SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Cost analysis and technical feasibility data are presented on five medium orbiting and six geosynchronous satellite data collection systems with varying degrees of spacecraft and local user terminal complexity. Data are also provided on system approaches, user requirements, and user classes. Systems considered include orbiting ERTS and EOS type satellites and geosynchronous SmS and SEOS type data collectors.
Early stage experimental data in structural biology is generally unmaintained and inaccessible to the public. It is increasingly believed that this data, which forms the basis for each macromolecular structure discovered by this field, must be archived and, in due course, published. Furthermore, the widespread use of shared scientific facilities such as synchrotron beamlines complicates the issue of data storage, access and movement, as does the increase of remote users. This work describes a prototype system that adapts existing federated cyberinfrastructure technology and techniques to significantly improve the operational environment for users and administrators of synchrotron data collection facilities used in structural biology. This is achieved through software from the Virtual Data Toolkit and Globus, bringing together federated users and facilities from the Stanford Synchrotron Radiation Lightsource, the Advanced Photon Source, the Open Science Grid, the SBGrid Consortium and Harvard Medical School. The performance and experience with the prototype provide a model for data management at shared scientific facilities.
This data package is associated with the publication “Radiative impact of record-breaking wildfires from integrated ground-based data” submitted to Nature Scientific Reports (Kassianov et al., 2024). Data from ground-based measurements of shortwave and spectrally resolved irradiance and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges were assessed to quantify the radiative impact of the September 2020 wildfires that occurred in the Western United States. Data were collected in September 2020 by several ground-based instruments at the Atmospheric Measurements Laboratory (AML) located in Richland, Washington (46.3451, -119.2792). These data include (1) Aerosol Optical Depth (AOD); (2) spectrally resolved and shortwave (SW) irradiances; (3) backscatter profiles; (4) total sky images; and (5) near-surface ambient air temperatures.The data package consists of five sub-directories: (1) “AML_Ceilometer_”; (2)” AML_CSPHOT_”; (3) “AML_MFRSR_irradiances_”; (4) “AML_SW_irradiances_and_Temp_”; (5) “AML_TSI_images_”; and 6 files stored at the directory level, including the readme, file-level metadata file, and data dictionary. The file-level metadata file (the file ending in “_flmd.csv”) lists all files contained in this data package and descriptions for each. The data dictionary (the file ending in “_dd.csv”) describes each tabular column header’s unit, definition, and structure. Below are descriptions of each sub-directory:“AML_Ceilometer_” includes ceilometer data collected at the AML. These files contain the corresponding narratives of data. Details related to the ceilometer data can be found in Morris (2016). “AML_CSPHOT_” includes ascii files with high-temporal resolution (about 10-15 min) AML CSPHOT data and their daily-averaged counterparts. These two files contain the corresponding narratives of data. Details related to the CSPHOT data can be found in Gregory (2011). “AML_MFRSR_irradiances_” includes ascii files with the AML MFRSR-measured diffuse, normal, and total spectrally resolved irradiance. Details related to the MFRSR data can be found in Hodges and Michalsky (2016) and Koontz et al. (2013). “AML_SW_irradiances_+_Temp_” includes near-surface ambient air temperature and SW irradiances, namely direct normal, diffuse hemispherical, and total hemispheric (global), measured at the AML. These files also incorporate the corresponding narratives of data. Details related to the SW irradiances can be found in Andreas et al. (2018). “AML_TSI_images_” includes Total Sky Images (TSIs) collected at the AML. Details related to the TSI data can be found in Morris (2005).
Since early 2020, COVID-19 has grown to affect the lives of billions globally. A worldwide investigation has been ongoing for characterizing the virus and also for finding an effective drug and developing vaccines. As time has been of the essence, a crucial part of this research has been drug repurposing; therefore, confirmation of in silico drug screening studies have been carried out for this purpose. Here we demonstrated the possibility of screening a variety of drugs efficiently by leveraging a high data collection rate of 120 images/second with the new low-noise, high dynamic range ePix10k2M Pixel Array Detector installed at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS). The X-ray Free-Electron Laser (XFEL) is used for remote high-throughput data collection for drug repurposing of the main protease (Mpro) of SARS-CoV-2 at ambient temperature with mitigated X-ray radiation damage. We obtained multiple structures soaked with nine drug candidate molecules in two crystal forms. Although our drug binding attempts failed, we successfully established a high-throughput Serial Femtosecond X-ray crystallographic (SFX) data collection protocol.
The author has identified the following significant results. The feasibility of using the data collection system on ERTS-1 to predict wheat leaf rust severity and resulting yield loss was tested. Ground-based data collection platforms (DCP'S), placed in two commercial wheat fields in Riley County, Kansas, transmitted to the satellite such meteorological information as maximum and minimum temperature, relative humidity, and hours of free moisture. Meteorological data received from the two DCP'S from April 23 to 29 were used to estimate the disease progress curve. Values from the curve were used to predict the percentage decrease in wheat yields resulting from leaf rust. Actual decrease in yield was obtained by applying a zinc and maneb spray (5.6 kg/ha) to control leaf rust, then comparing yields of the controlled (healthy) and the noncontrolled (rusted) areas. In each field a 9% decrease in yield was predicted by the DCP-derived data; actual decreases were 12% and 9%.
A method for automated data collection has been developed for a Charpy impact tester. A potentiometer is connected to the pivot point of the hammer and measures the angular displacement of the hammer. This data is collected with a computer and, through appropriate software, accurately records the energy absorbed by the specimen. The device can be easily calibrated with minimal effort.
MASSIF-1 (ID30A-1) is an ESRF undulator beamline operating at a fixed wavelength of 0.969 Å (12.8 keV) that is dedicated to the completely automatic characterization of and data collection from crystals of biological macromolecules. The first of the ESRF Upgrade MASSIF beamlines to be commissioned, it has been open since September 2014, providing a unique automated data collection service to academic and industrial users. Here, the beamline characteristics and details of the new service are outlined.
There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse spatial resolutions.
There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse ~~~iairesolutions.
This report addresses the general data requirements for reliability analysis of fielded wind turbines and other wind plant equipment. The report provides a rationale for why this data should be collected, a list of the data needed to support reliability and availability analysis, and specific data recommendations for a Computerized Maintenance Management System (CMMS) to support automated analysis. This data collection recommendations report was written by Sandia National Laboratories to address the general data requirements for reliability analysis of operating wind turbines. This report is intended to help develop a basic understanding of the data needed for reliability analysis from a Computerized Maintenance Management System (CMMS) and other data systems. The report provides a rationale for why this data should be collected, a list of the data needed to support reliability and availability analysis, and specific recommendations for a CMMS to support automated analysis. Though written for reliability analysis of wind turbines, much of the information is applicable to a wider variety of equipment and analysis and reporting needs. The 'Motivation' section of this report provides a rationale for collecting and analyzing field data for reliability analysis. The benefits of this type of effort can include increased energy delivered, decreased operating costs, enhanced preventive maintenance schedules, solutions to issues with the largest payback, and identification of early failure indicators.
The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.
The Software Engineering Laboratory was monitoring software development at NASA Goddard Space Flight Center since 1976. The data collection activities of the Laboratory and some of the difficulties of obtaining reliable data are described. In addition, the application of this data collection process to a current prototyping experiment is reviewed.
Discussion of future meteorological satellite data collection system consisting of automatic land, sea and balloon relay weather stations
The author has identified the following significant results. This experiment was, and continues to be, an integration of the LANDSAT-DCS with the data collection and processing system of the Geological Survey. Although an experimental demonstration, it was a successful integration of a satellite relay system that is capable of continental data collection, and an existing governmental nationwide operational data processing and distributing networks. The Survey's data processing system uses a large general purpose computer with insufficient redundancy for 24-hour a day, 7 day a week operation. This is significant, but soluble obstacle to converting the experimental integration of the system to an operational integration.
Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.
Viewgraphs on preprocessing data collected with the ACTS propagation terminal are presented. The steps in ACTS data preprocessing are reviewed.
Advances in sensors and robotics have dramatically improved the diversity of experimental approaches available to the materials community. Autonomous data collection platforms, either custom-made or commercially available, provide researchers with novel tools with which to probe materials behavior and perform advanced materials characterization. The application of novel control algorithms and active learning approaches can create much more robust experimental data, or can be used to improve the performance of existing characterization tools. Five papers within this special topic focus on experimental and computational methodologies for use in automatic data collection routines for materials characterization. From novel platforms for materials discovery to new statistical frameworks for assessing the autonomous experimentation process, these five papers highlight the diverse range of applications of automation for advancing materials science.
The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of ammonium nitrate (AN). AN was tested, in most cases, as both received from manufacturer and dried/sieved. The participants found the AN to be: 1) insensitive in Type 12A impact testing (although with a wide range of values), 2) completely insensitive in BAM friction testing, 3) less sensitive than the RDX standard in ABL friction testing, 4) less sensitive than RDX in ABL ESD testing, and 5) less sensitive than RDX and PETN in DSC thermal analyses.