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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Investigation Into the Use of Satellite Data in Aiding Characterization of Particulate Air Quality in the Atlanta, Georgia Metropolitan Area

Poor air quality episodes occur often in metropolitan Atlanta, Georgia. The primary focus of this research is to assess the capability of satellites as a tool in characterizing air quality in Atlanta. Results indicate that intra-city PM2.5 concentrations show similar patterns as other U.S. urban areas, with the highest concentrations occurring within the city. Both PM2.5 and MODIS AOD show more increases in the summer than spring, yet MODIS AOD doubles in the summer unlike PM2.5. A majority of OMI AI is below 0.5. Using this value as an ambient measure of carbonaceous aerosols in the urban area, aerosol transport events can be identified. Our results indicate that MODIS AOD is well correlated with PM2.5 on a yearly and seasonal basis with correlation coefficients as high as 0.8 for Terra and 0.7 for Aqua. A possible alternative view of the PM2.5 and AOD relationship is seen through the use of AOD thresholds. These probabilistic thresholds provide a means to describe the AQI through the use of past AOD for a specific area. We use the NAAQS to classify the AOD into different AQI codes, and probabilistically determine thresholds of AOD that represent the majority of a specific AQI category. For example, the majority 80% of moderate AQI days have AOD values between 0.5 - 0.6. The development of thresholds could be a tool used to evaluate air quality from the use of satellites in regions where there are sparse ground-based measurements of PM2.5.

Alston, Erica J.↗
NASA NTRSDate not supplied

NASA Exploration Toilet On-orbit Results and Impact on Future Missions

The Universal Waste Management System (UWMS), which has the ISS operational nomenclature “Toilet”, was initially installed on the International Space Station (ISS) in 2020 with final installation completed in 2021. Technical progress continued to be made with each on-orbit operation that culminated in additional crew use of the UWMS on ISS. Additional problems were evaluated during troubleshooting and testing with the UWMS hardware using water and pretreat to simulate crew use. This paper summarizes the additional testing, troubleshooting and the results as well as characterizes the additional data obtained and summarizes the interpretation of the data to characterize the hardware’s operational nuances. Use of the hardware by crew is planned and will also be summarized. The paper will also describe the additional portions of the technology demonstration that were completed and the benefits that inform the Orion-installed UWMS unit and future manifesting of consumables for both Orion and ISS.

toilet↗
NASA NTRSDate not supplied

NASA Exploration Toilet on-Orbit Results and Impact on Future Missions

The Universal Waste Management System (UWMS), which has the ISS operational nomenclature “Toilet”, was initially installed on the International Space Station (ISS) in 2020 with final installation completed in 2021. Technical progress continued to be made with each on-orbit operation that culminated in additional crew use of the UWMS on ISS. Additional problems were evaluated during troubleshooting and testing with the UWMS hardware using water and pretreat to simulate crew use. This paper summarizes the additional testing, troubleshooting and the results as well as characterizes the additional data obtained and summarizes the interpretation of the data to characterize the hardware’s operational nuances. Use of the hardware by crew is planned and will also be summarized. The paper will also describe the additional portions of the technology demonstration that were completed and the benefits that inform the Orion-installed UWMS unit and future manifesting of consumables for both Orion and ISS.

toilet↗
NASA NTRSDate not supplied

NASA Exploration Toilet on-Orbit Results and Impact on Future Missions

The Universal Waste Management System (UWMS), which has the ISS operational nomenclature “Toilet”, was initially installed on the International Space Station (ISS) in 2020 with final installation completed in 2021. Technical progress continued to be made with each on-orbit operation that culminated in additional crew use of the UWMS on ISS. Additional problems were evaluated during troubleshooting and testing with the UWMS hardware using water and pretreat to simulate crew use. This paper summarizes the additional testing, troubleshooting and the results as well as characterizes the additional data obtained and summarizes the interpretation of the data to characterize the hardware’s operational nuances. Use of the hardware by crew is planned and will also be summarized. The paper will also describe the additional portions of the technology demonstration that were completed and the benefits that inform the Orion-installed UWMS unit and future manifesting of consumables for both Orion and ISS.

toilet↗
NASA NTRSDate not supplied

NASA Exploration Toilet on-Orbit Results and Impact on Future Missions

The Universal Waste Management System (UWMS), which has the ISS operational nomenclature “Toilet”, was initially installed on the International Space Station (ISS) in 2020 with final installation completed in 2021. Technical progress continued to be made with each on-orbit operation that culminated in additional crew use of the UWMS on ISS. Additional problems were evaluated during troubleshooting and testing with the UWMS hardware using water and pretreat to simulate crew use. This paper summarizes the additional testing, troubleshooting and the results as well as characterizes the additional data obtained and summarizes the interpretation of the data to characterize the hardware’s operational nuances. Use of the hardware by crew is planned and will also be summarized. The paper will also describe the additional portions of the technology demonstration that were completed and the benefits that inform the Orion-installed UWMS unit and future manifesting of consumables for both Orion and ISS.

toilet↗
DOE OSTI2018

Characterizing Time Series Data Diversity for Wind Forecasting: Preprint

Wind forecasting plays an important role in integrating variable and uncertain wind power into the power grid. Various forecasting models have been developed to improve the forecasting accuracy. However, it is challenging to accurately compare the true forecasting performances from different methods and forecasters due to the lack of diversity in forecasting test datasets. This paper proposes a time series characteristic analysis approach to visualize and quantify wind time series diversity. The developed method first calculates six time series characteristic indices from various perspectives. Then the principal component analysis is performed to reduce the data dimension while preserving the important information. The diversity of the time series dataset is visualized by the geometric distribution of the newly constructed principal component space. The volume of the 3-dimensional (3D) convex polytope (or the length of 1D number axis, or the area of the 2D convex polygon) is used to quantify the time series data diversity. The method is tested with five datasets with various degrees of diversity.

17 WIND ENERGY↗
DOE OSTI2019

Replication Data for: Nanoscale crystallographic characterization of nanoporous catalyst by TKD

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A guide to the BRAIN Initiative Cell Census Network data ecosystem

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

PIMS Real-Time Data Reception and Environment Characterization

The methodology and system concepts developed by the PI Microgravity Services (PIMS) project to process real-time ISS microgravity acceleration data will be presented. The characterization of these data and analyses into information meaningful to microgravity scientists will also be described.

McPherson, Kevin M.↗
NASA NTRS2005

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Quattrochi, Dale A.↗