Design of an advanced satellite receiver for a binary FSK data collection system
UHF satellite receiver for binary FSK data collection system using matched integrate and dump filter detectors
Wishna, S.↗
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Results for “Data Collection”
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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Multispectral data collection and instrumentation studies
Research progress on multispectral data collection and infrared instrumentation for specially configured aircraft
Lowe, D. S.↗
Partial reflection data collection and processing using a small computer
Online data collection of the amplitudes of circularly polarized radio waves, partially reflected from the D region of the earth's ionosphere, has enabled the calculation of an electron-density profile in the height region 60-90 km. A PDP 15/30 digital computer with an analog to digital converter and magnetic tape as an intermediary storage device are used. The computer configuration, the software developed, and the preliminary results are described.
Birley, M. H.↗
Data Collection and Analysis [Slides]
The report summarizes the ongoing data collection as well as selection and analysis of field events based on measurement data from project partners.
14 SOLAR ENERGY↗
Data Collection and Analysis [Slides]
The report summarizes the ongoing data collection as well as selection and analysis of field events based on measurement data from project partners.
14 SOLAR ENERGY↗
INL’s Human Reliability Analysis Data Collection Based on the SHEEP Framework
This presentation introduces INL's human reliability analysis data collection studies.
99 GENERAL AND MISCELLANEOUS↗
A seismic signal processor suitable for use with the NOAA/GOES satellite data collection system
Because of the high data-rate requirements, a practical system capable of collecting seismic information in the field and relaying it, via satellite, to a central collection point is not yet available. A seismic signal processor has been developed and tested for use with the NOAA/GOES satellite data collection system. Performance tests on recorded, as well as real time, short period signals indicate that the event recognition technique used is nearly perfect in its rejection of environmental noise and other non-seismic signals and that, with the use of solid state buffer memories, data can be acquired in many swarm situations. The design of a complete field data collection platform is discussed based on the prototype evaluation.
Webster, W. J., Jr.↗
Novus: An Unmanned Aerial System and Virtual Reality Flight Deck for Data Collection and Visualization
Many emerging technologies offer tremendous new capabilities that will, without question, redefine how we interact with, utilize, understand, and optimize the energy systems around us. Drones offer a new ability to remotely capture data in ways that have previously been impractical. However, their flight control systems remain rudimentary and limit the ability of researchers to fully take advantage of these platforms as remote sensing devices. In this project, we constructed a hexarotor drone and outfitted it with advanced (yet inexpensive) sensors as well as a telemetry data management and control package. We then created a virtual reality flight deck that allows a drone operator to define waypoints "on-the-fly" or take manual control over flight operations. The flight deck provides a live on-board video stream display, a 3-dimensional topographic map with the drone’s position in space overlaid onto it, as well as a data visualization framework that keeps critical information immediately available to the operator. These advances provide a new platform for scientific data collection such as thermography of building envelopes or solar arrays. As the drone is in flight and data are being collected, these data are relayed to the virtual reality environment where they can be inspected for integrity and the flight plan altered if necessary to collect higher quality data. Future work will focus on implementing 3-dimensional mapping using both visible and thermal imagery collected from the drone, and streaming those into the virtual reality flight deck in real time.
Source record↗
Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants
Maintenance activities in the United States nuclear power industry are mainly centered on preventive and corrective maintenance. Predictive maintenance, which is a variable time basis maintenance strategy that is dependent on the condition of the equipment, is less utilized but potentially more effective. In the current maintenance practices, the nuclear power plants rely on manual processes to supply information to a human decision making process. The plants have several processes that generate information that is not typically used beyond the intended target for collecting that information. This information is a source of data that is manually collected by labor intensive tasks. The data is therefore expensive to collect, yet limited in use. The industry has realized the opportunity present in reducing the labor intensive tasks by automating them and increasing the uses of the data collected by either developing advanced predictive maintenance methods using data-driven decision making that could span from trending to machine learning and artificial intelligence. This shift in maintenance strategy may result in high cost saving impact. In addition to reducing labor requirements and frequency of maintenance activities, this shift in strategy will reduce the materials portion of the operations and maintenance cost as well. The aim of this specific effort is to focus on the automation of data collection process. It is part of a series of planned efforts to target multiple elements of migrating the current preventive maintenance approach in nuclear power plants to a data-driven approach. These elements include data collection, management, analysis, visualization, in addition to value analysis and change enabling. The other five elements of migration were not considered because they are planned to be explicitly studied in multiple parallel efforts. Challenges including regulations requirements or limitations are planned in a future effort that focuses on change enabling. The risk and benefit/cost of the approach shift is planned in another effort targeted towards value. The storage, communication, computational power, data architecture, and protection are part of the information infrastructure and are planned in dedicated data management effort. The best means to present the data for assisted human decision making is planned in a data visualization effort. The data interpretation and patterns recognition for machine decision making is planned through multiple efforts in data analytics over the following years. This work identified seventeen data sources collection methods in nuclear power plants that could be automated for an integrated data platform that enables comprehensive and informed decision making. For each of the identified seventeen data sources, the base, modern, and state of the art states were described. The current state of data collection used by most utilities was identified as the "base state". The current achievable state was identified as the "modern state", a state that has either been achieved by at least some US utilities or in other industries. The future state that requires research and development to reach was identified as the "state of the art" state. The described states used an out-of-the-box thinking approach. This effort found that there is a hug potential for task automation and data fidelity improvements by evolving the current industry data collection methods. The majority of the processes analyzed were found to be manual and labor intensive and fell in the base state. As a result, the modern state often targeted reducing the manual logging efforts by using electronic and semi-intelligent means or complementing the work with sensors and mobile or fixed technologies that can reduce the demand of labor activities. The state of the art state involved applications advanced methods of data correlation, data mining, and machine learning along with increasing the spatial distribution and fidelity of data, coupling multiple data sources, and enabling the use of sophisticated mobile devices and machine comprehension methods.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Near-real-time environmental monitoring and large-volume data collection over slow communication links
Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Changing Environments conducted in northern Minnesota. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high-carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO 2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable on-site data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. Furthermore this publication shares our experience of establishing a near-real-time data collection and monitoring system via a satellite link using the not very well-known possibilities of PakBus protocol.
47 OTHER INSTRUMENTATION↗
Performance of the ERTS data collection system in a total system context
The author has identified the following significant results. Approximately 70 percent of the DCP's being installed by Department of the Interior investigators have been successfully operated. These include DCP's operating in Iceland, Central America, Hawaii, and the Continental United States. The Data Collection System specifications are being met for frequency of data collection.
Paulson, R. W.↗
The use of the LANDSAT Data Collection Systems (DCS) for relaying hydrologic data
There are no author-identified significant results in this report.
Paulson, R. W.↗
Towards a knowledge-based system to assist the Brazilian data-collecting system operation
A study is reported which was carried out to show how a knowledge-based approach would lead to a flexible tool to assist the operation task in a satellite-based environmental data collection system. Some characteristics of a hypothesized system comprised of a satellite and a network of Interrogable Data Collecting Platforms (IDCPs) are pointed out. The Knowledge-Based Planning Assistant System (KBPAS) and some aspects about how knowledge is organized in the IDCP's domain are briefly described.
Rodrigues, Valter↗
hpMCA: A Python-based Graphical Program for Energy Dispersive X-Ray Diffraction Data Collection and Analysis
Energy-dispersive X-ray diffraction (EDXD) at synchrotron beamlines is commonly used for the study of material properties under high pressure and/or high temperature. Experimenters typically rely on the availability of robust data collection and analysis at a beamline, but this has become increasingly difficult, especially with the introduction of multi-element detectors that generate complex, multi-dimensional data sets. These data sets have energy resolution, and they can also be resolved in relation to sample position, diffraction angle, or different external stimuli. We report a new Python-based graphical program, hpMCA, for EDXD data collection and analysis that streamlines the experimental process for the beamline users. The program features a user-friendly interface, capability for online viewing and analyzing data from multi-element energy-dispersive detectors, and includes features useful for working with samples under high pressure and/or high temperature, such as crystal phase identification, real-time unit cell lattice refinement, and pressure determination based on an equation of state.
data analysis software↗
AuroraGPT Data Collection Interface
SF-25-043 This software package facilitates data collection for the purpose of assessing the performance of LLMs on scientific topics
Underwood, Robert [Argonne National Laboratory (AN↗
Integrated Data Collection Analysis (IDCA) Program — Bullseye ® Smokeless Powder
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 Bullseye ® smokeless powder (Gunpowder). The participants found the Gunpowder: 1) to have a range of sensitivity to impact, from less than RDX to almost as sensitive as PETN, 2) to be moderately sensitive to BAM and ABL friction, 3) have a range for ESD, from insensitive to more sensitive than PETN, and 4) to have thermal sensitivity about the same as PETN and RDX.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Integrated Data Collection Analysis (IDCA) Program - SSST Testing Methods
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 methods used for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis during the IDCA program. These methods changed throughout the Proficiency Test and the reasons for these changes are documented in this report. The most significant modifications in standard testing methods are: 1) including one specified sandpaper in impact testing among all the participants, 2) diversifying liquid test methods for selected participants, and 3) including sealed sample holders for thermal testing by at least one participant. This effort, funded by the Department of Homeland Security (DHS), is putting the issues of safe handling of these materials in perspective with standard military explosives. The study is adding SSST testing results for a broad suite of different HMEs to the literature. Ultimately the study will suggest new guidelines and methods and possibly establish the SSST testing accuracies needed to develop safe handling practices for HMEs. Each participating testing laboratory uses identical test materials and preparation methods wherever possible. The testing performers involved are Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Indian Head Division, Naval Surface Warfare Center, (NSWC IHD), Sandia National Laboratories (SNL), and Air Force Research Laboratory (AFRL/RXQL). These tests are conducted as a proficiency study in order to establish some consistency in test protocols, procedures, and experiments and to compare results when these testing variables cannot be made consistent.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The evolution of location and data collection systems in the United States.
Satellite location and data collection systems development began in the early 1960's in NASA and the French CNES. These systems were initially developed for application to meteorology and oceanography as a means of tracking moving platforms on a global scale. Additional applications such as geology, hydrology, and ecology have since evolved. To date, five successful missions have been completed. With each successive launch, systems improved in accordance with user requirements - particularly reduction in cost and complexity of platform equipment. With planned launches, facilities will be available to the user community through 1980; NASA is currently forecasting needs beyond 1980.
Morakis, J. C.↗