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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

TMBM: Tethered Micro-Balloons on Mars

The use of balloons/aerobots on Mars has been under consideration for many years. Concepts include deployment during entry into the atmosphere from a carrier spacecraft, deployment from a lander, use of super-pressurized systems for long duration flights, 'hot-air' systems, etc. Principal advantages include the ability to obtain high-resolution data of the surface because balloons provide a low-altitude platform which moves relatively slowly. Work conducted within the last few years has removed many of the technical difficulties encountered in deployment and operation of balloons/aerobots on Mars. The concept proposed here (a tethered balloon released from a lander) uses a relatively simple approach which would enable aspects of Martian balloons to be tested while providing useful and potentially unique science results. Tethered Micro-Balloons on Mars (TMBM) would be carried to Mars on board a future lander as a stand-alone experiment having a total mass of one to two kilograms. It would consist of a helium balloon of up to 50 cubic meters that is inflated after landing and initially tethered to the lander. Its primary instrumentation would be a camera that would be carried to an altitude of up to tens of meters above the surface. Imaging data would be transmitted to the lander for inclusion in the mission data stream. The tether would be released in stages allowing different resolutions and coverage. In addition during this staged release a lander camera system may observe the motion of the balloon at various heights above he lander. Under some scenarios upon completion of the primary phase of TMBM operations, the tether would be cut, allowing TMBM to drift away from the landing site, during which images would be taken along the ground.

Sims, M. H.↗
NASA NTRS2010

GSFC Technology Thrusts and Partnership Opportunities

This slide presentation reviews the technology thrusts and the opportunities to partner in developing software in support of the technological advances at the Goddard Space Flight Center (GSFC). There are thrusts in development of end-to-end software systems for mission data systems in areas of flight software, ground data systems, flight dynamic systems and science data systems. The required technical expertise is reviewed, and the supported missions are shown for the various areas given.

Le Moigne, Jacqueline↗
NASA NTRS1976

NASA/ESA CV-990 Spacelab simulation. Appendixes: C, data-handling: Planning and implementation; D, communications; E, mission documentation

Data handling, communications, and documentation aspects of the ASSESS mission are described. Most experiments provided their own data handling equipment, although some used the airborne computer for backup, and one experiment required real-time computations. Communications facilities were set up to simulate those to be provided between Spacelab and the ground, including a downlink TV system. Mission documentation was kept to a minimum and proved sufficient. Examples are given of the basic documents of the mission.

Reller, J. O., Jr.↗
NASA NTRS2011

Apollo Lunar Sample Integration into Google Moon: A New Approach to Digitization

The Google Moon Apollo Lunar Sample Data Integration project is part of a larger, LASER-funded 4-year lunar rock photo restoration project by NASA s Acquisition and Curation Office [1]. The objective of this project is to enhance the Apollo mission data already available on Google Moon with information about the lunar samples collected during the Apollo missions. To this end, we have combined rock sample data from various sources, including Curation databases, mission documentation and lunar sample catalogs, with newly available digital photography of rock samples to create a user-friendly, interactive tool for learning about the Apollo Moon samples

Dawson, Melissa D.↗
NASA NTRS2019

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗
NASA NTRS1983

Behavior of transition-region lines during impulsive solar flares

The emissions observed in lines originating in the transition-region plasma, particularly during impulsive flares, are investigated using data collected by the Ultraviolet Spectrometer and Polarimeter on the Solar Maximum Mission. Data concerning lines from ions such as Si II, C IV, Si IV, O V, and Fe XXI are analyzed. Topics examined include the transition region away from sunspots, oscillatory motions above sunspots, the shape of the transition region, the transition region during flares, and O V and Fe XXI during flare flash phases.

Tandberg-Hanssen, E.↗
NASA NTRS1994

Calibration of TOPEX/POSEIDON at Platform Harvest

We present estimates for the mean bias of the TOPEX/POSEIDON NASA altimeter (ALT) and the Centre National d'Etudes Spatiales altimeter (SSALT) using in-situ data gathered at Platform Harvest during the first 36 cycles of the mission. Data for 21 overflights of the ALT and six overflights of the SSALT have been analyzed. The analysis includes an independent assessment of in-situ measurements of sea level, the radial component of the orbit, wet tropospheric path delay, and ionospheric path delay. (The sign convention used is such that, to correct the geophysical data record values for sea level, add the bias algebraically. Unless otherwise stated, the uncertainty in a given parameter is depicted by +/- sigma(sub x), where sigma(sub x) is the sample standard deviation of x about the mean.) Tide gauges at Harvest provide estimates of sea level with an uncertainty of +/- 1.5 cm. The uncertainty in the radial component of the orbit is estimated to be +/- 1.3 cm. In-situ measurements of tropopsheric path delay at Harvest compare to within +/- 1.3 cm of the TOPEX/POSEIDON microwave radiometer, and in-situ measurements of the ionospheric path delay compare to within -0.4 +/- 0.7 cm of the dual-frequency ALT and 1.1 +/- 0.6 cm of Doppler orbitography and radiopositioning integrated by satellite. We obtain mean bias estimates of -14.5 +/- 2.9 cm for the ALT and +0.9 +/- 3.1 cm for the SSALT (where the uncertainties are based on the standard deviation of the estimated mean (sigma(sub bar x/y), which is derived from sample statistics and estimates for errors that cannot be observed). These results are consistent with independent estimates for the relative bias between the two altimeters. A linear regression applied to the complete set of data shows that there is a discernable secular trend in the time series for the ALT bias estimates. A preliminary analysis of data obtained through cycle 48 suggests that the apparent secular drift may be the result of a poorly sampled annual signal.

Christensen, E. J.↗
NASA NTRS2007

Capabilities of NASA's Space Physics Data Facility as Resources to Enable the Heliophysics Virtual discipline Observatories (VxOs)

SPDF now supports a broad range of data, user services and other activities. These include: CDAWeb current multi-mission data graphics, listings, file subsetting and supersetting by time and parameters; SSCWeb and 3-D Java client orbit graphics, listings and conjunction queries; OMNIWeb 1/5/60 minute interplanetary parameters at Earth; product-level SPASE descriptions of data including holdings of nssdcftp; VSPO SPASE-based heliophysics-wide product site finding and data use;, standard Data format Translation Webservices (DTWS); metrics software and others. These data and services are available through standard user and application webservices interfaces, so middleware services such as the Heliophysics VxOs, and externally-developed clients or services, can readily leverage our data and capabilities. Beyond a short summary of the above, we will then conduct the talk as a conversation to evolving VxO needs and planned approach to leverage such existing and ongoing services.

McGuire, Robert E.↗
NASA NTRS2018

Web-Based Geospatial Visualization of GPM Data with CesiumJS

Advancements in the capabilities of JavaScript frameworks and web browsing technology have made online visualization of large geospatial datasets such as those coming from precipitation satellites viable. These data benefit from being visualized on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS (http://cesiumjs.org), developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. This presentation will describe how CesiumJS has been used in three-dimensional visualization products developed as part of the NASA Precipitation Processing System (PPS) STORM data-order website. Existing methods of interacting with Global Precipitation Measurement (GPM) Mission data primarily focus on two-dimensional static images, whether displaying vertical slices or horizontal surface/height-level maps. These methods limit interactivity with the robust three-dimensional data coming from the GPM core satellite. Integrating the data with CesiumJS in a web-based user interface has allowed us to create the following products. We have linked with the data-order interface an on-the-fly visualization tool for any GPM/partner satellite orbit. A version of this tool also focuses on high-impact weather events. It enables viewing of combined radar and microwave-derived precipitation data on mobile devices and in a way that can be embedded into other websites. We also have used CesiumJS to visualize a method of integrating gridded precipitation data with modeled wind speeds that animates over time. Emphasis in the presentation will be placed on how a variety of technical methods were used to create these tools, and how the flexibility of the CesiumJS framework facilitates creative approaches to interact with the data.

3D↗
NASA NTRS1994

Calibration of TOPEX/Poseidon at Platform Harvest

We present preliminary estimates for the mean bias of the TOPEX/Poseidon NASA altimeter (ALT) and the CNES altimeter (SSALT) using in situ data gathered at platform Harvest during the first 36 cycles of the mission. Data for 21 overflights of the ALT and 3 overflights of the SSALT have been analyzed.

TOPEX/Poseidon↗
NASA NTRS2010

Integration of Apollo Lunar Sample Data into Google Moon

The Google Moon Apollo Lunar Sample Data Integration project is a continuation of the Apollo 15 Google Moon Add-On project, which provides a scientific and educational tool for the study of the Moon and its geologic features. The main goal of this project is to provide a user-friendly interface for an interactive and educational outreach and learning tool for the Apollo missions. Specifically, this project?s focus is the dissemination of information about the lunar samples collected during the Apollo missions by providing any additional information needed to enhance the Apollo mission data on Google Moon. Apollo missions 15 and 16 were chosen to be completed first due to the availability of digitized lunar sample photographs and the amount of media associated with these missions. The user will be able to learn about the lunar samples collected in these Apollo missions, as well as see videos, pictures, and 360 degree panoramas of the lunar surface depicting the lunar samples in their natural state, following collection and during processing at NASA. Once completed, these interactive data layers will be submitted for inclusion into the Apollo 15 and 16 missions on Google Moon.

Dawson, Melissa D.↗
NASA NTRS1993

Mission Requirements and Data Systems Support Forecast

This document was developed by the Flight Mission Support Office and prepared by the Forecast Analysis Section of the Bendix Field Engineering Corporation (BFEC) to provide NASA management with detailed mission information. It is one of a number of sources used in planning Mission Operations and Data Systems resource commitments in support of mission requirements. All mission dates are based on information available as of May 28, 1993.

Source record↗
NASA NTRS1987

Spacelab Data Processing Facility (SLDPF) quality assurance expert systems development

Spacelab Data Processing Facility (SLDPF) expert system prototypes have been developed to assist in the quality assurance of Spacelab and/or Attached Shuttle Payload (ASP) processed telemetry data. SLDPF functions include the capturing, quality monitoring, processing, accounting, and forwarding of mission data to various user facilities. Prototypes for the two SLDPF functional elements, the Spacelab Output Processing System and the Spacelab Input Processing Element, are described. The prototypes have produced beneficial results including an increase in analyst productivity, a decrease in the burden of tedious analyses, the consistent evaluation of data, and the providing of concise historical records.

Kelly, Angelita C.↗
NASA NTRS2001

Communication System Architecture for Planetary Exploration

Future human missions to Mars will require effective communications supporting exploration activities and scientific field data collection. Constraints on cost, size, weight and power consumption for all communications equipment make optimization of these systems very important. These information and communication systems connect people and systems together into coherent teams performing the difficult and hazardous tasks inherent in planetary exploration. The communication network supporting vehicle telemetry data, mission operations, and scientific collaboration must have excellent reliability, and flexibility.

Braham, Stephen P.↗
NASA NTRS2010

Photon Counting Using Edge-Detection Algorithm

New applications such as high-datarate, photon-starved, free-space optical communications require photon counting at flux rates into gigaphoton-per-second regimes coupled with subnanosecond timing accuracy. Current single-photon detectors that are capable of handling such operating conditions are designed in an array format and produce output pulses that span multiple sample times. In order to discern one pulse from another and not to overcount the number of incoming photons, a detection algorithm must be applied to the sampled detector output pulses. As flux rates increase, the ability to implement such a detection algorithm becomes difficult within a digital processor that may reside within a field-programmable gate array (FPGA). Systems have been developed and implemented to both characterize gigahertz bandwidth single-photon detectors, as well as process photon count signals at rates into gigaphotons per second in order to implement communications links at SCPPM (serial concatenated pulse position modulation) encoded data rates exceeding 100 megabits per second with efficiencies greater than two bits per detected photon. A hardware edge-detection algorithm and corresponding signal combining and deserialization hardware were developed to meet these requirements at sample rates up to 10 GHz. The photon discriminator deserializer hardware board accepts four inputs, which allows for the ability to take inputs from a quadphoton counting detector, to support requirements for optical tracking with a reduced number of hardware components. The four inputs are hardware leading-edge detected independently. After leading-edge detection, the resultant samples are ORed together prior to deserialization. The deserialization is performed to reduce the rate at which data is passed to a digital signal processor, perhaps residing within an FPGA. The hardware implements four separate analog inputs that are connected through RF connectors. Each analog input is fed to a high-speed 1-bit comparator, which digitizes the input referenced to an adjustable threshold value. This results in four independent serial sample streams of binary 1s and 0s, which are ORed together at rates up to 10 GHz. This single serial stream is then deserialized by a factor of 16 to create 16 signal lines at a rate of 622.5 MHz or lower for input to a high-speed digital processor assembly. The new design and corresponding hardware can be employed with a quad-photon counting detector capable of handling photon rates on the order of multi-gigaphotons per second, whereas prior art was only capable of handling a single input at 1/4 the flux rate. Additionally, the hardware edge-detection algorithm has provided the ability to process 3-10 higher photon flux rates than previously possible by removing the limitation that photoncounting detector output pulses on multiple channels being ORed not overlap. Now, only the leading edges of the pulses are required to not overlap. This new photon counting digitizer hardware architecture supports a universal front end for an optical communications receiver operating at data rates from kilobits to over one gigabit per second to meet increased mission data volume requirements.

Gin, Jonathan W.↗
NASA NTRS2010

The Lunar Mapping and Modeling Project Update

The Lunar Mapping and Modeling Project (LMMP) is managing the development of a suite of lunar mapping and modeling tools and data products that support lunar exploration activities, including the planning, design, development, test, and operations associated with crewed and/or robotic operations on the lunar surface. In addition, LMMP should prove to be a convenient and useful tool for scientific analysis and for education and public outreach (E/PO) activities. LMMP will utilize data predominately from the Lunar Reconnaissance Orbiter, but also historical and international lunar mission data (e.g. Lunar Prospector, Clementine, Apollo, Lunar Orbiter, Kaguya, and Chandrayaan-1) as available and appropriate. LMMP will provide such products as image mosaics, DEMs, hazard assessment maps, temperature maps, lighting maps and models, gravity models, and resource maps. We are working closely with the LRO team to prevent duplication of efforts and ensure the highest quality data products. A beta version of the LMMP software was released for limited distribution in December 2009, with the public release of version 1 expected in the Fall of 2010.

Noble, S.↗
NASA NTRS2016

The Polarimeter for Relativistic Astrophysical X-ray Sources

The Polarimeter for Relativistic Astrophysical X-ray Sources (PRAXyS) is one of three Small Explorer (SMEX) missions selected by NASA for Phase A study, with a launch date in 2020. The PRAXyS Observatory exploits grazing incidence X-ray mirrors and Time Projection Chamber Polarimeters capable of measuring the linear polarization of cosmic X-ray sources in the 2-10 keV band. PRAXyS combines well-characterized instruments with spacecraft rotation to ensure low systematic errors. The PRAXyS payload is developed at the Goddard Space Flight Center with the Johns Hopkins University Applied Physics Laboratory, University of Iowa, and RIKEN (JAXA) collaborating on the Polarimeter Assembly. The LEOStar-2 spacecraft bus is developed by Orbital ATK, which also supplies the extendable optical bench that enables the Observatory to be compatible with a Pegasus class launch vehicle. A nine month primary mission will provide sensitive observations of multiple black hole and neutron star sources, where theory predicts polarization is a strong diagnostic, as well as exploratory observations of other high energy sources. The primary mission data will be released to the community rapidly and a Guest Observer extended mission will be vigorously proposed.

Small Explorer↗