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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Software Archive Related Issues

With the archive opening of the major X-ray and Gamma ray missions, the school is intended to provide information on the resource available in the data archive and the public software. This talk reviews the archive content, the data format for the major active missions Chandra, XMM-Newton, Swift, RXTE, Integral and Suzaku and the available software for each of these missions. It will explain the FITS format in general and the specific layout for the most popular mission, explaining the role of keywords and how they fit in the multimission standard approach embrace by the High Energy Community. Specifically, it reviews : the difference data levels and the difference software applicable; the popular/standard method of analysis for high level products such as spectra, timing and images; the role of calibration in the multi mission approach; how to navigate the archive query databases. It will present also how the school is organized and how the information provided will be relevant to each of the afternoon science projects that will be proposed to the students and led by a project leader

Angelini, Lorella↗
NASA NTRS1984

Advanced Data Structure and Geographic Information Systems

The current state of the art in specified areas of Geographic Information Systems GIS technology is examined. Study of the question of very large, efficient, heterogeneous spatial databases is required in order to explore the potential application of remotely sensed data for studying the long term habitability of the Earth. Research includes a review of spatial data structures and storage, development of operations required by GIS, and preparation of a testbed system to compare Vaster data structure with NASA's Topological Raster Structure.

Peuquet, D.↗
NASA NTRS1992

Interdisciplinary analysis from the spacecraft thermal analyst's viewpoint

Interdisciplinary analyses performed at the Marshall Space Flight Center based on multidiscipline data flows are reviewed. Particular attention is given to global software packages for allowing efficient interdisciplinary data exchange, the use of a number of smaller individual packages, specific software programs utilized by the various interfacing disciplines to perform calculations in terms of interface compatibility, and tasks based on thermal evaluations integral. Recommendations for improvements in the MSFC equipment, software, and organization are proposed.

Humphries, W. R.↗
NASA NTRS1982

A review of the 1979 March 5 transient

Existing observational data and analyses are reviewed for the gamma-ray transient event of Mar. 5, 1979. Differences between the event and classical gamma-ray bursts are summarized, and unusual features of the March 5 event are described. They include the oscillations, time history, intensity, spectrum, and recurrent events. The possible association of the event with a neutron star in the N49 supernova remnant in the Large Magellanic Cloud is examined in detail. The alternative possibility of an invisible source within the Galaxy is also considered.

Cline, T. L.↗
DOE OSTI2025

A model to assess Zircaloy’s mechanical property changes following a transient beyond critical heat flux

Maintaining the integrity of nuclear fuel rods is essential for ensuring public health and safety in nuclear power generation. During reactor operation, this integrity is confirmed by demonstrating compliance with established regulatory acceptance criteria. For moderate-frequency events, such as limiting transients and anticipated operational occurrences (AOOs), the current fuel integrity criterion is based on preventing boiling transition. This criterion assumes that prevention of boiling transition will prevent excessive cladding heating and, thus, fuel failure during normal operations. While conservative, this approach places significant constraints on core design, fuel cycle economics, and a plant’s ability to perform major power uprates, leading to suboptimal fuel utilization and inefficient carbon-free energy production. A more efficient approach could be achieved by revising the failure criterion to a material-specific limit rather than strictly preventing the boiling transition, since boiling transition per se is not a cause of fuel cladding failure. Here, as a result, a new licensing framework based on material properties, termed time-at-temperature (t@T), is needed. This approach would allow for brief periods of post–critical heat flux operation during an AOO without compromising safety. Implementing the t@T licensing strategy requires a robust technical foundation in material properties, which must be established through comprehensive data collection on both unirradiated and irradiated fuel and cladding materials. This foundation would enable the development of a safety basis that ensures safe operation while providing greater flexibility and efficiency for reactor operation. This paper documents a thorough review of the available data to establish a baseline knowledge that can inform the development of cladding mechanical models, as well as identify experimental data gaps that need to be addressed in future research. Machine learning and data informatics were utilized to extract the importance of parameters on the t@T parameter. Industry tools were used to perform baseline analyses to define the relevant transient conditions for data analysis. The subsequent review successfully identified applicable experimental data, as well as sufficient data to evaluate changes in cladding mechanical properties following an AOO transient. Rather than developing new models, this work coupled existing irradiation annealing and recrystallization models to calculate changes in hardness, yield stress, and ultimate tensile stress following an AOO event. The findings from this review were summarized to highlight the experimental data needs required to fill remaining gaps and support the development of future t@T licensing methodologies.

Cladding performance↗
NASA NTRS1992

Issues on human acceleration tolerance after long-duration space flights

This report reviewed the literature on human tolerance to acceleration at 1 G and changes in tolerance after exposure to hypogravic fields. It was found that human tolerance decreased after exposure to hypokinetic and hypogravic fields, but the magnitude of such reduction ranged from 0 to 30 percent for plateau G forces and 30 to 70 percent for time tolerance on sustained G forces. A logistic regression model of the probability of individuals with 25 percent reduction in +Gz tolerance after 1 to 41 days of hypogravic exposures was constructed. The estimated values from the model showed a good correlation with the observed data. A brief review of the need for in-flight centrifuge during long-duration missions was also presented. Review of the available data showed that the use of countermeasures (such as anti-G suits, periodic acceleration, and exercise) reduced the decrement in acceleration tolerance after long-duration space flights. Areas of further research include quantification of the effect of countermeasures on tolerance, and methods to augment tolerance during and after exposures to hypogravic fields. Such data are essential for planning long-duration human missions.

Kumar, K. Vasantha↗
DOE OSTI2023

Observations and Lessons Learned in Residential Roofing Integrated Photovoltaics

The data file includes field observations of residential roofing integrated photovoltaics installation that happened between July 2021 and June 2022 in California. There are 21 observations - 2 in the re-roofing category and 19 in the new construction category. The file includes two time and motion forms (Re-Roofing & New Construction) we used to capture the time it takes for each activity in the rooftop solar and electrical installation process. You will see the duration for detailed steps along with activities that are included for total installation time for the paper. There are three parts to the time and motion form - Part 1 has project and crew characteristics, product information, and inspection and permitting data and can be filled before the installation. Part 2 has the actual installation time stamps and related notes. Part 3 has the crew information and can be filled on-site or off-site, but this section is optional. The re-roofing form has pre-solar activities and gutters and vents section in Part 2 of the form, whereas new construction form includes a section for capturing the time it took for rough wiring. The re-roofing form does not include rough wiring but instead includes the final electrical wiring process. These are the key differences in both the forms. Each day/step/installation activity needs to include the crew break time as they happen and there is space available to capture the crew breaks duration. In Table 1 below, the different terms used in the time and motion form are defined and their corresponding unit of measurement stated. We also highlight the optional sections. The data is captured in total mins, total hours, person mins, person hours. You can use this form or make edits to the form to recreate the study or make your own observations. The data herein was reviewed but may not be comprehensive. NREL invites questions and inputs to improve the data, including to: Correct erroneous information Fill in missing/updated information Clarifications on data and variables Updated information may be submitted to Sushmita Jena at sushmita.jena@nlr.gov.

14 SOLAR ENERGY↗
NASA NTRS1981

Progress on low altitude cloud icing research

The icing environment at altitudes below 10,000 feet were studied. The following questions are asked, are: (1) existing aircraft certification criteria applicable; (2) too stringent on icing for helos; (3) based on accurate data; (4) appropriate for low (10,000 ft) altitudes? The research plan is outlined: review historical icing data, obtain new measurements, collect modern icing data from other groups, and recommend LWC, OAT, and MVD criteria for helicopters. Estimated accuracies and known sources of error are included. It is concluded that the net effect of possible sources of error of both signs is uncertain.

Jeck, R. K.↗
NASA NTRS1990

Proposed military handbook for dynamic data acquisition and analysis - An invitation to review

A draft Military Handbook prepared under the sponsorship of the USAF Space Division is presently being distributed throughout the U.S. for review by the aerospace community. This comprehensive document provides recommended guidelines for the acquisition and analysis of structural dynamics and aeroacoustic data, and is intended to reduce the errors and variability commonly found in flight, ground and laboratory dynamic test measurements. In addition to the usual variety of measurement problems encountered in the definition of dynamic loads, the development of design and test criteria, and the analysis of failures, special emphasis is given to certain state-of-the-art topics, such as pyroshock data acquisition and nonstationary random data analysis.

Himelblau, Harry↗
NASA NTRS2011

Pre/Post Data Analysis - Simple or Is It?

This slide presentation reviews some of the problems of data analysis in analyzing pre and post data. Using as an example, ankle extensor strength (AES) experiments, to measure bone density loss during bed rest, the presentation discusses several questions: (1) How should we describe change? (2) Common analysis methods for comparing post to pre results. (3) What do we mean by "% change"? and (4) What are we testing when we compare % changes?

Feiveson, Al↗
NASA NTRS2019

MERRA-2 Data and Analytic Services at NASA GES DISC for Climate Extremes Study

NASA's climate reanalysis datasets from the Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) contains numerous long-term atmosphere, land, and ocean data products from 1980-present. MERRA-2 datasets, such as precipitation, soil moisture, and temperature, have been used widely to study extreme events. The native archived MERRA-2 data files are day-file (hourly time interval) and month-file, containing up to 125 parameters in one file. Due to the large number of data files and volumes, it is challenging for users, especially the applications research community, to handle the original hourly data files for long time periods to analyze extreme events. In this presentation, we review MERRA-2 data for studies of extreme conditions, and demonstrate analytic services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). One of the current operational services, 'subsetter', allows users to download only specific data of interest, i.e. data selected by parameter, region, and time period. New services are under development that will provide more 'on-the-fly' statistical calculations when downloading data; improve efficiency when accessing long time-series data. We will provide additional "How-to" resources that include step-by-step instructions on data access and usage. We have tested restructuring of day-files in an optimized data cube, which has significantly improved system performance for accessing long time-series. Overall performance is associated with cube size and structure, data compression method, and how the data are accessed. The optimized data cube structure will enable better online analytic services for statistical analysis and extreme events mining. To demonstrate the service, we use an extreme drought associated with the anomalous 2016 monsoon over southern Asia. This prototype time-series service may be augmented in the cloud infrastructure in the future.

data access↗
NASA NTRS1998

Nutrition, endocrinology, and body composition during space flight

Space flight induces endocrine changes that perturb metabolism. This altered metabolism affects both the astronauts' body composition and the nutritional requirements necessary to maintain their health. During the last 25 years, a combination of studies conducted on Skylab (the first U.S. space laboratory), U.S. Shuttle flights, and Soviet and Russian flights provides a range of data from which general conclusions about energy and protein requirements can be drawn. We have reviewed the endocrine data from those studies and related it to changes in body composition. From these data it appears that protein and energy intake of astronauts are similar to those on Earth. However, a combination of measures, including exercise, appropriate diet, and, potentially, drugs, is required to provide the muscle health needed for long duration space flight.

Flight Experiment↗
NASA NTRS1983

The magnetosphere of Saturn

Characterizations of the Saturn magnetospheric activities that have been made possible through data gathered by means of the Pioneer 11 and Voyagers 1 and 2 flybys are reviewed. The spacecraft data confirmed the presence of a Saturn magnetosphere, which features inward diffusion and energization of trapped energetic particles as well as cosmic ray albedo neutron decay as a source of inner belt protons. A dense plasma was identified in the region covering the outer magnetosphere to the magnetopause, which extends outward 17.3-23.6 Saturn radii on the sunward side and from 30.3-70 radii on the far side, according to the satellite measurements. Characteristics of the particle populations and behaviors of the outer magnetosphere, the slot region, the inner magnetosphere, and the ring region are reviewed, as are those of the magnetic field, the solar wind-magnetospheric interaction, and the Titan-magnetospheric interaction are described. Further investigation of the longitudinal asymmetry of decimetric radio emissions from Saturn is recommended.

Schardt, A. W.↗
DOE OSTI2023

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a collection of objects stored within an RDate file, stateWaterRightsHarmonized.RData. Each object either describes how one should interact with the other objects, or contains the harmonized water rights data. Here is each object described in detail: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. The column headers for each data frame are: waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. basinNum - The alpha-numeric identifier of the WMA the record belongs to. priorityDate - The priority date associated with the right. allocatedFlow - The maximum flow of the allocation in cubic feet per second (ft3s-1). source - Whether the right is for surface water or groundwater. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. rightsByState_surface: A list of the cleaned surface water rights collected from each state. See rightsByState_ground for more details on how the data is formatted. fullRightsRecs: A list of the combined groundwater and surface water records for each state. Essentially, these lists are the merging of rightsByState_ground and rightsByState_surface by state. See rightsByState_ground for more details on how the data is formatted. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page.

Economics↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to included within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state.

Economics↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a series of various files organized by state sub-directories. The first two characters of each file name is the abbreviation for the state the in which the file contains data for. After the abbreviation is the text which describes the contents of the file. Here is each file type described in detail: XXFullHarmonizedRights.csv: A file of the combined groundwater and surface water records for each state. Essentially, this file is the merging of XXGroundwaterHarmonizedRights.csv and XXSurfaceWaterHarmonizedRights.csv by state. The column headers for each of this type of file are: state - The name of the state the data comes from. FIPS - The two-digit numeric state ID code. waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. priorityDate - The priority date associated with the right. origWaterUse - The original stated water use(s) from the state. waterUse - The water use category under the unified use categories established here. source - Whether the right is for surface water or groundwater. basinNum - The alpha-numeric identifier of the WMA the record belongs to. CFS - The maximum flow of the allocation in cubic feet per second (ft3s-1). Arizona is unique among the states, as its surface and groundwater resources are managed with two different sets of boundaries. So, for Arizona, the basinNum column is missing and instead there are two columns: surBasinNum - The alpha-numeric identifier of the surface water WMA the record belongs to. grdBasinNum - The alpha-numeric identifier of the groundwater WMA the record belongs to. XXStatePOD.shp: A shapefile which identifies the location of the Points of Diversion for the state's water rights. It should be noted that not all water right records in XXFullHarmonizedRights.csv have coordinates, and therefore may be missing from this file. XXStatePOU.shp: A shapefile which contains the area(s) in which each water right is claimed to be used. Currently, only Idaho and Washington provided valid data to include within this file. XXGroundwaterHarmonizedRights.csv: A file which contains only harmonized groundwater rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. XXSurfaceWaterHarmonizedRights.csv: A file which contains only harmonized surface water rights collected from each state. See XXFullHarmonizedRights.csv for more details on how the data is formatted. Additionally, one file, stateWMALabels.csv, is not stored within a sub-directory. While we have referred to the spatial boundaries that each state uses to manage its water resources as WMAs, this term is not shared across all states. This file lists the proper name for each boundary set, by state. For those whom may be interested in exploring our code more in depth, we are also making available an internal data file for convenience. The file is in .RData format and contains everything described above as well as some minor additional objects used within the code calculating the cumulative curves. For completeness, here is a detailed description of the various objects which can be found within the .RData file: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. This object holds the the data that is exported to created the xxGroundwaterHarmonizedRights.csv files. rightsByState_surface: A list of data frames with the cleaned surface water rights collected from each state. This object holds the the data that is exported to created the xxSurfaceWaterHarmonizedRights.csv files. fullRightsRecs: A list of the combined groundwater and surface water records for each state. This object holds the the data that is exported to created the xxFullHarmonizedRights.csv files. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page. The code related to the creation of this dataset can be viewed within HarDWR GitHub Repository/dataHarmonization.

Economics↗
NASA NTRS1978

The structure of vortex breakdown

The term 'vortex breakdown', as used in the reported investigation, refers to a disturbance characterized by the formation of an internal stagnation point on the vortex axis, followed by reversed flow in a region of limited axial extent. Two forms of vortex breakdown, which predominate, are shown in photographs. One form is called 'near-axisymmetric' (sometimes 'axisymmetric'), and the other is called 'spiral'. A survey is presented of work published since the 1972 review by Hall. Most experimental data taken since Hall's review have been in tubes, and the survey deals primarily with such cases. It is found that the assumption of axial-symmetry has produced useful results. The classification of flows as supercritical or subcritical, a step that assumes symmetry, has proved universally useful. Experiments show that vortex breakdown is always preceded by an upstream supercritical flow and followed by a subcritical wake. However, a comparison between experiments and attempts at prediction is less than encouraging. For a satisfactory understanding of the structure of vortex breakdown it is apparently necessary to take into account also aspects of asymmetry.

Leibovich, S.↗
NASA NTRS1985

Auroral imaging from Spacelab 3

A comprehensive set of video and photographic images of the aurora was acquired and analyzed from Spacelab 3. Since each pass of Spacelab covers several hours of local time during an elapsed time of only a few minutes, it was hoped that these images would provide additional insight into the local-time dependence of the auroral morphology. Spacelab 3 was launched on April 29, 1985 and auroral data were obtained during the period April 30 to May 5. Preparations made for the auroral experiment, the quality and quantity of the data obtained, the initial scientific results, and ideas for further inquiry suggested by the preliminary review of the data are discussed.

Hallinan, T. J.↗