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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 NTRS1995

A Mars Micro-Meteorological Station Mission

The Mars Micro-Meteorological Station (Micro-Met) Mission is designed to provide the global surface pressure measurements required to help characterize the martian general circulation and climate system. Measurements of surface pressure distributed both spatially and temporally, coupled with simultaneous measurements from orbit, will enable the determination of the general circulation, structure and driving factors of the martian atmosphere as well as the seasonal CO2 cycle. The influence of these atmospheric factors will in turn provide insight into the overall martian climate system. With the science objective defined as the long term (at least one Mars year) globally distributed measurement of surface atmospheric pressure, a straightforward, near term and low cost network mission has been designed. The Micro-Met mission utilizes a unique silicon micro-machined pressure sensor coupled with a robust and lightweight surface station to deliver to Mars 16 Micro-Met stations via a Med-Lite launch vehicle. The battery powered Micro-Met surface stations are designed to autonomously measure, record and transmit the science data via a UHF relay satellite. Entry, descent and landing is provided by an aeroshell with a new lightweight ceramic thermal protection system, a parachute and an impact absorbing structure. The robust lander is capable of surviving the landing loads imposed by the high altitude landing sites required in a global network. By trading the ability to make many measurements at a single site for the ability to make a single measurement at several sites, the Micro-Met mission design satisfies the requirement for truly global meteorological science.

Merrihew, Steven C.↗
NASA NTRS2017

NASA's Optical Program on Ascension Island: Bringing MCAT to Life as the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT)

In June 2015, the construction of the Meter Class Autonomous Telescope was completed and MCAT saw the light of the stars for the first time. In 2017, MCAT was newly dedicated as the Eugene Stansbery-MCAT telescope by NASA's Orbital Debris Program Office (ODPO), in honor of his inspiration and dedication to this newest optical member of the NASA ODPO. Since that time, MCAT has viewed the skies with one engineering camera and two scientific cameras, and the ODPO optical team has begun the process of vetting the entire system. The full system vetting includes verification and validation of: (1) the hardware comprising the system (e.g. the telescopes and its instruments, the dome, weather systems, all-sky camera, FLIR cloud infrared camera, etc.), (2) the custom-written Observatory Control System (OCS) master software designed to autonomously control this complex system of instruments, each with its own control software, and (3) the custom written Orbital Debris Processing software for post-processing the data. ES-MCAT is now capable of autonomous observing to include Geosynchronous survey, TLE (Two-line element) tracking of individual catalogued debris at all orbital regimes (Low-Earth Orbit all the way to Geosynchronous (GEO) orbit), tracking at specified non-sidereal rates, as well as sidereal rates for proper calibration with standard stars. Ultimately, the data will be used for validation of NASA's Orbital Debris Engineering Model, ORDEM, which aids in engineering designs of spacecraft that require knowledge of the orbital debris environment and long-term risks for collisions with Resident Space Objects (RSOs).

Lederer, S. M.↗
NASA NTRS2007

Development of an Airborne Molecular Direct Detection Doppler Lidar for Tropospheric Wind Profiling

Global measurement of tropospheric winds is a key measurement for understanding atmospheric dynamics and improving numerical weather prediction. Global wind profiles remain a high priority for the operational weather community and also for a variety of research applications including studies of the global hydrologic cycle and transport studies of aerosols and trace species. In addition to space based winds, high altitude airborne Doppler lidar systems flown on research aircraft, UAV's or other advanced sub-orbital platforms would be of great scientific benefit for studying mesoscale dynamics and storm systems such as hurricanes. The Tropospheric Wind Lidar Technology Experiment (TWiLiTE) is a three year program to advance the technology readiness level of the key technologies and subsystems of a molecular direct detection wind lidar system by validating them, at the system level, in an integrated airborne lidar system. The TWiLiTE Doppler lidar system is designed for autonomous operation on the WB57, a high altitude aircraft operated by NASA Johnson. The WE357 is capable of flying well above the midlatitude tropopause so the downward looking lidar will measure complete profiles of the horizontal wind field through the lower stratosphere and the entire troposphere. The completed system will have the capability to profile winds in clear air from the aircraft altitude of 18 km to the surface with 250 m vertical resolution and < 3 mis velocity accuracy. Progress in technology development and status of the instrument design will be presented.

Gentry, Bruce↗
NASA NTRSDate not supplied

Using Coordinated, Multi-Agent Platforms for Dynamic Ocean Worlds Science

Planetary science missions have the opportunity to enhance science return through deployment of autonomous capabilities designed to dynamically respond to new information. Future outer solar system missions to ocean worlds in particular would benefit from this technology - intelligent science payloads (ISP) - because it would allow for a coordinated, near real-time response to ephemeral ‘events’ such as plumes, tectonism, surface implantation, volatile releases, thermal and magnetic anomalies, or radiation, as well as increasing the cadence and coverage of data collection. Prioritization and decision-making frameworks from ISP could be deployed at various scales - from analysis onboard a spacecraft with multiple instruments – to coordinated analyses among separate spacecraft in an e.g., distributed systems mission (DSM) composed of multiple SmallSats. Goddard’s Intelligent Science Payload team is developing an agile autonomous architecture for an icy ocean worlds DSM concept. Our goals are to coordinate data collection and onboard data analysis, and to make autonomous decisions for new data collection and analysis based on science priorities between multiple spacecraft with variable instrumentation and orbits. We use a range of data analysis tools to coordinate the DSM response, spanning from observations of data over a specified threshold to more computationally intensive machine learning algorithms (ML). ML algorithms here currently focus on determining the composition of an ocean world using mass spectrometry, and specifically methods for understanding ‘novelties’ and potential biosignatures. These algorithms could be used to quickly process and analyze onboard data that would be significantly delayed in downlink due to long communication delays for outer solar system missions in order to make dynamic science observations. Our ocean worlds case study ISP architecture is intended as an ‘agile’ and modular framework that could be used as a whole or as particular modules based on mission needs.

Distributed Systems↗
NASA NTRS1987

Integrated analysis and applications

A select overview is provided of ongoing research focusing on the development and verification of integrated structural analysis and optimal design capabilities for advanced aerospace propulsion and power systems. Subjects discussed include the following: (1) Composites - analytical models (composite mechanics), integrated computational methods, and characterization of composite structural response and durability for resin-, metal-, and ceramic-matrix systems; (2) Advanced inelastic analysis - algorithm/numerical methods for more accurate and efficient analysis; (3) Constitutive modeling - theoretical formulation and characterization of thermoviscoplastic material behavior; (4) Computational simulation - engine structures from components to assembly, and up to an entire engine system subjected to simulated test-stand and mission load histories; (5) Probabilistic structural analysis - quantification of the effects of uncertainty in geometry, material, loads, and boundary conditions on structural response for true reliability assessment; and (6) Interdisciplinary optimization - incorporation of mathematical optimization and multidisciplinary analyses to provide streamlined, autonomous optimal design systems.

Hopkins, Dale A.↗
NASA NTRS2006

The Tropospheric Wind Lidar Technology Experiment (TWiLiTE): An Airborne Direct Detection Doppler Lidar Instrument Development Program

Global measurement of tropospheric winds is a key measurement for understanding atmospheric dynamics and improving numerical weather prediction. Global wind profiles remain a high priority for the operational weather community and also for a variety of research applications including studies of the global hydrologic cycle and transport studies of aerosols and trace species. In addition to space based winds, a high altitude airborne system flown on UAV or other advanced platforms would be of great interest for studying mesoscale dynamics and hurricanes. The Tropospheric Wind Lidar Technology Experiment (TWiLiTE) project was selected in 2005 by the NASA Earth Sun Technology Office as part of the Instrument Incubator Program. TWiLiTE will leverage significant research and development investments in key technologies made in the past several years. The primary focus will be on integrating these sub-systems into a complete molecular direct detection Doppler wind lidar system designed for autonomous operation on a high altitude aircraft, such as the NASA WB57, so that the nadir viewing lidar will be able to profile winds through the full troposphere. TWiLiTE is a collaboration involving scientists and technologists from NASA Goddard, NOAA ESRL, Utah State University Space Dynamics Lab and industry partners Michigan Aerospace Corporation and Sigma Space Corporation. NASA Goddard and it's partners have been at the forefront in the development of key lidar technologies (lasers, telescopes, scanning systems, detectors and receivers) required to enable spaceborne global wind lidar measurement. The TWiLiTE integrated airborne Doppler lidar instrument will be the first demonstration of a airborne scanning direct detection Doppler lidar and will serve as a critical milestone on the path to a fixture spaceborne tropospheric wind system. The completed system will have the capability to profile winds in clear air from the aircraft altitude of 18 h to the surface with 250 m vertical resolution and less than 2 meters per second velocity accuracy. The instrument design, technologies and predicted performance will be presented.

Gentry, Bruce↗
NASA NTRS2015

An Imaging System for Satellite Hypervelocity Impact Debris Characterization

This paper discusses the design of an automated imaging system for size characterization of debris produced by the DebriSat hypervelocity impact test. The goal of the DebriSat project is to update satellite breakup models. A representative LEO satellite, DebriSat, was constructed and subjected to a hypervelocity impact test. The impact produced an estimated 85,000 debris fragments. The size distribution of these fragments is required to update the current satellite breakup models. An automated imaging system was developed for the size characterization of the debris fragments. The system uses images taken from various azimuth and elevation angles around the object to produce a 3D representation of the fragment via a space carving algorithm. The system consists of N point-and-shoot cameras attached to a rigid support structure that defines the elevation angle for each camera. The debris fragment is placed on a turntable that is incrementally rotated to desired azimuth angles. The number of images acquired can be varied based on the desired resolution. Appropriate background and lighting is used for ease of object detection. The system calibration and image acquisition process are automated to result in push-button operations. However, for quality assurance reasons, the system is semi-autonomous by design to ensure operator involvement. This paper describes the imaging system setup, calibration procedure, repeatability analysis, and the results of the debris characterization.

Moraguez, Matthew↗
NASA NTRS2018

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗
NASA NTRS1993

Miniature wide field-of-view star trackers for spacecraft attitude sensing and navigation

Introducing a family of miniature, wide field-of-view star trackers for low cost, high performance spacecraft attitude determination and navigation applications. These devices, derivative of the WFOV Star Tracker Camera developed cooperatively by OCA Applied Optics and the Lawrence Livermore National Laboratory for the Brilliant Pebbles program, offer a suite of options addressing a wide range of spacecraft attitude measurement and control requirements. These sensors employ much wider fields than are customary (ranging between 20 and 60 degrees) to assure enough bright stars for quick and accurate attitude determinations without long integration intervals. The key benefit of this approach are light weight, low power, reduced data processing loads and high information carrier rates for wide ACS bandwidths. Devices described range from the proven OCA/LLNL WFOV Star Tracker Camera (a low-cost, space-qualified star-field imager utilizing the spacecraft's own computer and centroiding and position-finding), to a new autonomous subsystem design featuring dual-redundant cameras and completely self-contained star-field data processing with output quaternion solutions accurate to 100 micro-rad, 3 sigma, for stand-alone applications.

Mccarty, William↗
NASA NTRS1994

Situational reaction and planning

One problem faced in designing an autonomous mobile robot system is that there are many parameters of the system to define and optimize. While these parameters can be obtained for any given situation determining what the parameters should be in all situations is difficult. The usual solution is to give the system general parameters that work in all situations, but this does not help the robot to perform its best in a dynamic environment. Our approach is to develop a higher level situation analysis module that adjusts the parameters by analyzing the goals and history of sensor readings. By allowing the robot to change the system parameters based on its judgement of the situation, the robot will be able to better adapt to a wider set of possible situations. We use fuzzy logic in our implementation to reduce the number of basic situations the controller has to recognize. For example, a situation may be 60 percent open and 40 percent corridor, causing the optimal parameters to be somewhere between the optimal settings for the two extreme situations.

Yen, John↗
NASA NTRS1995

Site testing Antarctica for astronomy

The Antarctic Plateau provides the preeminent sites on the surface of the Earth for many types of astronomical observation. We have embarked on a site testing program to quantify the ultimate sensitivity levels achievable. The program is now in operation at the South Pole, where an infrared sky brightness monitor and micro-thermal temperature sensors have been deployed. We plan to extend these measurements, first at the Pole, and then to the highest parts of the plateau, Domes Argus and Circe. The latter will involve adapting an 'automated geophysical observatory,' a mobile laboratory designed for autonomous operation on the plateau, for astrophysical purposes.

Burton, Michael G.↗
NASA NTRS1996

Hybrid Architectures and Their Impact on Intelligent Design

In this presentation we investigate a novel framework for the design of autonomous fuzzy intelligent systems. The system integrates the following modules into a single autonomous entity: (1) a fuzzy expert system; (2) artificial neural network; (3) genetic algorithm; and (4) case-base reasoning. We describe the integration of these units into one intelligent structure and discuss potential applications.

Kandel, Abe↗
NASA NTRS1998

STS-90 Day 13 Highlights

On this thirteenth day of the STS-90 mission, the flight crew, Cmdr. Richard A. Searfoss, Pilot Scott D. Altman, and Mission Specialists Richard M. Linnehan, Dafydd Rhys Williams and Kathryn P. Hire, and Payload Specialists Jay C. Buckey and James A. Pawelczyk once agian take part in a variety of human autonomic experiments designed to examine blood pressure regulation in microgravity. Crew members repeat an experiment in which they use an innovative technique called microneurography. This involves placing a very fine needle in a nerve just below the knee, allowing nerve signals traveling from the brain to the blood vessels to be measured directly while the cardiovascular system is challenged using the Lower Body Negative Pressure device. LBNP is a hi-tech canister that pulls bodily fluids into the lower extremities, simulating the effect of standing on Earth.

Source record↗
NASA NTRS1998

STS-90 Day 12 Highlights

On this twelth day of the STS-90 mission, the flight crew, Cmdr. Richard A. Searfoss, Pilot Scott D. Altman, and Mission Specialists Richard M. Linnehan, Dafydd Rhys Williams and Kathryn P. Hire, and Payload Specialists Jay C. Buckey and James A. Pawelczyk continue their investigations into how the human nervous system adapts to the weightlessness of space. Buckey and Pawelczyk take part in a variety of autonomic experiments designed to examine blood pressure regulation in microgravity. The test uses a special device resembling a hi-tech sack to place a stress on the cardiovascular system similar to that experienced when standing in Earth's gravity.

Source record↗
NASA NTRS2004

Results of the Magnetometer Navigation (MAGNAV) Inflight Experiment

The Magnetometer Navigation (MAGNAV) algorithm is currently running as a flight experiment as part of the Wide Field Infrarad Explorer Post-Science Engineer- ing Testbed. Initialization of MAGNAV occured on September 4, 2004. MAGNAV is designed to autonomously estimate the spacecraft orbit, attitude, and rate using magnetometer and sun sensor data. Since the earth s magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computed magnetic field and measured magnetic field components, as measured by the magnetometer throughout the entire spacecraft orbit, are a function of the spacecraft trajectory and attitude errors. Therefore, these errors are used to estimate both trajec- tory and attitude. In addition, the time rate of change of the magnetic field vector is used to estimate the spacecraft rotation rate. The estimation of the attitude and tra- jectory is augmented with the rate estimation into an Extended Kalman filter blended with a pseudc-linear Kalman filter. Sun sensor data is also used to improve the accu- racy and observability of the attitude and rate estimates. This test serves to validate MAGNAV as a single low cost navigation system which utilizes reliable, flight qualified sensors. MAGNAV is intended as a backup algorithm, an initialization algorithm, or possibly a prime navigation algorithm for a mission with coarse constraints.

Thienel, Julie↗
NASA NTRS2004

Results of the Magnetometer Navigation (MAGNAV)lnflight Experiment

The Magnetometer Navigation (MAGNAV) algorithm is currently running as a flight experiment as part of the Wide Field Infrared Explorer (WIRE) Post-Science Engineering Testbed. Initialization of MAGNAV occurred on September 4, 2003. MAGNAV is designed to autonomously estimate the spacecraft orbit, attitude, and rate using magnetometer and sun sensor data. Since the Earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computed magnetic field and measured magnetic field components, as measured by the magnetometer throughout the entire spacecraft orbit, are a function of the spacecraft trajectory and attitude errors. Therefore, these errors are used to estimate both trajectory and attitude. In addition, the time rate of change of the magnetic field vector is used to estimate the spacecraft rotation rate. The estimation of the attitude and trajectory is augmented with the rate estimation into an Extended Kalman filter blended with a pseudo-linear Kalman filter. Sun sensor data is also used to improve the accuracy and observability of the attitude and rate estimates. This test serves to validate MAGNAV as a single low cost navigation system which utilizes reliable, flight qualified sensors. MAGNAV is intended as a backup algorithm, an initialization algorithm, or possibly a prime navigation algorithm for a mission with coarse requirements. Results from the first six months of operation are presented.

Thienel, Julie K.↗
NASA NTRS2003

Automating planetary mission operations

In this paper, we describe the elements of a semi-autonomous system designed to provide instrument health, pointing, and data in a cost effective fashion.

automation parallel processing↗
NASA NTRS2006

Automated Classification of Thermal Infrared Spectra Using Self-organizing Maps

Existing and planned space missions to a variety of planetary and satellite surfaces produce an ever increasing volume of spectral data. Understanding the scientific informational content in this large data volume is a daunting task. Fortunately various statistical approaches are available to assess such data sets. Here we discuss an automated classification scheme based on Kohonen Self-organizing maps (SOM) we have developed. The SUM process produces an output layer were spectra having similar properties lie in close proximity to each other. One major effort is partitioning this output layer into appropriate regions. This is prefonned by defining dosed regions based upon the strength of the boundaries between adjacent cells in the SOM output layer. We use the Davies-Bouldin index as a measure of the inter-class similarities and intra-class dissimilarities that determines the optimum partition of the output layer, and hence number of SOM clusters. This allows us to identify the natural number of clusters formed from the spectral data. Mineral spectral libraries prepared at Arizona State University (ASU) and John Hopkins University (JHU) are used to test and evaluate the classification scheme. We label the library sample spectra in a hierarchical scheme with class, subclass, and mineral group names. We use a portion of the spectra to train the SOM, i.e. produce the output layer, while the remaining spectra are used to test the SOM. The test spectra are presented to the SOM output layer and assigned membership to the appropriate cluster. We then evaluate these assignments to assess the scientific meaning and accuracy of the derived SOM classes as they relate to the labels. We demonstrate that unsupervised classification by SOMs can be a useful component in autonomous systems designed to identify mineral species from reflectance and emissivity spectra in the therrnal IR.

Roush, Ted L.↗