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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 109 records · Page 6
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NASA NTRS1999

MOLA: The New Approach for Mars Global Cartography

The MGS Orbiter is carrying the high-precision Mars Orbiter Laser Altimeter (MOLA) which, when combined with telemetered latitude data, provides a tie between inertial space and Mars-fixed coordinates to an accuracy of 100 m in latitude/longitude and 10 m in radius (1 sigma), orders of magnitude more accurate than previous global geodetic/ cartographic control data. Over the 2 year MGS mission lifetime, it is expected that over 30,000 MOLA Global Cartographic Control Points will be produced to form the basis for new and re-derived map and geodetic products, key to the analysis of existing and evolving MGS data as well as future Mars exploration.

Duxbury, Thomas C.↗
NASA NTRS2008

The NASA Phoenix 2007 Mars Lander Thruster Calibration Estimator: Design and Validation

The NASA Phoenix 2007 Mars Lander mission, launched in August 2007 on its mission to land near the north pole of Mars in May 2008, had a driving need for entry-corridor delivery precision, which parlayed into stringent requirements on deep space navigation accuracy. This, in turn, necessitated in-cruise calibration of the three-axis thrust force vectors produced by each of the vehicle's four reactioncontrol system (RCS) thrusters during frequent daily low-catalyst-bed-temperature firings done to maintain the 3-axis attitude deadbands. A novel recursive sigmapoint consider-covariance filter was designed, validated and ultimately utilized extensively during flight operations, to estimate the RCS force vectors, per individual thruster. The estimate was achieved through ground-based processing of Deep Space Network (DSN) and telemetered gyroscope data from the spacecraft's inertial measurement unit (IMU), using a novel sigma-point consider filter (SPCF) formulation. During early-cruise active calibration, the spacecraft was flown in attitudes chosen, using this filter, to maximize observability of all thruster axes, to an extent constrained by vehicle thermal and communication considerations. The design of the Phoenix thruster calibration filter, and its validation through processing of archived Mars Odyssey thruster calibration radiometric data, and simulated sets of data, are discussed in this paper. The paper concludes with the formulation of the thruster calibration campaign and a summary of the thruster calibration campaign results. The SPCF algorithm is summarized in the Appendix.

sigma-point filter↗
NASA NTRS1999

Summary Report of Mission Acceleration Measurement for STS-87: Launched November 19, 1997

Two accelerometer systems, the Orbital Acceleration Research Experiment and the Space Acceleration Measurement System, were used to measure and record the microgravity environment of the Orbiter Columbia during the STS-87 mission in November-December 1997. Data from two separate Space Acceleration Measurement System units were telemetered to the ground during the mission and data plots were displayed for investigators of the Fourth United States Microgravity Payload experiments in near real-time using the World Wide Web. Plots generated using Orbital Acceleration Research Experiment data (telemetered to the ground using a tape delay) were provided to the investigators using the World Wide Web approximately twelve hours after data recording. Disturbances in the microgravity environment as recorded by these instruments are grouped by source type: Orbiter systems, on-board activities, payload operations, and unknown sources. The environment related to the Ku-band antenna dither, Orbiter structural modes, attitude deadband collapses, water dump operations, crew sleep, and crew exercise was comparable to the effects of these sources on previous Orbiter missions. Disturbances related to operations of the Isothermal Dendritic Growth Experiment and Space Acceleration Measurement Systems that were not observed on previous missions are detailed. The effects of Orbiter cabin and airlock depressurization and extravehicular activities are also reported for the first time. A set of data plots representing the entire mission is included in the CD-ROM version of this report.

Rogers, Melissa J. B.↗
NASA NTRS1999

Summary Report of Mission Acceleration Measurement for STS-87, Launched November 19, 1997

Two accelerometer systems, the Orbital Acceleration Research Experiment and the Space Acceleration Measurement System, were used to measure and record the microgravity environment of the Orbiter Columbia during the STS-87 mission in November-December 1997. Data from two separate Space Acceleration Measurement System units were telemetered to the ground during the mission and data plots were displayed for investigators of the Fourth United States Microgravity Payload experiments in near real-time using the World Wide Web. Plots generated using Orbital Acceleration Research Experiment data (telemetered to the ground using a tape delay) were provided to the investigators using the World Wide Web approximately twelve hours after data recording. Disturbances in the microgravity environment as recorded by these instruments are grouped by source type: Orbiter systems, on-board activities, payload operations, and unknown sources. The environment related to the Ku-band antenna dither, Orbiter structural modes, attitude deadband collapses, water dump operations, crew sleep, and crew exercise was comparable to the effects of these sources on previous Orbiter missions. Disturbances related to operations of the Isothermal Dendritic Growth Experiment and Space Acceleration Measurement Systems that were not observed on previous missions are detailed. The effects of Orbiter cabin and airlock depressurization and extravehicular activities are also reported for the first time. A set of data plots representing the entire mission is included in the CD-ROM version of this report.

Rogers, Melissa J. B.↗
NASA NTRS1981

airborne data analysis/monitor system

An Airborne Data Analysis/Monitor System (ADAMS), a ROLM 1666 computer based system installed onboard test airplanes used during experimental testing is evaluated. In addition to the 1666 computer, the ADAMS hardware includes a DDC System 90 fixed head disk and a Miltape DD400 floppy disk. Boeing designed a DMA interface to the data acquisition system and an intelligent terminal to reduce system overhead and simplify operator commands. The ADAMS software includes RMX/RTOS and both ROLM FORTRAN and assembly language are used. The ADAMS provides real time displays that enable onboard test engineers to make rapid decisions about test conduct thus reducing the cost and time required to certify new model airplanes, and improved the quality of data derived from the test, leading to more rapid development of improvements resulting in quieter, safer, and more efficient airplanes. The availability of airborne data processing removes most of the weather and geographical restrictions imposed by telemetered flight test data systems. A data base is maintained to describe the airplane, the data acquisition system, the type of testing, and the conditions under which the test is performed.

Stephison, D. B.↗
NASA NTRS2008

NASA Langley's AirSTAR Testbed: A Subscale Flight Test Capability for Flight Dynamics and Control System Experiments

As part of the Airborne Subscale Transport Aircraft Research (AirSTAR) project, NASA Langley Research Center (LaRC) has developed a subscaled flying testbed in order to conduct research experiments in support of the goals of NASA s Aviation Safety Program. This research capability consists of three distinct components. The first of these is the research aircraft, of which there are several in the AirSTAR stable. These aircraft range from a dynamically-scaled, twin turbine vehicle to a propeller driven, off-the-shelf airframe. Each of these airframes carves out its own niche in the research test program. All of the airplanes have sophisticated on-board data acquisition and actuation systems, recording, telemetering, processing, and/or receiving data from research control systems. The second piece of the testbed is the ground facilities, which encompass the hardware and software infrastructure necessary to provide comprehensive support services for conducting flight research using the subscale aircraft, including: subsystem development, integrated testing, remote piloting of the subscale aircraft, telemetry processing, experimental flight control law implementation and evaluation, flight simulation, data recording/archiving, and communications. The ground facilities are comprised of two major components: (1) The Base Research Station (BRS), a LaRC laboratory facility for system development, testing and data analysis, and (2) The Mobile Operations Station (MOS), a self-contained, motorized vehicle serving as a mobile research command/operations center, functionally equivalent to the BRS, capable of deployment to remote sites for supporting flight tests. The third piece of the testbed is the test facility itself. Research flights carried out by the AirSTAR team are conducted at NASA Wallops Flight Facility (WFF) on the Eastern Shore of Virginia. The UAV Island runway is a 50 x 1500 paved runway that lies within restricted airspace at Wallops Flight Facility. The facility provides all the necessary infrastructure to conduct the research flights in a safe and efficient manner. This paper gives a comprehensive overview of the development of the AirSTAR testbed.

Jordan, Thomas L.↗
NASA NTRS1975

ASTP Onboard Voice Transcription

The transcription is presented of the Apollo-Soyuz Test Project voice communications as recorded on the command module data storage equipment. Data from this recorder are telemetered (dumped) to Space Tracking and Data Network sites for retransmission to the Johnson Space Center. The transcript is divided into three columns -- time, speaker, and text. The Greenwich mean time column consists of three two-digit numbers representing hours, minutes, and seconds (e.g., 22 34 14) for the Julian dates shown at the top of the page on which a new day begins. The speaker column indicates the source of a transmission; the text column contains the verbatim transcript of the communications.

Source record↗
NASA NTRS1982

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

Ruedger, W. H.↗
NASA NTRSDate not supplied

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗
NASA NTRSDate not supplied

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗
NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗
NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗
NASA NTRS2007

Forward Technology Solar Cell Experiment First On-Orbit Data

This paper presents first on orbit measured data from the Forward Technology Solar Cell Experiment (FTSCE). FTSCE is a space experiment housed within the 5th Materials on the International Space Station Experiment (MISSE-5). MISSE-5 was launched aboard the Shuttle return to flight mission (STS-114) on July 26, 2005 and deployed on the exterior of the International Space Station (ISS). The experiment will remain in orbit for nominally one year, after which it will be returned to Earth for post-flight testing and analysis. While on orbit, the experiment is designed to measure a 36 point current vs. voltage (IV) curve on each of the experimental solar cells, and the data is continuously telemetered to Earth. The experiment also measures the solar cell temperature and the orientation of the solar cells to the sun. A range of solar cell technologies are included in the experiment including state-of-the-art triple junction InGaP/GaAs/Ge solar cells from several vendors, thin film amorphous Si and CuIn(Ga)Se2 cells, and next-generation technologies like single-junction GaAs cells grown on Si wafers and metamorphic InGaP/InGaAs/Ge triple-junction cells. In addition to FTSCE, MISSE-5 also contains a Thin-Film Materials experiment. This is a passive experiment that will provide data on the effect of the space environment on more than 200 different materials. FTSCE was initially conceived in response to various on-orbit and ground test anomalies associated with space power systems. The Department of Defense (DoD) required a method of rapidly obtaining on orbit validation data for new space solar cell technologies, and NRL was tasked to devise an experiment to meet this requirement. Rapid access to space was provided by the MISSE Program which is a NASA Langley Research Center program. MISSE-5 is a completely self-contained experiment system with its own power generation and storage system and communications system. The communications system, referred to as PCSat, transmits and receives in the Amateur Radio band providing a node on the Amateur Radio Satellite Service. This paper presents an overview of the various aspects of MISSE-5 and a sample of the first measured on orbit data.

Walters, R. J.↗
NASA NTRS1977

Altimeter waveform software design

Techniques are described for preprocessing raw return waveform data from the GEOS-3 radar altimeter. Topics discussed include: (1) general altimeter data preprocessing to be done at the GEOS-3 Data Processing Center to correct altimeter waveform data for temperature calibrations, to convert between engineering and final data units and to convert telemetered parameter quantities to more appropriate final data distribution values: (2) time "tagging" of altimeter return waveform data quantities to compensate for various delays, misalignments and calculational intervals; (3) data processing procedures for use in estimating spacecraft attitude from altimeter waveform sampling gates; and (4) feasibility of use of a ground-based reflector or transponder to obtain in-flight calibration information on GEOS-3 altimeter performance.

Hayne, G. S.↗
NASA NTRS1971

Gravity measured at the Apollo 14 landing site.

The gravity at the Apollo 14 landing site has been determined from the accelerometer data that were telemetered from the lunar module. The values for the lunar gravity measured at the Apollo 11, 12, and 14 sites were reduced to a common elevation and were then compared between sites. A theoretical gravity, based on the assumption of a spherical moon, was computed for each landing site and compared with the observed value. The observed gravity was also used to compute the lunar radius at each landing site.

Nance, R. L.↗
NASA NTRS1981

In-flight jet engine noise measurement system

An instrumentation system in flight tests for noise research is described which utilizes miniature transducers to measure low-amplitude, high-frequency fluctuating pressures in a jet engine mounted under the wing of a turboprop aircraft. The system employs a rotor-mounted FM telemeter to acquire data from eight fan-blade-mounted transducers which are subjected to up to 75,000 g's of loading. Data is transmitted from the rotor to an antenna mounted in the inlet-duct wall using a low-power, close-coupled RF link. The blade pressures and other inlet and stator-vane fluctuating pressures are recorded on airborne, magnetic-tape recorders. The flight instrumentation described also includes PCM techniques to encode and record a variety of quasi-static measurements to provide engine and aircraft performance data. The instrumentation and experimental measurements are of value to an improved understanding of noise sources in jet engines and for the advancement of jet-engine ground noise testing techniques.

Knight, V. H., Jr.↗
NASA NTRS1983

NASA/RAE collaboration on nonlinear control using the F-8C digital fly-by-wire aircraft

A cooperative advanced digital research experiment (CADRE) was established by the National Aeronautics and Space Administration (NASA) and the Royal Aircraft Establishment (RAE), in which nonlinear control algorithms developed by the RAE were tested on the F-8C digital fly-by-wire (DFBW) aircraft based at the Dryden Flight Research Facility. In the initial phase of the collaboration, some variable-gain algorithms, referred to collectively as variable integral control to optimize response (VICTOR) algorithms, were fight tested. With VICTOR, various measures available within the control system are used to vary gains and time-constants within the closed loop and thereby enhance the control capability of the system, while reducing the adverse effects of sensor noise on the control surfaces. A review of design procedures for VICTOR and results of preliminary flight tests are presented. the F-8C aircraft is operated in the remotely augmented vehicle (RAV) mode, with the control laws implemented as FORTRAN programs on a ground-based computer. Pilot commands and sensor information are telemetered to the ground, where the data are processed to form surface commands which are then telemetered to the ground, where the data are processed to form surface commands which are then telemetered back to the aircraft. The RAV mode represents a single-string (simplex) system and is therefore vulnerable to a hardover since comparison monitoring is not possible. Hence, extensive error checking is conducted on both the ground and airborne computers to prevent the development of potentially hazardous situations. Experience with the RAV monitoring and validation procedures is described.

Butler, G. F.↗