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Pyramid Comet Sampler Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:34:48.000ZBased on the sampling requirements, we propose an Inverted Pyramid sampling system. Each face of the pyramid includes a cutting blade which is independently actuated by redundant pyrotechnic actuators. Such sampler shape has a number of advantages. The pyramidal V shape acts as an arrow piercing into the comet surface at a steep angle. The 4 opposing blades offset tangential forces, meaning that only vertical forces would need to be reacted during impact. These forces could be minimized by making the pyramid height low (and in turn the pyramid would be more flat). In the latest Decadal Survey, the committee recommended selecting a Comet Surface Sample Return mission as one of the five New Frontiers 4 (NF4) missions, solidifying the importance of studying returned physical samples from a comet. Lunar South Pole-Aitken Basin Sample Return could also benefit from the development of this sampling approach.
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OMI/Aura Ozone (O3) Profile 1-Orbit L2 Swath 13x48km V003
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:53:30.000ZThe OMI/Aura Level-2 Ozone Profile data product OMO3PR (Version 003) is now available ( http://disc.gsfc.nasa.gov/Aura/OMI/omo3pr_v003.shtml ) from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI Level-2 ozone profile product, OMO3PR at the pixel resolution 13x 48 km (at nadir), is based on the optimal estimation algorithm (Rodgers, 2000) with climatological ozone profiles as a-priori information. The OMO3PR retrieval algorithm uses spectral radiance values from the UV1 channel (270 nm to 308.5 nm) and from the first part of the UV2 channel (311.5 nm to 33 0 nm). OMO3PR product provides ozone values (in Dobson unit) for 18 atmospheric layers. It also provides a-priori ozone profile values, error covariance matrix, averaging kernel and some ancillary information such as time, latitude, longitude, solar zenith and viewing zenith angles and quality flags . (The short name for this Level-2 OMI ozone profile product is OMO3PR) The lead scientist for this product is Dr. Johan de Haan (johan.de.haan@knmi.nl). OMO3PR product files are stored in Hierarchical Data Format (HDF-EOS5 ). Each file contains data from the day lit portion of an orbit (approx 53 minutes). There are approximately 14 orbits per day thus the total data volume is approximately 150 GB/day. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A 'Readme' document containing brief algorithm description and known data quality related issues and file spec are provided by the OMO3PR algorithm lead (see http://disc.gsfc.nasa.gov/Aura/OMI/omo3pr_v003.shtml ).
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Gridded Population of the World, Version 3 (GPWv3): Population Density Grid
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:36:45.000ZGridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated datasets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
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Global 15 x 15 Minute Grids of the Downscaled Population Based on the SRES B2 Scenario, 1990 and 2025
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T07:57:32.000ZThe Global 15x15 Minute Grids of the Downscaled Population Based on the Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990 and 2025, are geospatial distributions of the downscaled population per unit area (population densities). These global grids were generated using the Country-level Population and Downscaled Projections Based on the SRES B2 Scenario, 1990-2100 dataset, and CIESIN's Gridded Population of World, Version 2 (GPWv2) dataset as the base map. The 1990 GPW was used as the base distribution and the country-level downscaled projections were used to replace population estimates of 1990 in GPW and 2025. The fractional distribution of the population at each grid cell is the same as the 1990 GPW, sub-nationally. This dataset is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
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TRMM Precipitation Radar (PR) Level 2 Rainfall Rate and Profile Product (TRMM Product 2A25) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:53:20.000ZThe TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines the layer depth of the precipitation. The objectives of 2A25 is to correct for the rain attenuation in measured radar reflectivity and to estimate the instantaneous three-dimensional distribution of rain from the TRMM Precipitation Radar (PR) data. The estimates of attenuation-corrected radar reflectivity factor and rainfall rate are given at each resolution cell of the PR. The estimated near-surface rainfall rate and average rainfall rate between the two pre-defined altitudes (2 and 4 km) are also calculated for each beam position. 2A25 basically uses a hybrid of the Hitschfeld-Bordan method and the surface reference method to estimate the vertical true radar reflectivity (Z) profile. (The hybrid method is described in Iguchi and Meneghini (1994)). The vertical rain profile is then calculated from the estimated true Z profile by using an appropriate Z-R relationship. The attenuation correction is, in principle, based on the surface reference method. This method assumes that the decrease in the apparent surface cross section (delta sigma-zero) is caused by the propagation loss in rain. The coefficient a in the k-Z relationship, k=a Z**b, is adjusted in such a way that the path-integrated attenuation (PIA) estimated from the measured Zm-profile will match the delta sigma-zero. The attenuation correction of Z is carried out by the Hitschfeld-Bordan method with the modified a. Since a is adjusted, this type of surface reference method is called the a-adjustment method. The a-adjustment method assumes that the discrepancy between the PIA estimate from delta sigma-zero and that from the measured Zm-profile can be attributed to the inappropriate choice of a values, which may vary depending on the raindrop size distribution and other conditions. It assumes that the radar is properly calibrated and that the measured Zm has no error. In order to avoid inaccuracies in the attenuation correction when rain is weak, a hybrid of the surface reference method and the Hitschfeld-Bordan method is used (Iguchi and Meneghini, 1994). The PIA is first estimated from the precipitation echo alone. The weight given by the hybrid method to the PIA estimate from the surface reference increases as the attenuation estimate increases. When rain is very weak and the attenuation estimate is small, the PIA estimate from the surface reference is effectively neglected. With the introduction of the hybrid method, the divergence associated with the Hitschfeld-Bordan method is also prevented. One major difference from the method described in the above reference is that, in order to deal with the beam-filling problem, a non-uniformity parameter is introduced and is used to correct the bias in the surface reference arising from the horizontal non-uniformity of rain field within the beam. Since radar echoes from near the surface are contaminated by the mainlobe clutter, the rain estimate at the lowest point in the clutter-free region is given as the near-surface rainfall rate for each angle bin. Spatial coverage is between 38 degrees North and 38 degrees South, owing to the 35 degree inclination of the TRMM satellite. This orbit provides extensive coverage in the tropics and allows each location to be covered at a different local time each day, enabling the analysis of the diurnal cycle of precipitation. There are, in general, 9150 scans along the orbit, with each scan consisting of 49 rays. The scan width is about 220 km. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the PR measurements. A fi...
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Approximate Cartesian Control for Robotic Tool Usage with Graceful Degradation Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:31:39.000ZMany of NASA's exploration scenarios include important roles for autonomous or partially autonomous robots. It is desirable for them to utilize human tools when possible, rather than needing to build custom tools for each robot. Control of robotic manipulators for tool usage generally requires a very precise Cartesian-space trajectory of the tool tip (e.g., moving a marker along the surface of a whiteboard or rotating a screwdriver about an axis). Well-known techniques exist for manipulator control in Cartesian space, most of which necessitate solving a series of Inverse Kinematics (IK) problems. Closed-form IK solvers work well for 7-degree-of-freedom (DOF) arms with rigid tool attachments, but cannot handle non-rigid tools that slip in the robot's hands. Numerical IK approaches are more generic and can handle non-rigid links to tools, but can be slow to converge. More importantly, if any joints fail or become limited in their range of motion, the robot arm essentially becomes 6-DOF or lower. IK solvers often fail in these lower DOF spaces because the configuration space becomes non-continuous and full of "holes". As a result, a 7-DOF robotic arm in space might be rendered largely useless if a single joint fails or even loses mobility until it can be serviced. TRACLabs proposes to investigate an alternative approach to traditional Cartesian control approaches, which rely on complex IK solvers that go from Cartesian space backwards to joint space. We propose to leverage cheap memory and modern processing speeds to instead perform simple computations that go from joint space forwards to Cartesian space. Such techniques should overcome common changes to a manipulation chain caused by tool slippage or the grasping of a new tool and to overcome uncommon changes to a chain caused by joint failures, reduced joint mobility, changes in joint geometry or range of motion, or added joints.
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Combining Discrete Element Modeling, Finite Element Analysis, and Experimental Calibrations for Modeling of Granular Material Systems Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:43:27.000ZThe current state-of-the-art in DEM modeling has two major limitations which must be overcome to ensure that the technique can be useful to NASA engineers and the commercial sector: the computational intensive nature of the software, and the lack of an established methodology to determine the particle properties to best accurately model a given physical system. The proposed work will address both of these limitations. We will look at two approaches to overcome the particle count limitations of DEM: investigate the scaling up of particle size; and combine FEA and DEM to look at problems of densely packed solids. We will explore regimes where DEM and FEA are applicable and establish a coupling methodology that can be further developed during phase II. To address the lack of an established methodology to determine the particle properties to best accurately model a given physical system, we will investigate several small scale experiments that can be used to characterize DEM models. The proposed work will advance the state-of-the-art in DEM. At the end of phase I we will show the feasibility of developing modeling approaches to overcome the main limitations of DEM.
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SBUV2/NOAA-11 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:54:41.000ZThe Solar Backscattered Ultra Violet (SBUV) from NOAA-11 Level-3 monthly zonal mean (MZM) product (SBUV2N11L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 147 months of data from January 1989 through March 2001. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 deg.) 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 deg; large discrepancy between profile total and best total ozone) NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angle where B-Pair total ozone estimate is not as reliable as profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15)
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Population Exposure Estimates in Proximity to Nuclear Power Plants, Country-Level Aggregates
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:36:37.000ZThe Population Exposure Estimates in Proximity to Nuclear Power Plants, Country-Level Aggregates data set consists of country-level estimates of total, urban, and rural populations and land area, country-wide, that are in proximity to a nuclear power plant. This data set was created using a global data set of point locations of nuclear power plants, with buffer zones at 30km, 75km, 150km, 300km, 600km, and 1200km, and the Global Population Count Grid Time Series Estimates, Version 1 to estimate the population within each buffer zone for the years 1990, 2000, and 2010. Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) Land and Geographic Unit Area Grids were used to estimate land area within each buffer zone. The GRUMPv1 Urban Extents Grid was used to further delineate population and land area estimates within urban and rural areas. All grids used for population, land area, and urban mask were of 1 km (30 arc-second) resolution.
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SBUV2/NOAA-16 Ozone (O3) Profile and Total Column Ozone 1 Month Zonal Mean L3 Global 5.0 degree Latitude Zones V1 (SBUV2N16L3zm) at GES DISC
data.nasa.gov | Last Updated 2022-01-17T05:51:01.000ZThe Solar Backscattered Ultraviolet (SBUV) from NOAA-16 Level-3 monthly zonal mean (MZM) product (SBUV2N16L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 154 months of data from October 2000 through July 2013. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees). 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone). NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).