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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

The impact of cockpit automation on crew coordination and communication. Volume 1: Overview, LOFT evaluations, error severity, and questionnaire data

The purpose was to examine, jointly, cockpit automation and social processes. Automation was varied by the choice of two radically different versions of the DC-9 series aircraft, the traditional DC-9-30, and the glass cockpit derivative, the MD-88. Airline pilot volunteers flew a mission in the simulator for these aircraft. Results show that the performance differences between the crews of the two aircraft were generally small, but where there were differences, they favored the DC-9. There were no criteria on which the MD-88 crews performed better than the DC-9 crews. Furthermore, DC-9 crews rated their own workload as lower than did the MD-88 pilots. There were no significant differences between the two aircraft types with respect to the severity of errors committed during the Line-Oriented Flight Training (LOFT) flight. The attitude questionnaires provided some interesting insights, but failed to distinguish between DC-9 and MD-88 crews.

Wiener, Earl L.↗
NASA NTRS2017

Horizon Detection for Mars Surface Operations

A new image processing method for automated horizon detection is presented in this paper. This method was developed for the Mars Exploration Rovers mission’s surface operations to aid in determining orbiter visibility periods for downlink data, and is now being considered for all Mars surface missions and for a variety of applications. Starting with images received from Mars rovers or landers, the horizon pixel location is found by (1) obtaining the gradient images using the Sobel operator, (2) calculating the preliminary horizon locations by optimizing the maximum difference between sky and ground regions in the gradient domain, and (3) applying a multi-variable thresholding method. The results are analyzed using a variety of images from the Mars rovers, as an example one dataset’s results were categorized as 94.2% Good, 4.11% Okay, and 1.65% Poor. The pixel location corresponding to the found horizon in an image is converted to azimuth and elevation values using the camera model. The elevation of the terrain surrounding the rover or lander directly affects the duration orbiters are visible for downlink data volume, and when the sun is visible for image quality or solar energy consumption. Having an automated process to detect the elevation of the terrain allows the operation team to better predict the outcome of the plan, reducing heath and safety risks and allowing new operational limits to be defined.

Oij, Stephanie Lynn↗
NASA NTRSDate not supplied

Populating a Graph Database to Run a Usage-Based Discovery Tool

Most dataset discovery tools for Earth Observation data rely on descriptions and other metadata of the datasets, using keyword searches or attribute filtering to determine relevance. However, these descriptions often do not include the potential uses of the data. Thus, a user working on floods will rarely see few if any rainfall datasets show up in such a search. The Usage Based Discovery tool, on the other hand, offers usage instances to the user, either research articles or applications, along with the datasets that those usage instances used. This allows a user, particularly one new to the world of Earth Observation data, to investigate which datasets are used in similar cases. The information that powers Usage-Based Discovery is a graph database of relationships of usage to dataset and usage to topic, allowing the user to narrow their search for similar cases. In order to scale out to a graph database rich enough to provide a satisfactory user experience, we combine manual and automated processes to populate the graph. The initial content of the graph has been seeded primarily via human-aided data curation methods, using sites like Google Scholar. To scale up this effort, we’ve employed crowdsourcing. It is easy for anyone to contribute to our graph using their Open Researcher and Contributor Identifier for authorization. We’re now experimenting with Machine Learning and Natural Language Processing to help automate population of the graph, starting with the classification of research articles by topic. Finding adequate training data in the absence of a comprehensive and open research article API continues to be a significant challenge.

Vincent Inverso↗
NASA NTRS1994

A Software Architecture for Automating Operations Processes

The Operations Engineering Lab (OEL) at JPL has developed a software architecture based on an integrated toolkit approach for simplifying and automating mission operations tasks. The toolkit approach is based on building adaptable, reusable graphical tools that are integrated through a combination of libraries, scripts, and system-level user interface shells. The graphical interface shells are designed to integrate and visually guide a user through the complex steps in an operations process. They provide a user with an integrated system-level picture of an overall process, defining the required inputs and possible outputs through interactive on-screen graphics.

mission↗
NASA NTRS2001

New Data on the Topside Electron Density Distribution

The existing uncertainties about the electron density profiles in the topside ionosphere, i.e., in the height region from hmF2 to approx. 2000 km, require the search for new data sources. The ISIS and Alouette topside sounder satellites from the sixties to the eighties recorded millions of ionograms and most were not analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2001 about 350,000 ionograms have been digitized from the original 7-track analog tapes. These data are available in binary and CDF format from the anonymous ftp site of the National Space Science Data Center. A search site and browse capabilities on CDAWeb assist the scientific usage of these data. All information and access links can be found at http://nssdc.gsfc.nasa.gov/space/isis/isis-status.html. This paper describes the ISIS data restoration effort and shows how the digital ionograms are automatically processed into electron density profiles from satellite orbit altitude (1400 km for ISIS-2) down to the F peak. Because of the large volume of data an automated processing algorithm is imperative. The automatic topside ionogram scaler with true height algorithm TOPIST software developed for this task is successfully scaling approx.70 % of the ionograms. An 'editing process' is available to manually scale the more difficult ionograms. The automated processing of the digitized ISIS ionograms is now underway, producing a much-needed database of topside electron density profiles for ionospheric modeling covering more than one solar cycle. The ISIS data restoration efforts are supported through NASA's Applied Systems and Information Research Program.

Huang, Xue-Qin↗
NASA NTRS1980

Automating the process of estimating spacecraft mass

To help prevent the problem of mass reduction late in a spacecraft development program, the process of estimating spacecraft mass has been formulated in algorithmic form and incorporated in software that will allow trained users to interface with the integral design parameters data base interactively. The software will use historical data to extrapolate future values of a given time-dependent parameter and be manipulated by a dynamic graphics configuration builder. Future expansions of this work promise to automate the entire conceptual mission design process.

Skinner, D. L.↗
NASA NTRS2016

Atmosphere Processing Module Automation and Catalyst Durability Analysis for Mars ISRU Pathfinder

The Mars In-Situ Resource Utilization Pathfinder was designed to create fuel using components found in the planet’s atmosphere and regolith for an ascension vehicle to return a potential sample return or crew return vehicle from Mars. The Atmosphere Processing Module (APM), a subunit of the pathfinder, uses cryocoolers to isolate and collect carbon dioxide from Mars simulant gas. The carbon dioxide is fed with hydrogen into a Sabatier reactor where methane is produced. The APM is currently undergoing the final stages of testing at Kennedy Space Center prior to process integration testing with the other subunits of the pathfinder. The automation software for the APM cryocoolers was tested and found to perform nominally. The catalyst used for the Sabatier reactor was investigated to determine the factors contributing to catalyst failure. The results from the catalyst testing require further analysis, but it appears that the rapid change in temperature during reactor start up or the elevated operating temperature is responsible for the changes observed in the catalyst.

Atmosphere Processing Module↗
NASA NTRS2003

Automating the Processing of Earth Observation Data

NASA s vision for Earth science is to build a "sensor web": an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving this vision will require automation not only in the scheduling of the observations but also in the processing of the resulting data. To address this need, we are developing a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products.

Golden, Keith↗
NASA NTRS2002

Electron Density Profiles of the Topside Ionosphere

The existing uncertainties about the electron density profiles in the topside ionosphere, i.e., in the height region from h,F2 to - 2000 km, require the search for new data sources. The ISIS and Alouette topside sounder satellites from the sixties to the eighties recorded millions of ionograms but most were not analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2001 about 350000 ionograms have been digitized from the original 7-track analog tapes. These data are available in binary and CDF format from the anonymous ftp site of the National Space Science Data Center. A search site and browse capabilities on CDAWeb assist the scientific usage of these data. All information and access links can be found at http://nssdc.gsfc.nasa.gov/space/isis/isis- status.htm1. This paper describes the ISIS data restoration effort and shows how the digital ionograms are automatically processed into electron density profiles from satellite orbit altitude (1400 km for ISIS-2) down to the F peak. Because of the large volume of data an automated processing algorithm is imperative. The TOPside Ionogram Scaler with True height algorithm TOPIST software developed for this task is successfully scaling - 70% of the ionograms. An < > is available to manually scale the more difficult ionograms. The automated processing of the digitized ISIS ionograms is now underway, producing a much-needed database of topside electron density profiles for ionospheric modeling covering more than one solar cycle.

Huang, Xue-Qin↗
NASA NTRS2003

Automated Data Processing as an AI Planning Problem

NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.

Golden, Keith↗
NASA NTRS1988

The evolution of automated launch processing

The NASA Launch Processing System (LPS) to which attention is presently given has arrived at satisfactory solutions for the distributed-computing, good user interface and dissimilar-hardware interface, and automation-related problems that emerge in the specific arena of spacecraft launch preparations. An aggressive effort was made to apply the lessons learned in the 1960s, during the first attempts at automatic launch vehicle checkout, to the LPS. As the Space Shuttle System continues to evolve, the primary contributor to safety and reliability will be the LPS.

Tomayko, James E.↗
NASA NTRS1994

Flexible manufacturing for photonics device assembly

The assembly of photonics devices such as laser diodes, optical modulators, and opto-electronics multi-chip modules (OEMCM), usually requires the placement of micron size devices such as laser diodes, and sub-micron precision attachment between optical fibers and diodes or waveguide modulators (usually referred to as pigtailing). This is a very labor intensive process. Studies done by the opto-electronics (OE) industry have shown that 95 percent of the cost of a pigtailed photonic device is due to the use of manual alignment and bonding techniques, which is the current practice in industry. At Lawrence Livermore National Laboratory, we are working to reduce the cost of packaging OE devices through the use of automation. Our efforts are concentrated on several areas that are directly related to an automated process. This paper will focus on our progress in two of those areas, in particular, an automated fiber pigtailing machine and silicon micro-technology compatible with an automated process.

Lu, Shin-Yee↗
NASA NTRS1992

Qualification of the gritblast assembly and process for the inside diameter of the RSRM forward and aft domes

This gritblast assembly shall be used when refurbishing the Inside Diameter (ID) of RSRM forward and aft domes. Initial blasting is used to remove corrosion and adhesive not removed during the insulation washout. Final blasting is conducted just prior to part finalization in order to remove residual contamination and prepare the ID surface for bonding. The media used in this gritblaster is DuPont Zirclean Blasting Abrasive. It is possible to use other media in this gritblast assembly, however the only facility that has the control capability for this assembly is the Zirclean blast booth. This blast booth can not use other media without the occurrence of contamination. This automated process shall replace the manually controlled gritblasting that is currently in operation. Manual gritblasting does not provide the consistency, control, and safety that an automated process is capable of delivering.

Nolan, Michael J.↗
NASA NTRS1975

Automated space processing payloads study. Volume 2, book 2: Technical report, appendices A through E

Experiment hardware and operational requirements for space shuttle experiments are discussed along with payload and system concepts. Appendixes are included in which experiment data sheets, chamber environmental control and monitoring, method for collection and storage of electrophoretically-separated samples, preliminary thermal evaluation of electromagnetic levitation facilities L1, L2, and L3, and applicable industrial automation equipment are discussed.

Source record↗
NASA NTRS2003

Intelligent Machines in the 21st Century: Automating the Processes of Inference and Inquiry

The last century saw the application of Boolean algebra toward the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines. in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. However, modern intelligent machines work by inferring knowledge using only their pre-programmed prior knowledge and the data provided. They lack the ability to ask questions, or request data that would aid their inferences. Recent advances in understanding the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we identified the algebra of questions as the free distributive algebra, which now allows us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper we describe this logic of inference and inquiry using the mathematics of partially ordered sets and the scaffolding of lattice theory, discuss the far-reaching implications of the methodology, and demonstrate its application with current examples in machine learning. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them to not only make inferences from data, but also decide which question to ask, experiment to perform, or measurement to take given what they have learned and what they are designed to understand.

Knuth, Kevin H.↗
NASA NTRSDate not supplied

NASA biological and physical sciences databases: who’s the FAIRest of them all?

Conceptual models are a key part of the foundation of scientific study. Scientific data discovery and retrieval are often inaccurate and incomplete because these models are not sufficiently well-incorporated into data retrieval systems. Systems often don’t provide the necessary tools to those producing scientific data to fully and unambiguously annotate them and the result is consumers of the data cannot find them efficiently. The capability of data archives to provide these tools to link data to underlying conceptual models is one of dimensions of the recently developed “FAIR” principles (https://www.go-fair.org/fair-principles/ ), and is key to many automated processes being able to operate on these data, particularly analytics involving artificial intelligence. We used an open-source web service to measure the FAIR compliance of the three data archives operated by NASA for the biological and physical sciences: the Life Sciences Data Archive, the Physical Sciences Informatics database, and GeneLab. The service ingests references to data sets in these archives, and then executes domain-non-specific examinations of these data and metadata that test compliance to the FAIR principles. Of the 22 metrics tested, GeneLab passed 11 (50%), and PSI and LSDA each passed 7 (32%). These data were gathered using only one representative data set from each archive and we anticipate variability in results as we continue to apply these metrics to other data. A preliminary study of the failure traces for each metric suggests there is a wide range of effort and complexity in the enhancements required for each system to elevate FAIR compliance, and this is the subject of continued investigation. This information has been and will likely continue to be important information in planning these enhancements, with the goal of increased readiness of the data for automated processes.

database↗