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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Knowledge Base for Distributed Spacecraft Mission Design Using the Trade-Space Analysis Tool for Constellations (TAT-C)

Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.

Pattern Recognition↗
NASA NTRS2004

Materials Characterization at Utah State University: Facilities and Knowledge-base of Electronic Properties of Materials Applicable to Spacecraft Charging

In an effort to improve the reliability and versatility of spacecraft charging models designed to assist spacecraft designers in accommodating and mitigating the harmful effects of charging on spacecraft, the NASA Space Environments and Effects (SEE) Program has funded development of facilities at Utah State University for the measurement of the electronic properties of both conducting and insulating spacecraft materials. We present here an overview of our instrumentation and capabilities, which are particularly well suited to study electron emission as related to spacecraft charging. These measurements include electron-induced secondary and backscattered yields, spectra, and angular resolved measurements as a function of incident energy, species and angle, plus investigations of ion-induced electron yields, photoelectron yields, sample charging and dielectric breakdown. Extensive surface science characterization capabilities are also available to fully characterize the samples in situ. Our measurements for a wide array of conducting and insulating spacecraft materials have been incorporated into the SEE Charge Collector Knowledge-base as a Database of Electronic Properties of Materials Applicable to Spacecraft Charging. This Database provides an extensive compilation of electronic properties, together with parameterization of these properties in a format that can be easily used with existing spacecraft charging engineering tools and with next generation plasma, charging, and radiation models. Tabulated properties in the Database include: electron-induced secondary electron yield, backscattered yield and emitted electron spectra; He, Ar and Xe ion-induced electron yields and emitted electron spectra; photoyield and solar emittance spectra; and materials characterization including reflectivity, dielectric constant, resistivity, arcing, optical microscopy images, scanning electron micrographs, scanning tunneling microscopy images, and Auger electron spectra. Further details of the instrumentation used for insulator measurements and representative measurements of insulating spacecraft materials are provided in other Spacecraft Charging Conference presentations. The NASA Space Environments and Effects Program, the Air Force Office of Scientific Research, the Boeing Corporation, NASA Graduate Research Fellowships, and the NASA Rocky Mountain Space Grant Consortium have provided support.

Dennison, J. R.↗
NASA NTRS2025

Laminae as Structural Biosignatures in NASA’s Life Detection Knowledge Base

Laminae are millimeter-scale features in rocks created by physiochemical processes that can be influenced by the presence and activities of communities of organisms that occur as biofilms and microbial mats. The structure and composition of laminae reflect the processes involved in their formation and can be preserved in the rock record over geologic time, however diagenetic and metamorphic alteration can lead to the loss of primary information and confusion over the interpretation of their origins. As potential records of ancient life, laminae can preserve evidence of microbial activity over billions of years of Earth’s history. On planetary bodies beyond Earth, laminae in sedimentary rocks are the most common sedimentary structure and represent significant features of interest that can record habitable conditions (e.g., the presence of liquid water) at the time of their formation. Here we review the significance of laminae as targets for astrobiological exploration. We discuss common mechanisms by which laminae form in natural environments on Earth, present arguments and evidence for laminae as biosignatures, and describe how such information is incorporated into the NASA Life Detection Knowledge Base.

Astrobiology↗
NASA NTRS2015

Data Recipes: Toward Creating How-To Knowledge Base for Earth Science Data

Both the diversity and volume of Earth science data from satellites and numerical models are growing dramatically, due to an increasing population of measured physical parameters, and also an increasing variety of spatial and temporal resolutions for many data products. To further complicate matters, Earth science data delivered to data archive centers are commonly found in different formats and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and or formats. The data recipe project at Goddard Earth Science Data and Information Services Center (GES DISC) was initiated in late 2012 for enhancing user support. A data recipe is a How-To online explanatory document, with step-by-step instructions and examples of accessing and working with real data (http:disc.sci.gsfc.nasa.govrecipes). The current suite of recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant, even though the data recipe topics are still limited. An Earth Science Data System Working Group (ESDSWG) for data recipes was established in the spring of 2014, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group is working on an inventory and analysis of existing data recipes and tutorials, and will provide guidelines and recommendation for writing and grouping data recipes, and for cross linking recipes to data products. This presentation gives an overview of the data recipe activites at GES DISC and ESDSWG. We are seeking requirements and input from a broader data user community to establish a strong knowledge base for Earth science data research and application implementations.

data recipe↗
DOE OSTI2015

Knowledge-based fault diagnosis system for refuse collection vehicle

The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1991

Knowledge-based processing for aircraft flight control

The purpose is to develop algorithms and architectures for embedding artificial intelligence in aircraft guidance and control systems. With the approach adopted, AI-computing is used to create an outer guidance loop for driving the usual aircraft autopilot. That is, a symbolic processor monitors the operation and performance of the aircraft. Then, based on rules and other stored knowledge, commands are automatically formulated for driving the autopilot so as to accomplish desired flight operations. The focus is on developing a software system which can respond to linguistic instructions, input in a standard format, so as to formulate a sequence of simple commands to the autopilot. The instructions might be a fairly complex flight clearance, input either manually or by data-link. Emphasis is on a software system which responds much like a pilot would, employing not only precise computations, but, also, knowledge which is less precise, but more like common-sense. The approach is based on prior work to develop a generic 'shell' architecture for an AI-processor, which may be tailored to many applications by describing the application in appropriate processor data bases (libraries). Such descriptions include numerical models of the aircraft and flight control system, as well as symbolic (linguistic) descriptions of flight operations, rules, and tactics.

Painter, John H.↗
NASA NTRS1988

Dynamic reasoning in a knowledge-based system

Any space based system, whether it is a robot arm assembling parts in space or an onboard system monitoring the space station, has to react to changes which cannot be foreseen. As a result, apart from having domain-specific knowledge as in current expert systems, a space based AI system should also have general principles of change. This paper presents a modal logic which can not only represent change but also reason with it. Three primitive operations, expansion, contraction and revision are introduced and axioms which specify how the knowledge base should change when the external world changes are also specified. Accordingly the notion of dynamic reasoning is introduced, which unlike the existing forms of reasoning, provide general principles of change. Dynamic reasoning is based on two main principles, namely minimize change and maximize coherence. A possible-world semantics which incorporates the above two principles is also discussed. The paper concludes by discussing how the dynamic reasoning system can be used to specify actions and hence form an integral part of an autonomous reasoning and planning system.

Rao, Anand S.↗
NASA NTRS1991

Impact of knowledge-based software engineering on aerospace systems

The emergence of knowledge engineering as a software technology will dramatically alter the use of software by expanding application areas across a wide spectrum of industries. The engineering and management of large aerospace software systems could benefit from a knowledge engineering approach. An understanding of this technology can potentially make significant improvements to the current practice of software engineering, and provide new insights into future development and support practices.

Peyton, Liem↗
NASA NTRS1991

A knowledge based application of the extended aircraft interrogation and display system

A family of multiple-processor ground support test equipment was used to test digital flight-control systems on high-performance research aircraft. A unit recently built for the F-18 high alpha research vehicle project is the latest model in a series called the extended aircraft interrogation and display system. The primary feature emphasized monitors the aircraft MIL-STD-1553B data buses and provides real-time engineering units displays of flight-control parameters. A customized software package was developed to provide real-time data interpretation based on rules embodied in a highly structured knowledge database. The configuration of this extended aircraft interrogation and display system is briefly described, and the evolution of the rule based package and its application to failure modes and effects testing on the F-18 high alpha research vehicle is discussed.

Glover, Richard D.↗
NASA NTRS2019

NASA Earthdata Knowledge Base

Prototype work for connecting together the main elements of Earth Observation knowledge and context in a way that is: machine-readable, human-usable and curatable. Using the latest in graph technologies and cloud managed services.

earth data↗
DOE OSTI2024

An ontology-based knowledge graph for representing interactions involving RNA molecules

The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

SU-E-P-43: A Knowledge Based Approach to Guidelines for Software Safety

Purpose: In the fall of 2012, a survey was distributed to medical physicists across Canada. The survey asked the respondents to comment on various aspects of software development and use in their clinic. The survey revealed that most centers employ locally produced (in-house) software of some kind. The respondents also indicated an interest in having software guidelines, but cautioned that the realities of cancer clinics include variations, that preclude a simple solution. Traditional guidelines typically involve periodically repeating a set of prescribed tests with defined tolerance limits. However, applying a similar formula to software is problematic since it assumes that the users have a perfect knowledge of how and when to apply the software and that if the software operates correctly under one set of conditions it will operate correctly under all conditions Methods: In the approach presented here the personnel involved with the software are included as an integral part of the system. Activities performed to improve the safety of the software are done with both software and people in mind. A learning oriented approach is taken, following the premise that the best approach to safety is increasing the understanding of those associated with the use or development of the software. Results: The software guidance document is organized by areas of knowledge related to use and development of software. The categories include: knowledge of the underlying algorithm and its limitations; knowledge of the operation of the software, such as input values, parameters, error messages, and interpretation of output; and knowledge of the environment for the software including both data and users. Conclusion: We propose a new approach to developing guidelines which is based on acquiring knowledge-rather than performing tests. The ultimate goal is to provide robust software guidelines which will be practical and effective.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1991

Expert operator's associate: A knowledge based system for spacecraft control

The Expert Operator's Associate (EOA) project is presented which studies the applicability of expert systems for day-to-day space operations. A prototype expert system is developed, which operates on-line with an existing spacecraft control system at the European Space Operations Centre, and functions as an 'operator's assistant' in controlling satellites. The prototype is demonstrated using an existing real-time simulation model of the MARECS-B2 telecommunication satellite. By developing a prototype system, the extent to which reliability and effectivens of operations can be enhanced by AI based support is examined. In addition the study examines the questions of acquisition and representation of the 'knowledge' for such systems, and the feasibility of 'migration' of some (currently) ground-based functions into future spaceborne autonomous systems.

Nielsen, Mogens↗
NASA NTRS1988

Knowledge-based operation and management of communications systems

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Heggestad, Harold M.↗
NASA NTRS1992

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Maslanik, J. A.↗
NASA NTRS1992

Reuse: A knowledge-based approach

This paper describes our research in automating the reuse process through the use of application domain models. Application domain models are explicit formal representations of the application knowledge necessary to understand, specify, and generate application programs. Furthermore, they provide a unified repository for the operational structure, rules, policies, and constraints of a specific application area. In our approach, domain models are expressed in terms of a transaction-based meta-modeling language. This paper has described in detail the creation and maintenance of hierarchical structures. These structures are created through a process that includes reverse engineering of data models with supplementary enhancement from application experts. Source code is also reverse engineered but is not a major source of domain model instantiation at this time. In the second phase of the software synthesis process, program specifications are interactively synthesized from an instantiated domain model. These specifications are currently integrated into a manual programming process but will eventually be used to derive executable code with mechanically assisted transformations. This research is performed within the context of programming-in-the-large types of systems. Although our goals are ambitious, we are implementing the synthesis system in an incremental manner through which we can realize tangible results. The client/server architecture is capable of supporting 16 simultaneous X/Motif users and tens of thousands of attributes and classes. Domain models have been partially synthesized from five different application areas. As additional domain models are synthesized and additional knowledge is gathered, we will inevitably add to and modify our representation. However, our current experience indicates that it will scale and expand to meet our modeling needs.

Iscoe, Neil↗
DOE OSTI2014

Advancing the hydrogen safety knowledge base

The International Energy Agency's Hydrogen Implementing Agreement (IEA HIA) was established in 1977 to pursue collaborative hydrogen research and development and information exchange among its member countries. Information and knowledge dissemination is a key aspect of the work within IEA HIA tasks, and case studies, technical reports and presentations/publications often result from the collaborative efforts. The work conducted in hydrogen safety under Task 31 and its predecessor, Task 19, can positively impact the objectives of national programs even in cases for which a specific task report is not published. As a result, the interactions within Task 31 illustrate how technology information and knowledge exchange among participating hydrogen safety experts serve the objectives intended by the IEA HIA.

08 HYDROGEN↗