from Red Lake, Ontario, respectively, at the beginning and end of totality during the solar eclipse of February 26, 1979. Data obtained by a rocket launched on February 24, 1979 showed that the electron density was normal (at 10,000 cu cm) above 110 km, to rocket apogee (130.5 km). Below 110 km, the electron density was found to be enhanced compared with data from Wallops Island at the same solar zenith angle (63 deg). It is proposed that this enhancement was due to the large flux of field-aligned energetic particles observed on the same rocket. The electron density above 110 km to rocket apogee (132.6 and 132. 3 km) was found to be reduced during totality by a factor of about three. However, below 110 km, the electron density was found to be much greater than observed during previous eclipses, probably due to the additional ionization resulting from energetic particles. The particle flux measured on February 26 was found to be an order of magnitude less than on February 24 but showed greater variability, particularly at the higher energies (100 keV).

Smith, L. G.↗
NASA NTRS2023

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Carl Malings↗
NASA NTRSDate not supplied

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Nathan R. Pavlovic↗
DOE OSTI2024

Using data-science approaches to unravel insights for enhanced transport of lithium ions in single-ion conducting polymer electrolyte

Solid polymer electrolytes have yet to achieve the an ionic conductivity > 1 mS/cm at room temperature for realistic applications. This target implies the need to reduce the effective energy barriers of ion transport in polymer electrolytes to around 20 kJ/mol. In this work, we combine information extracted from existing experimental results with theoretical calculations to provide insights into ion transport in single-ion conductors (SICs) with a focus on lithium ion SICs. Through the analysis of temperature-dependent ionic conductivity data obtained from the literature, we evaluate different methods of extracting energy barriers for lithium transport. The traditional Arrhenius fit to the temperature-dependent ionic conductivity data indicates that the Meyer-Neldel rule holds for SICs. However, the values of the fitting parameters remain unphysical. Our modified approach based on recent work (Macromolecules, 56, 15, 6051(2023)), which incorporates a fixed pre-exponential factor, reveals that the energy barriers exhibit temperature dependence over a wide range of temperatures. Using this approach, we identify a series of anions leading to the energy barriers less than 30 kJ/mol, which include trifluoromethane sulfonimide (TFSI), fluoromethane sulfonimide (FSI), and boron-based organic anions. In our efforts to design the next generation of anions, which can exhibit the energy barriers less than 20 kJ/mol, we focused on boron-containing SICs, and performed density functional theory (DFT) based calculations to connect the chemical structures via the binding energy of cation (lithium)-anion pairs with the experimentally derived effective energy barriers for ion transport. Not only have we identified a correlation between the binding energy and the energy barriers, but we also propose a strategy to design new boron-based anions by using the correlation. This combined approach involving experiments and theoretical calculations is capable of facilitating the identification of promising new anions, which can exhibit ionic conductivity $> 1$ mS/cm near room temperature, thereby expediting the development of novel superionic single-ion conducting polymer electrolytes. The published datasets include all the temperature-dependent ionic conductivity collected from the literature with literature DOIs, DFT calculated binding energies, and python scripts to analyze data, construct statistical models, and generate plots.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Using Data-Science Approaches to Unravel Insights for Enhanced Transport of Lithium Ions in Single-Ion Conducting Polymer Electrolytes

Solid polymer electrolytes have yet to achieve the desired ionic conductivity (>1 mS/cm) near room temperature required for many applications. This target implies the need to reduce the effective energy barriers for ion transport in polymer electrolytes to around 20 kJ/mol. In this work, we combine information extracted from existing experimental results with theoretical calculations to provide insights into ion transport in single-ion conductors (SICs) with a focus on lithium ion SICs. Through the analysis of temperature-dependent ionic conductivity data obtained from the literature, we evaluate different methods of extracting energy barriers for lithium transport. The traditional Arrhenius fit to the temperature-dependent ionic conductivity data indicates that the Meyer–Neldel rule holds for SICs. However, the values of the fitting parameters remain unphysical. Our modified approach based on recent work (Macromolecules 2023, 56, 15, 6051), which incorporates a fixed pre-exponential factor, reveals that the energy barriers exhibit temperature dependence over a wide range of temperatures. Using this approach, we identify anions leading to the energy barriers <30 kJ/mol, which include trifluoromethane sulfonimide (TFSI), fluoromethane sulfonimide (FSI), and boron-based organic anions. In our efforts to design the next generation of anions, which can exhibit the energy barriers <20 kJ/mol, we have performed density functional theory (DFT) based calculations to connect the chemical structures of boron-based anions via the binding energy of cation (lithium)-anion pairs with the experimentally derived effective energy barriers for ion hopping. Not only have we identified a correlation between the binding energy and the energy barriers, but we also propose a strategy to design new boron-based anions by using the correlation. This combined approach involving experiments and theoretical calculations is capable of facilitating the identification of promising new anions, which can exhibit ionic conductivity >1 mS/cm near room temperature, thereby expediting the development of novel superionic single-ion conducting polymer electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Advanced flip-coil system for magnetic field integral measurements of insertion devices

A novel flip-coil measurement system has been developed for the National Synchrotron Light Source II (NSLS-II) at Brookhaven National Laboratory. This paper describes the design, implementation, and commissioning of the new measurement bench, highlighting its key features, including improved mechanical stability, advanced data acquisition, and enhanced reproducibility. The system enables precise characterization of field integrals and multipole components, ensuring the optimal performance of Insertion Devices (IDs) before installation in the NSLS-II storage ring. The flip-coil system incorporates an innovative approach to minimize mechanical and electrical errors, which significantly improves the reproducibility of measurements. In addition, the system features a state-of-the-art data acquisition system that enables real-time monitoring and analysis, further enhancing the efficiency and accuracy of the measurement process. Furthermore, preliminary tests have demonstrated that the new system meets the stringent requirements for magnetic field characterization of advanced insertion devices, making it an essential tool for future ID commissioning and quality assurance at NSLS-II.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Developments in Test Facility and Data Networking for the Altitude Test Stand at the John C. Stennis Space Center, MS - A General Overview

May 2007, NASA's Constellation Program selected John C Stennis Space Center (SSC) near Waveland Mississippi as the site to construct an altitude test facility for the developmental and qualification testing of the Ares1 upper stage (US) engine. Test requirements born out of the Ares1 US propulsion system design necessitate exceptional Data Acquisition System (DAS) design solutions that support facility and propellant systems conditioning, test operations control and test data analysis. This paper reviews the new A3 Altitude Test Facility's DAS design requirements for real-time deterministic digital data, DAS technology enhancements, system trades, technology validation activities, and the current status of this system's new architecture. Also to be discussed will be current network technologies to improve data transfer.

Hebert, Phillip W., Sr.↗
NASA NTRS2012

Use of Statistical Analysis of Acoustic Emission Data on Carbon-Epoxy COPV Materials-of-Construction for Enhanced Felicity Ratio Onset Determination

Broadband modal acoustic emission (AE) data were acquired during intermittent load hold tensile test profiles on Toray T1000G carbon fiber-reinforced epoxy (C/Ep) single tow specimens. A novel trend seeking statistical method to determine the onset of significant AE was developed, resulting in more linear decreases in the Felicity ratio (FR) with load, potentially leading to more accurate failure prediction. The method developed uses an exponentially weighted moving average (EWMA) control chart. Comparison of the EWMA with previously used FR onset methods, namely the discrete (n), mean (n (raised bar)), normalized (n%) and normalized mean (n(raised bar)%) methods, revealed the EWMA method yields more consistently linear FR versus load relationships between specimens. Other findings include a correlation between AE data richness and FR linearity based on the FR methods discussed in this paper, and evidence of premature failure at lower than expected loads. Application of the EWMA method should be extended to other composite materials and, eventually, composite components such as composite overwrapped pressure vessels. Furthermore, future experiments should attempt to uncover the factors responsible for infant mortality in C/Ep strands.

Abraham, Arick Reed A.↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2024

TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems

Deep learning (DL), in particular deep neural networks, by default is purely data-driven and in general does not require physics. This is the strength of DL but also one of its key limitations when applied to science and engineering problems in which underlying physical properties—such as stability, conservation, and positivity—and accuracy are required. DL methods in their original forms are often not capable of respecting the underlying mathematical models or achieving desired accuracy even in big-data regimes. On the other hand, many data-driven science and engineering problems, such as inverse problems, typically have limited experimental or observational data, and DL would overfit the data in this case. Leveraging information encoded in the underlying mathematical models, we argue, not only compensates for missing information in low data regimes but also provides opportunities to equip DL methods with the underlying physics, hence promoting better generalization. This paper develops a model-constrained DL approach and its variant TNet—a Tikhonov neural network—which are capable of learning not only information hidden in the training data but also in the underlying mathematical models to solve inverse problems governed by partial differential equations in low data regimes. We provide the constructions and some theoretical results for the proposed approaches for both linear and nonlinear inverse problems. Since TNet is designed to learn inverse solutions with Tikhonov regularization, it is interpretable: in fact it recovers Tikhonov solutions for linear cases while potentially approximating Tikhonov solutions for nonlinear inverse problems. We also prove that data randomization can enhance not only the smoothness of the networks but also their generalizations. Comprehensive numerical results confirm the theoretical findings and show that with even as little as 1 training data sample for one-dimensional (1D) deconvolution, 5 for an inverse 2D heat conductivity problem, 100 for inverse initial conditions for a time-dependent 2D Burgers’s equation, and 50 for inverse initial conditions for 2D Navier–Stokes equations, TNet solutions can be as accurate as Tikhonov solutions while being several orders of magnitude faster. Furthermore, this is possible owing to the model-constrained term, replications, and randomization.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

The structure and dynamics of mesoscale systems influencing severe thunderstorm development during AVE/SESAME 1

Relationships between meso-beta scale systems and thunderstorm formation were examined as part of the NASA atmospheric variability experiment/severe environmental storms and mesoscale experiment 1979. The McIdas program was employed for meso-beta scale analyses of atmospheric structure and dynamics in kinematic computations of the Abilene Triangle on a grid mesh of 100 km for station spacing of 275 km. Mesoscale short wave systems were detected imbedded and propagating cyclonically around upper-level vortex circulation and creating environmental conditions conducive to thunderstorm development. TIROS-N and GOES satellite data served to connect the systems with two convective storms which developed. The necessity to use spaceborne instrumentation carried on the Shuttle or on free-flying satellites for enhancing the data-base on storm development is noted.

Wilson, G. S.↗
NASA NTRS2003

Diffusion of Siderophile Elements in Fe Metal: Application to Zoned Metal Grains in Chondrites

The distribution of highly siderophile elements (HSE) in planetary materials is controlled mainly by metal. Diffusion processes can control the distribution or re-distribution of these elements within metals, yet there is little systematic or appropriate diffusion data that can be used to interpret HSE concentrations in such metals. Because our understanding of isotope chronometry, redox processes, kamacite/taenite-based cooling rates, and metal grain zoning would be enhanced with diffusion data, we have measured diffusion coefficients for Ni, Co, Ga, Ge, Ru, Pd, Ir and Au in Fe metal from 1200 to 1400 C and 1 bar and 10 kbar. These new data on refractory and volatile siderophile elements are used to evaluate the role of diffusional processes in controlling zoning patterns in metal-rich chondrites.

Righter, K.↗
NASA NTRS1994

TOPS On-Line: Automating the Construction and Maintenance of HTML Pages

After the Technology Opportunities Showcase (TOPS), in October, 1993, Langley Research Center's (LaRC) Information Systems Division (ISD) accepted the challenge to preserve the investment in information assembled in the TOPS exhibits by establishing a data base. Following the lead of several people at LaRC and others around the world, the HyperText Transport Protocol (HTTP) server and Mosaic were the obvious tools of choice for implementation. Initially, some TOPS exhibitors began the conventional approach of constructing HyperText Markup Language (HTML) pages of their exhibits as input to Mosaic. Considering the number of pages to construct, a better approach was conceived that would automate the construction of pages. This approach allowed completion of the data base construction in a shorter period of time using fewer resources than would have been possible with the conventional approach. It also provided flexibility for the maintenance and enhancement of the data base. Since that time, this approach has been used to automate construction of other HTML data bases. Through these experiences, it is concluded that the most effective use of the HTTP/Mosaic technology will require better tools and techniques for creating, maintaining and managing the HTML pages. The development and use of these tools and techniques are the subject of this document.

Jones, Kennie H.↗
DOE OSTI2025

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2016

The Model Intercomparison Project on the Climatic Response to Volcanic Forcing (VolMIP): Experimental Design and Forcing Input Data for CMIP6

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used.

Volcanoes↗
NASA NTRS1980

Application of digital terrain data to quantify and reduce the topographic effect on LANDSAT data

Integration of LANDSAT multispectral scanner (MSS) data with 30 m U.S. Geological Survey (USGS) digital terrain data was undertaken to quantify and reduce the topographic effect on imagery of a forested mountain ridge test site in central Pennsylvania. High Sun angle imagery revealed variation of as much as 21 pixel values in data for slopes of different angles and aspects with uniform surface cover. Large topographic effects were apparent in MSS 4 and 5 was due to a combination of high absorption by the forest cover and the MSS quantization. Four methods for reducing the topographic effect were compared. Band ratioing of MSS 6/5 and MSS 7/5 did not eliminate the topographic effect because of the lack of variation in MSS 4 and 5 radiances. The three radiance models examined to reduce the topographic effect required integration of the digital terrain data. Two Lambertian models increased the variation in the LANDSAT radiances. The nonLambertian model considerably reduced (86 per cent) the topographic effect in the LANDSAT data. The study demonstrates that high quality digital terrain data, as provided by the USGS digital elevation model data, can be used to enhance the utility of multispectral satellite data.

Justice, C. O.↗
NASA NTRS1989

Space Station-era ground data handling

Planning is underway for the handling of the peak return link data rates ranging from 300 to 1200 Mbps that are associated with the emerging Space Station orbital-systems era. Ground data handling services encompass the enhancement of on-board ancilliary data packets to furnish standard calibrations and transformations not available on-board; remote access to an interactive data base will allow users to select and withdraw specified parameters based on user-defined criteria.

Smith, Gene A.↗
NASA NTRS1992

The Earth Observing System

The restructuring of the NASA Earth Observing System (EOS), designed to provide comprehensive long term observations from space of changes occurring on the Earth from natural and human causes in order to have a sound scientific basis for policy decisions on protection of the future, is reported. In response to several factors, the original program approved in the fiscal year 1991 budget was restructured and somewhat reduced in scope. The resulting program uses three different sized launch vehicles to put six different spacecraft in orbit in the first phase, followed by two replacement launches for each of five of the six satellites to maintain a long term observing capability to meet the needs of global climate change research and other science objectives. The EOS system, including the space observatories, the data and information system, and the interdisciplinary global change research effort, are approved and proceeding. Elements of EOS are already in place, such as the research investigations and initial data system capabilities. The flights of precursor satellite and Shuttle missions, the ongoing data analysis, and the evolutionary enhancements to the integrated Earth science data management capabilities are all important building blocks to the full EOS program.

Shaffer, Lisa Robock↗