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Correlated optical observations with BATSE/CGRO on SCO X-1

The Burst and Transient Source Experiment (BATSE) instrument on the Compton Gamma-Ray Observatory consists of two banks of eight instruments referred to as the Large Area Detectors (LADs) and the Spectroscopic Detectors (SDs). Each LAD crystal is 50.8 cm in diameter by 1.27 cm thick while for a SD these values are 12.7 cm in diameter by 7.62 cm in diameter. Both the LADs and SDs are NaI(TI) scintillation detectors. The LADs and SDs are situated on the CGRO spacecraft so as to provide all sky coverage for both sets of detectors. The SDs have the ability to measure energies in the 8-16 keV range whereas the minimum energy at which the LADs operate is near 20 keV. SCO X-1 is the brightest continuous x-ray source in the sky. It is believed to consist of a low mass star orbiting and transferring mass onto a neutron star. It is representative of a class of similar objects referred to as low mass x-ray binaries (LMXB). Because SCO X-1 serves as the prototype of this class of x-ray emitters and since its detectable emission is so large, it warrants extended study. One of the most fruitful techniques of studying a LMXB system is by simultaneously monitoring its emission at a variety of different wavelengths. These correlated datasets can be used to probe the source environment, investigate emission mechanisms, and examine the mass transfer process itself. In principle, the BATSE SDs have the capability of providing a nearly continuous 8-16 keV record of SCO X-1 activity. The aim of this study was to investigate the feasibility of using the BATSE SDs along with simultaneous optical measurements to study this source.

Mcnamara, Bernard↗

A self-defining hierarchical data system

The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.

Bailey, J.↗

NASA's spacecraft data system

The NASA Small Explorer Data System (SEDS), a space flight data system developed to support the Small Explorer (SMEX) project, is addressed. The system was flown on the Solar Anomalous Magnetospheric Particle Explorer (SAMPEX) SMEX mission, and with reconfiguration for different requirements will fly on the X-ray Timing Explorer (XTE) and the Tropical Rainfall Measuring Mission (TRMM). SEDS is also foreseen for the Hubble repair mission. Its name was changed to Spacecraft Data System (SDS) in view of expansions. Objectives, SDS hardware, and software are described. Each SDS box contains two computers, data storage memory, uplink (command) reception circuitry, downlink (telemetry) encoding circuitry, Instrument Telemetry Controller (ITC), and spacecraft timing circuitry. The SDS communicates with other subsystems over the MIL-STD-1773 data bus. The SDS software uses a real time Operating System (OS) and the C language. The OS layer, communications and scheduling layer, application task layer, and diagnostic software, are described. Decisions on the use of advanced technologies, such as ASIC's (Application Specific Integrated Circuits) and fiber optics, led to technical improvements, such as lower power and weight, without increasing the risk associated with the data system. The result was a successful SAMPEX development, integration and test, and mission using SEDS, and the upgrading of that system to SDS for TRMM and XTE.

Cudmore, Alan↗

On-line process analysis innovation: DiComp (tm) shunting dielectric sensor technology

The DiComp Shunting Dielectric Sensor (SDS) is a new patent-pending technology developed under the Small Business Innovation Research Program (SBIR) for NASA's Kennedy Space Center. The incorporation of a shunt electrode into a conventional fringing field dielectric sensor makes the SDS uniquely sensitive to changes in material dielectric properties in the KHz to MHz range which were previously detectable only at GHz measurement frequencies. The initial NASA application of the SDS for Nutrient Delivery Control has demonstrated SDS capabilities for thickness and concentration measurement of Hoagland nutrient solutions. The commercial introduction of DiComp SDS technology for concentration and percent solids measurements in dispersions, emulsions and solutions represents a new technology for process measurements for liquids in a variety of industries.

Davis, Craig R.↗

A Science Data System Approach for the SMAP Mission

Though Science Data System (SDS) development has not traditionally been part of the mission concept phase, lessons learned and study of past Earth science missions indicate that SDS functionality can greatly benefit algorithm developers in all mission phases. We have proposed a SDS approach for the SMAP Mission that incorporates early support for an algorithm testbed, allowing scientists to develop codes and seamlessly integrate them into the operational SDS. This approach will greatly reduce both the costs and risks involved in algorithm transitioning and SDS development.

PCS↗

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

Development of the Space Debris Sensor

The Space Debris Sensor (SDS) is a NASA experiment scheduled to fly aboard the International Space Station (ISS) starting in 2017. The SDS is the first flight demonstration of the Debris Resistive/Acoustic Grid Orbital NASA-Navy Sensor (DRAGONS) developed and matured by the NASA Orbital Debris Program Office. The DRAGONS concept combines several technologies to characterize the size, speed, direction, and density of small impacting objects. With a minimum two-year operational lifetime, SDS is anticipated to collect statistically significant information on orbital debris ranging from 50 micron to 500 micron in size. This paper describes the SDS features and how data from the ISS mission may be used to update debris environment models. Results of hypervelocity impact testing during the development of SDS and the potential for improvement on future sensors at higher altitudes will be reviewed.

Hamilton, J.↗

Freestream Mach-Number and Temperature Measurement in NASA Langley’s 20-Inch Supersonic Wind Tunnel Using Laser-Induced Thermal Acoustics

We report single-laser-shot (0.3 us) and time-averaged (500 laser shots at 30 Hz repetition rate) measurements of static temperature T and Mach number M in the freestream of NASA Langley’s 20-inch Supersonic Wind Tunnel (SWT), using a nonintrusive optical technique: laser-induced thermal acoustics (LITA). Although the single-shot LITA T measurements show typical standard deviations (SD) of the sample of +- 4% (+- 1-sigma or 68% confidence for random errors), the 1-s averages show SDs of the mean deltaT = +- 0.5 K, or +- 0.3% for flow at T ~ 160 K. The 17-s averages show ± 0.1% SDs of the mean. Both 1-s and 17-s averages agree to within about 1% of SWT’s traditional probe measurements. Additionally, the single-shot LITA M measurements show typical shot-to-shot SDs of the sample of +- 5% (+- 1-sigma), but the 1-s averages indicate 1-sigma SDs of the means deltaM = +- 0.02, or +- 1% for M = 2.0. Extending the time averages to 17 s, SDs of the mean are reduced to about deltaM = +- 0.007, or +- 0.4% (± 1-sigma). The 1-s and 17-s time-averaged LITA-measured Mach numbers also agree with the SWT probe instrumentation to within 1%. Most of the shot-to-shot measurement noise probably arises from the LITA instrument itself (the fundamental limit of Fourier transforming a short-duration data series). Thus the 1-s averages only provide upper limits for the temporal stability of the freestream tunnel flow on 1-s time scales and complement previous work that characterized the SWT spatial uniformity of the flow. They also provide a first noninvasive comparison to the traditional calibrations with physical probes, for both the mean and fluctuating components of the freestream.

Laser-Induced Thermal Acoustics (LITA)↗

Spacecraft Data Simulator for the test of level zero processing systems

The Microelectronic Systems Branch (MSB) at Goddard Space Flight Center (GSFC) has developed a Spacecraft Data Simulator (SDS) to support the development, test, and verification of prototype and production Level Zero Processing (LZP) systems. Based on a disk array system, the SDS is capable of generating large test data sets up to 5 Gigabytes and outputting serial test data at rates up to 80 Mbps. The SDS supports data formats including NASA Communication (Nascom) blocks, Consultative Committee for Space Data System (CCSDS) Version 1 & 2 frames and packets, and all the Advanced Orbiting Systems (AOS) services. The capability to simulate both sequential and non-sequential time-ordered downlink data streams with errors and gaps is crucial to test LZP systems. This paper describes the system architecture, hardware and software designs, and test data designs. Examples of test data designs are included to illustrate the application of the SDS.

Shi, Jeff↗

ICESat (GLAS) Science Processing Software Document Series: Science Software Management Plan - Volume 1

This document provides the Software Management Plan for the GLAS Standard Data Software (SDS) supporting the GLAS instrument of the EOS ICESat Spacecraft. The SDS encompasses the ICESat Science Investigator-led Processing System (I-SIPS) Software and the Instrument Support Terminal (IST) Software. For the I-SIPS Software, the SDS will produce Level 0, Level 1, and Level 2 data products as well as the associated product quality assessments and descriptive information. For the IST Software, the SDS will accommodate the GLAS instrument support areas of engineering status, command, performance assessment, and instrument health status.

Hancock, David W., III↗

Effects of Microheterogeneity in Hen Egg-White Lysozyme Crystallization

In earlier sodium dodecylsulfate polyacylamide gel electrophoresis (SDS-PAGE) studies it has been found that commonly utilized commercial hen egg-white lysozyme (HEWL) preparations contained 0.2-0.4 mol% covalently bound dimers. Here it is shown, using high-performance capillary electrophoresis (HPCE), that HEWL contains, in addition, two differently charged monomers in comparable amounts. To explore the origin of these microheterogeneous contaminants, purified HEWL (PHEWL) has been oxidized with hydrogen peroxide (0.0026-0.88 M) at various pH levels between 4.5 and 12.0. Optical densitometry of oxidized PHEWL (OHEWL) bands in SDS PAGE gels shows that hydrogen peroxide at 0.88 M in acetate buffer pH 4.5 increased the amount of dimers about sixfold over that in commercial HEWL. OHEWL had, in addition to one of the two monomer forms found in HEWL and PHEWL, three other differently charged monomer forms, each of them representing about 25% of the preparation. SDS-PAGE analysis of OHEWL yielded two closely spaced dimer bands with M(sub r) = 28 000 and 27 500. In addition, larger HEWL oligomers with M, = 1.7 million and 320 000 were detected by gel-filtration fast protein liquid chromatography with multiangle laser light scattering detection. Non-dissociating PAGE in large pore size gels at pH 4.5 confirmed the presence of these large oligomers in HEWL and OHEWL. Increased microheterogeneity resulted in substantial effects on crystal growth and nucleation rate. On addition of 10 microgram(exp -1) mg ml(exp -1) OHEWL to 32 mg ml(exp -1) HEWL crystallizing solutions, both the number and size of forming crystals decreased roughly proportionally to the concentration of the added microheterogeneity. The same effect was observed in HEWL solutions on addition of 0.03-9,3 M Hydrogen peroxide. Repartioning of the dimer during crystallzation aat various temperatures between 277 and 293 K was analyzed by SDS-PAGE. The crystals contained <= 25 % weight by volume of the oligomers in the solution, with no apparent temperature dependence of the repartioning.

Thomas, B. R.↗

Advanced Applications of Adifor 3.0 for Efficient Calculation of First-and Second-Order CFD Sensitivity Derivatives

This final report will document the accomplishments of the work of this project. 1) The incremental-iterative (II) form of the reverse-mode (adjoint) method for computing first-order (FO) aerodynamic sensitivity derivatives (SDs) has been successfully implemented and tested in a 2D CFD code (called ANSERS) using the reverse-mode capability of ADIFOR 3.0. These preceding results compared very well with similar SDS computed via a black-box (BB) application of the reverse-mode capability of ADIFOR 3.0, and also with similar SDs calculated via the method of finite differences. 2) Second-order (SO) SDs have been implemented in the 2D ASNWERS code using the very efficient strategy that was originally proposed (but not previously tested) of Reference 3, Appendix A. Furthermore, these SO SOs have been validated for accuracy and computational efficiency. 3) Studies were conducted in Quasi-1D and 2D concerning the smoothness (or lack of smoothness) of the FO and SO SD's for flows with shock waves. The phenomenon is documented in the publications of this study (listed subsequently), however, the specific numerical mechanism which is responsible for this unsmoothness phenomenon was not discovered. 4) The FO and SO derivatives for Quasi-1D and 2D flows were applied to predict aerodynamic design uncertainties, and were also applied in robust design optimization studies.

Taylor, Arthur C., III↗

Modeling Spectral Degradation of MODIS and VIIRS Solar Diffusers

Solar diffusers (SDs) onboard the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua spacecraft and the Visible Infrared Imaging Radiometer Suite (VIIRS) on SNPP and NOAA-20 spacecraft have been used as the primary onboard radiometric calibrator for reflective solar bands and their spectral reflectance is known to degrade on-orbit. All of the solar diffusers on these instrument show faster degradation of reflectance in the 0.4 to 0.6 µm channels than the longer wavelength channels. The spectral degradation of these SDs is due to the surface roughness growth under the exposure to solar UV and energetic particle radiation in space. In this paper, the origin of SD degradation is modeled by the physics-based Surface Roughness-induced Rayleigh Scattering (SRRS) model. The longterm growths of surface roughness of the SD on these instruments are characterized to show the consistency of SD roughness growth rates between Terra/Aqua MODIS and SNPP/NOAA-20 VIIRS. There was coincidental flattening or reverse in the growth trend of the surface roughness for the Terra/Aqua MODIS and SNPP VIIRS SDs, which can be due to the space weather variation. The applicability of the SRRS model is demonstrated with the long term spectral reflectance data from independent spaceborne SDs.

Calibration↗

The Impact of New Accelerometer Transplant Data (ACH) on GRACE Follow-On Along-Orbit Inter-Satellite Laser Ranging Observations and Monthly Time-Variable Gravity and Mascon Solutions

GRACE-D accelerometer data show significant bias jumps since one month after the launch of the GRACE Follow-On (GRACE-FO) satellites in May 2018, making them inapplicable for correcting GRACE-FO products for non-gravitational accelerations. The GRACE-FO Science Data System (SDS) compensated this issue by transplanting the GRACE-C accelerometer data toward that of GRACE-D. Recently, GRACE-FO SDS implemented an updated transplant method, used in the latest release of GRACE-FO data. Here, we examine the impact of updated accelerometer transplant data (ACH) on GRACE-FO measurements at all levels: (a) Level-1B inter-satellite laser ranging residuals measured along satellite orbit, (b) Level-2 time-variable gravity solutions from all SDS centers (JPL, CSR, and GFZ), and (c) Level-3 mascon solutions. We show that inter-satellite laser ranging residuals are modified at low frequencies below 1 mHz, affecting the along-orbit analysis of large-scale time-variable gravity signals. When mapped into monthly Level-2 spherical harmonic coefficients of geopotential, the low-frequency change in inter-satellite ranging residuals leads to substantial improvement of coefficients associated with resonant orders (i.e., 15, 30, 45, etc.) and C 30 . We also present an improved SLR-derived C 30 which significantly improves the agreement with updated GRACE-FO C 30 at seasonal and interannual timescales. Moreover, we demonstrate the noise reduction in mass change estimates from new GRACE-FO Level-2 data over oceans, Greenland, and Antarctica for all SDS solutions. GRACE-FO mascon solutions show a moderate change in the updated release. Our comprehensive analyses demonstrate high-quality estimates of non-gravitational accelerations by the updated transplant method, resulting in more accurate GRACE-FO time-variable gravity and mass change observations.

Laser ranging interferometer↗

Effect of Hindlimb Unweighting on Single Soleus Fiber Maximal Shortening Velocity and ATPase Activity

This study characterizes the time course of change in single soleus muscle fiber size and function elicited by hindlimb un weighting (HU) and analyzes the extent to which varying durations of HU altered maximal velocity of shortening (V(sub o)), myofibrillar adenosinetriphosphatase (ATPase), and relative content of slow and fast myosin in individual soleus fibers. After 1, 2, or 3 weeks of HU, soleus muscle bundles were prepared and stored in skinning solution at -20 C. Single fibers were isolated and mounted between a motor arm and a transducer, and fiber force, V(sub o), and ATPase activity were measured. Fiber myosin content was determined by one-dimensional sodium dodecyl sulfate- (SDS) polyacrylamide gel electrophoresis. After 1, 2, and 3 weeks of HU, soleus fibers exhibited a progressive reduction in fiber diameter (16, 22, and 42%, respectively) and peak force (42, 48, and 7%, respectively). Peak specific tension was significantly reduced after 1 week of HU (18%) and showed no further change in 2-3 weeks of HU. During 1 and 3 wk of HU, fiber V(sub o) and ATPase showed a significant increase. By 3 week, V(sub o) had increased from 1.32 +/- 0.04 to 2.94 +/- 0.17 fiber lengths/s and fiber ATPase from 291 +/- 16 to 1064 +/- 128 micro-M min(sub -1) mm(sub -3). The percent fibers expressing fast myosin heavy chain increased from 4% to 29% by 3 week of HU, and V(sub o) and ATPase activity within a fiber were highly correlated. However, a large population of fibers after 1, 2, and 3 weeks of HU showed increases in V(sub o) and ATPase but displayed the same myosin protein profile on SDS gels as control fibers. The mechanism eliciting increased fiber V(sub o) and ATPase activity was not obvious but may have been due to increases in fast myosin that went undetected on SDS gels and/or other factors unrelated to the myosin filament.

McDonald, K. S.↗

Enhanced protein electrophoresis technique for separating human skeletal muscle myosin heavy chain isoforms

Talmadge and Roy (J. Appl. Physiol. 1993, 75, 2337-2340) previously established a sodium dodecyl sulfate - polyacrylamide gel electrophoresis (SDS-PAGE) protocol for separating all four rat skeletal muscle myosin heavy chain (MHC) isoforms (MHC I, IIa, IIx, IIb); however, when applied to human muscle, the type II MHC isoforms (Ila, IIx) are not clearly distinguished. In this brief paper we describe a modification of the SDS-PAGE protocol which yields distinct and consistent separation of all three adult human MHC isoforms (MHC I, IIa, IIx) in a minigel system. MHC specificity of each band was confirmed by Western blot using three monoclonal IgG antibodies (mAbs) immunoreactive against MHCI (mAb MHCs, Novacastra Laboratories), MHCI+IIa (mAb BF-35), and MHCIIa+IIx (mAb SC-71). Results provide a valuable SDS-PAGE minigel technique for separating MHC isoforms in human muscle without the difficult task of casting gradient gels.

NASA Center JSC↗

The NPOESS Preparatory Project Science Data Segment: Brief Overview

The NPOESS Preparatory Project (NPP) provides remotely-sensed land, ocean, atmospheric, ozone, and sounder data that will serve the meteorological and global climate change scientific communities while also providing risk reduction for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government s future low-Earth orbiting satellite system monitoring global weather and environmental conditions. NPOESS and NPP are a new era, not only because the sensors will provide unprecedented quality and volume of data but also because it is a joint mission of three federal agencies, NASA, NOAA, and DoD. NASA's primary science role in NPP is to independently assess the quality of the NPP science and environmental data records. Such assessment is critical for making NPOESS products the best that they can be for operational use and ultimately for climate studies. The Science Data Segment (SDS) supports science assessment by assuring the timely provision of NPP data to NASA s science teams organized by climate measurement themes. The SDS breaks down into nine major elements, an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. This paper will describe how the NPP SDS will leverage on NASA experience to provide a mission-reliable research capability for science assessment of NPP derived measurements.

Schweiss, Robert J.↗

NASA's NPOESS Preparatory Project Science Data Segment: A Framework for Measurement-based Earth Science Data Systems

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) provides a framework for the future of NASA s distributed Earth science data systems. The NPP SDS performs research and data product assessment while using a fully distributed architecture. The components of this architecture are organized around key environmental data disciplines: land, ocean, ozone, atmospheric sounding, and atmospheric composition. The SDS thus establishes a set of concepts and a working prototypes. This paper describes the framework used by the NPP Project as it enabled Measurement-Based Earth Science Data Systems for the assessment of NPP products.

Schwaller, Mathew R.↗