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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Logic programming and metadata specifications

Artificial intelligence (AI) ideas and techniques are critical to the development of intelligent information systems that will be used to collect, manipulate, and retrieve the vast amounts of space data produced by 'Missions to Planet Earth.' Natural language processing, inference, and expert systems are at the core of this space application of AI. This paper presents logic programming as an AI tool that can support inference (the ability to draw conclusions from a set of complicated and interrelated facts). It reports on the use of logic programming in the study of metadata specifications for a small problem domain of airborne sensors, and the dataset characteristics and pointers that are needed for data access.

Lopez, Antonio M., Jr.↗
NASA NTRS1993

Automated inspection of solder joints for surface mount technology

Researchers at NASA/GSFC evaluated various automated inspection systems (AIS) technologies using test boards with known defects in surface mount solder joints. These boards were complex and included almost every type of surface mount device typical of critical assemblies used for space flight applications: X-ray radiography; X-ray laminography; Ultrasonic Imaging; Optical Imaging; Laser Imaging; and Infrared Inspection. Vendors, representative of the different technologies, inspected the test boards with their particular machine. The results of the evaluation showed limitations of AIS. Furthermore, none of the AIS technologies evaluated proved to meet all of the inspection criteria for use in high-reliability applications. It was found that certain inspection systems could supplement but not replace manual inspection for low-volume, high-reliability, surface mount solder joints.

Savage, Robert M.↗
NASA NTRS1992

The activities of comets related to their aging and origin

Attention is given to two indices developed for the purpose of comparing the natures of various classes of comets: the Activity Index (AI), which measures the inherent magnitude increase in brightness from great solar distances to maximum near the perihelion, and the Volatility Index (VI), which measures the variation in magnitude near the perihelion. AI determinations are made for 32 long-period (LP) comets and for 14 short-period (SP). The range of values of AI is of the order of 3 to 10 magnitudes with a median of about 6. No fading with aging among the LP comets was found. No systematic change with period occurs for the VI index. Weak correlations are found with the gas/dust ratio of comets. No correlations are discovered between the two indices, nor of either index with near-perihelion magnitudes or orbital inclination.

Whipple, Fred L.↗
NASA NTRS1991

Search-based model identification of smart-structure damage

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Glass, B. J.↗
NASA NTRS1990

Space Station module Power Management And Distribution (PMAD) system

This project consists of several tasks which are unified toward experimentally demonstrating the operation of a highly autonomous, user-supportive power management and distribution system for Space Station Freedom (SSF) habitation/laboratory modules. This goal will be extended to a demonstration of autonomous, cooperative power system operation for the whole SSF power system through a joint effort with NASA's Lewis Research Center, using their Autonomous Power System. Short term goals for the space station module power management and distribution include having an operational breadboard reflecting current plans for SSF, improving performance of the system communications, and improving the organization and mutability of the artificial intelligence (AI) systems. In the middle term, intermediate levels of autonomy will be added, user interfaces will be modified, and enhanced modeling capabilities will be integrated in the system. Long term goals involve conversion of all software into Ada, vigorous verification and validation efforts and, finally, seeing an impact of this research on the operation of SSF. Conversion of the system to a DC Star configuration is now in progress, and should be completed by the end of October, 1989. This configuration reflects the latest SSF module architecture. Hardware is now being procured which will improve system communications significantly. The Knowledge-Based Management System (KBMS) is initially developed and the rules from FRAMES have been implemented in the KBMS. Rules in the other two AI systems are also being grouped modularly, making them more tractable, and easier to eventually move into the KBMS. Adding an intermediate level of autonomy will require development of a planning utility, which will also be built using the KBMS. These changes will require having the user interface for the whole system available from one interface. An Enhanced Model will be developed, which will allow exercise of the system through the interface without requiring all of the power hardware to be operational. The functionality of the AI systems will continue to be advanced, including incipient failure detection. Ada conversion will begin with the lowest level processor (LLP) code. Then selected pieces of the higher level functionality will be recorded in Ada and, where possible, moved to the LLP level. Validation and verification will be done on the Ada code, and will complete sometimes after completion of the Ada conversion.

Walls, Bryan↗
NASA NTRS1990

ART/Ada and CLIPS/Ada

Although they have reached a point of commercial viability, expert systems were originally developed in artificial intelligence (AI) research environments. Many of the available tools still work best in such environments. These environments typically utilize special hardware such as LISP machines and relatively unfamiliar languages such as LISP or Prolog. Space Station applications will require deep integration of expert system technology with applications developed in conventional languages, specifically Ada. The ability to apply automation to Space Station functions could be greatly enhanced by widespread availability of state-of-the-art expert system tools based on Ada. Although there have been some efforts to examine the use of Ada for AI applications, there are few, if any, existing products which provide state-of-the-art AI capabilities in an Ada tool. The goal of the ART/Ada Design Project is to conduct research into the implementation in Ada of state-of-the-art hybrid expert systems building tools (ESBT's). This project takes the following approach: using the existing design of the ART-IM ESBT as a starting point, analyze the impact of the Ada language and Ada development methodologies on that design; redesign the system in Ada; and analyze its performance. The research project will attempt to achieve a comprehensive understanding of the potential for embedding expert systems in Ada systems for eventual application in future Space Station Freedom projects. During Phase 1 of the project, initial requirements analysis, design, and implementation of the kernel subset of ART-IM functionality was completed. During Phase 2, the effort has been focused on the implementation and performance analysis of several versions with increasing functionality. Since production quality ART/Ada tools will not be available for a considerable time, and additional subtask of this project will be the completion of an Ada version of the CLIPS expert system shell developed by NASA. This tool will provide full syntactic compatibility with any eventual products of the ART/Ada design while allowing SSFP developers early access to this technology.

Culbert, Chris↗
NASA NTRS1993

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Wang, Lui↗
NASA NTRS1990

CLIPS on the NeXT computer

This paper discusses the integration of CLIPS into a hybrid expert system neural network AI tool for the NeXT computer. The main discussion is devoted to the joining of these two AI paradigms in a mutually beneficial relationship. We conclude that expert systems and neural networks should not be considered as competing AI implementation methods, but rather as complimentary components of a whole.

Charnock, Elizabeth↗
NASA NTRS1993

NASA Automatic Information Security Handbook

This handbook details the Automated Information Security (AIS) management process for NASA. Automated information system security is becoming an increasingly important issue for all NASA managers and with rapid advancements in computer and network technologies and the demanding nature of space exploration and space research have made NASA increasingly dependent on automated systems to store, process, and transmit vast amounts of mission support information, hence the need for AIS systems and management. This handbook provides the consistent policies, procedures, and guidance to assure that an aggressive and effective AIS programs is developed, implemented, and sustained at all NASA organizations and NASA support contractors.

Source record↗
NASA NTRS1998

Formal Modeling of Multi-Agent Systems using the Pi-Calculus and Epistemic Logic

Multi-agent systems have become important recently in computer science, especially in artificial intelligence (AI). We allow a broad sense of agent, but require at least that an agent has some measure of autonomy and interacts with other agents via some kind of agent communication language. We are concerned in this paper with formal modeling of multi-agent systems, with emphasis on communication. We propose for this purpose to use the pi-calculus, an extension of the process algebra CCS. Although the literature on the pi-calculus refers to agents, the term is used there in the sense of a process in general. It is our contention, however, that viewing agents in the AI sense as agents in the pi-calculus sense affords significant formal insight. One formalism that has been applied to agents in the AI sense is epistemic logic, the logic of knowledge. The success of epistemic logic in computer science in general has come in large part from its ability to handle concepts of knowledge that apply to groups. We maintain that the pi-calculus affords a natural yet rigorous means by which groups that are significant to epistemic logic may be identified, encapsulated, structured into hierarchies, and restructured in a principled way. This paper is organized as follows: Section 2 introduces the pi-calculus; Section 3 takes a scenario from the classical paper on agent-oriented programming [Sh93] and translates it into a very simple subset of the n-calculus; Section 4 then shows how more sophisticated features of the pi-calculus may bc brought into play; Section 5 discusses how the pi-calculus may be used to define groups for epistemic logic; and Section 6 is the conclusion.

Rorie, Toinette↗
NASA NTRS2004

Cloud-Aerosol Interaction and Its Impact on the Onset of the East Asian Summer Monsoon

Effect of aerosols from biomass burning on the early development of East Asian monsoon is investigated using various satellites and in situ observations including TOMS Aerosol Index (AI). GPCP precipitation, ISCCP cloud cover, and GISS surface air temperature. Based on TRMM fire produce and mean winds fields at 85Omb. we identified the source and interaction regions of aerosols and investigated aerosol-cloud-precipitation characteristics in those regions. During March-April, northern Thailand, Myanmar. and Laos are major source of smoke from the combustion of agricultural waste. Excessive smoke. represented by high AI, is observed especially during dry and cloud-free year. On the other hand. there is no ground source of smoke in the interaction region. The most of aerosols in this area are believed to be transported from the source region. AI is appeared to be correlated with more clouds and less precipitation in interaction region. It suggests that the aerosol-cloud interaction can alter the distribution of cloud and the characteristics of regional hydrology. Aerosol-induced changes in atmospheric stability and associated circulation turns out to be very important to pre-monsoon rainfall pattern in southern China. Prolonged biomass burning is especially effective in changing rainfall pattern during April and May. Results suggest that excessive aerosol transported from source region may intensify pre-monsoon rain band over central China in May and lead to early monsoon onset.

Kim, Kyu-Myong↗
NASA NTRS2004

Multi-Sensor Distributive On-Line Processing, Visualization, and Analysis Infrastructure for an Agricultural Information System at the NASA Goddard Earth Sciences DAAC

The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM On-line Visualization and Analysis System precipitation and other satellite data products and services. AIS outputs will be ,integrated into existing operational decision support system for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that ,allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical ,parameters, area of interest, and time period; and the system generates an output ,on screen in a matter of seconds.

Teng, William↗
NASA NTRS2005

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

Teng, William↗
NASA NTRS2005

V and V of ISHM Software for Space Exploration

NASA has established a far-reaching and long-term program for robotic and manned exploration of the solar system, beginning with missions to the moon and Mars. The Crew Transportation System (CTS), a key system for space exploration, imposes four requirements' that ISHM addresses. These requirements have a wide range of implications for V&V and certification of ISHM. There is a range of time-criticality for ISHM actions, from prognostication, which is often (but not always) non-time-critical, to time-critical state estimation and system management under off-nominal emergency conditions. These are externally imposed requirements on ISHM that are subject to V&V. - In addition, a range of techniques are needed to implement an ISHM. The approaches to ISHM are described elsewhere. These approaches range from well-understood algorithms for low-level data analysis, validation and reporting, to AI techniques for state estimation and planning. The range of techniques, and specifically the use of AI techniques such as reasoning under uncertainty and mission planning (and re-planning), implies that several V&V approaches may be required. Depending on the ISHM architecture, traditional testing approaches may be adequate for some ISHM functionality. The AI-based approaches to reasoning under uncertainty, model-based reasoning, and planning share characteristics typical of other complex software systems, but they also have characteristics that set them apart and challenge standard V&V techniques. The range of possible solutions to the overall ISHM problem impose internal challenges to V&V. The V&V challenges increase when hard real-time constraints are imposed for time-critical functionality. For example, there is an external requirement that impending catastrophic failure of the Launch Vehicle (LV) at launch time be detected and life-saving action be taken within two seconds. In this paper we outline the challenges for ISHM V&V, existing approaches and analogs in other software application areas, and possible new approaches to the V&V challenges for space exploration ISHM.

Markosian, Lawrence↗
NASA NTRS2007

Methylhopane Biomarker and Carbon Isotopic Evidence for Late Archean Aerobic Ecosystems

Molecular fossils are particularly valuable in early Earth studies because they provide information about microbial sources and ecology. Here we report on the distribution of 2- methyl and 3-methylhopanes preserved in a 2.72-2.56 billion-year-old section of shallow and deepwater sediments of the Hamersley Province [Eigenbrode et aI., submitted]. These biomarkers are mostly from cyanobacteria and oxygen-respiring methanotrophs, respectively. The relative abundance of 2-methylhopanes increases with carbonate abundance in shallow-water facies indicating cyanobacteria were key microbes in shallow ecosystems and suggesting they supplied both molecular oxygen and fixed carbon. The relative abundance of 3-methylhopane strongly correlates with kerogen-carbon isotopic values, and is more abundant in the samples with 13C-enriched signatures. Thus, molecular data provides evidence for cycling of methane in shallow settings, even though the anoxic deeper environments bear stronger 13C-depletion, which together suggests a more complex methane cycle than previously envisioned. Detailed facies analysis of the Hamersley carbon-isotope record reveals temporal changes suggesting continued oxidation of shallow settings favoring the expansion of aerobic ecosystems and respiring organisms [Eigenbrode et aI., 2006, PNAS, 103: 15759]. Similar analysis of published carbon-isotopic records suggests similar, but diachronous, expansion of oxygenated habitats in shallow then deep waters as anaerobic microbial communities gave way to respiring communities fueled by oxygenic photosynthesis before the post 2.45-Ga atmospheric oxygenation event [Eigenbrode et aI., 2006]. The robust relationships observed provide geochemical support for methanogenesis, aerobic methanotrophy, and oxygenic photosynthesis in the late Archean, as well as major ecological shifts linked to biogeochemical reorganization.

Eigenbrode, Jennifer L.↗
NASA NTRS2012

Quantifying Above-Cloud Aerosols through Integrating Multi-Sensor Measurements from A-Train Satellites

Quantifying above-cloud aerosols can help improve the assessment of aerosol intercontinental transport and climate impacts. Large-scale measurements of aerosol above low-level clouds had been generally unexplored until very recently when CALIPSO lidar started to acquire aerosol and cloud profiles in June 2006. Despite CALIPSO s unique capability of measuring above-cloud aerosol optical depth (AOD), such observations are substantially limited in spatial coverage because of the lidar s near-zero swath. We developed an approach that integrates measurements from A-Train satellite sensors (including CALIPSO lidar, OMI, and MODIS) to extend CALIPSO above-cloud AOD observations to substantially larger areas. We first examine relationships between collocated CALIPSO above-cloud AOD and OMI absorbing aerosol index (AI, a qualitative measure of AOD for elevated dust and smoke aerosol) as a function of MODIS cloud optical depth (COD) by using 8-month data in the Saharan dust outflow and southwest African smoke outflow regions. The analysis shows that for a given cloud albedo, above-cloud AOD correlates positively with AI in a linear manner. We then apply the derived relationships with MODIS COD and OMI AI measurements to derive above-cloud AOD over the whole outflow regions. In this talk, we will present spatial and day-to-day variations of the above-cloud AOD and the estimated direct radiative forcing by the above-cloud aerosols.

Zhang, Yan↗
NASA NTRS2015

Parameter Impact on Sharing Studies Between UAS CNPC Satellite Transmitters and Terrestrial Systems

In order to provide a control and non-payload communication (CNPC) link for civil-use unmanned aircraft systems (UAS) when operating in beyond-line-of-sight (BLOS) conditions, satellite communication links are generally required. The International Civil Aviation Organization (ICAO) has determined that the CNPC link must operate over protected aviation safety spectrum allocations. Although a suitable allocation exists in the 5030-5091 MHz band, no satellites provide operations in this band and none are currently planned. In order to avoid a very lengthy delay in the deployment of UAS in BLOS conditions, it has been proposed to use existing satellites operating in the Fixed Satellite Service (FSS), of which many operate in several spectrum bands. Regulatory actions by the International Telecommunications Union (ITU) are needed to enable such a use on an international basis, and indeed Agenda Item (AI) 1.5 for the 2015 World Radiocommunication Conference (WRC) was established to decide on the enactment of possible regulatory provisions. As part of the preparation for AI 1.5, studies on the sharing FSS bands between existing services and CNPC for UAS are being contributed by NASA and others. These studies evaluate the potential impact of satellite CNPC transmitters operating from UAS on other in-band services, and on the potential impact of other in-band services on satellite CNPC receivers operating on UAS platforms. Such studies are made more complex by the inclusion of what are essentially moving FSS earth stations, compared to typical sharing studies between fixed elements. Hence, the process of determining the appropriate technical parameters for the studies meets with difficulty. In order to enable a sharing study to be completed in a less-than-infinite amount of time, the number of parameters exercised must be greatly limited. Therefore, understanding the impact of various parameter choices is accomplished through selectivity analyses. In the case of sharing studies for AI 1.5, identification of worst-case parameters allows the studies to be focused on worst-case scenarios with assurance that other parameter combinations will yield comparatively better results and therefore do not need to be fully analyzed. In this paper, the results of such sensitivity analyses are presented for the case of sharing between UAS CNPC satellite transmitters and terrestrial receivers using the Fixed Service (FS) operating in the same bands, and the implications of these analyses on sharing study results.

air traffic control↗
NASA NTRS2017

Enabling Autonomous Space Mission Operations with Artificial Intelligence

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

Frank, Jeremy↗