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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 235 records · Page 13

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

Tradeoffs in the utility of learned knowledge

Planning systems which make use of domain theories can produce more accurate plans and achieve more goals as the quality of their domain knowledge improves. MTR, a multi-strategy learning system, was designed to learn from system failures and improve domain knowledge used in planning. However, augmented domain knowledge can decrease planning efficiency. We describe how improved knowledge that becomes expensive to use can be approximated to yield calculated tradeoffs in accuracy and efficiency.

Kedar, Smadar↗

Knowledge-based diagnosis for aerospace systems

The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

Atkinson, David J.↗

Knowledge-based diagnosis for aerospace systems

The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

Atkinson, David↗

Knowledge of the systems H2O-SO3-N2O3. Report 1: The system H2SO4-H2O-N2O3

The amount of N2O3 being absorbed in 50-100% H2SO4 at 19, 60, and 95 C is directly proportional to the acid concentration and inversely proportional to the temperature. NO+ formation according to the above-formulated equation occurs only at H2SO4 concentrations greater than 52%. Absorption in highly concentrated sulfuric acid results in the formation of crystalline NOHSO4.

Stopperka, K.↗

Knowledge-based Expert Systems for Crop Identification

The development of an improved understanding of the interactive man machine environment is investigated. In such an environment, as many feature inputs as practical would be automatically derived from a data base and input into an expert system decision making procedure. This procedure could then provide expert assistance to a trained image analyst to upgrade and improve the quantity and accuracy of the information extracted from the input data. A comparison of the similarities and differences between manual and automated image interpretation techniques is also examined.

Smith, T. R.↗

A knowledge based expert system for propellant system monitoring at the Kennedy Space Center

The Lox Expert System (LES) is the first attempt to build a realtime expert system capable of simulating the thought processes of NASA system engineers, with regard to fluids systems analysis and troubleshooting. An overview of the hardware and software describes the techniques used, and possible applications to other process control systems. LES is now in the advanced development stage, with a full implementation planned for late 1985.

Jamieson, J. R.↗

Automatic Scheduling and Planning (ASAP) in future ground control systems

This report describes two complementary approaches to the problem of space mission planning and scheduling. The first is an Expert System or Knowledge-Based System for automatically resolving most of the activity conflicts in a candidate plan. The second is an Interactive Graphics Decision Aid to assist the operator in manually resolving the residual conflicts which are beyond the scope of the Expert System. The two system designs are consistent with future ground control station activity requirements, support activity timing constraints, resource limits and activity priority guidelines.

Matlin, Sam↗

Application of Artificial Intelligence (AI) programming techniques to tactical guidance for fighter aircraft

A research program investigating the use of Artificial Intelligence (AI) programming techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined and example rules are presented. The results of tests to evaluate the performance of the TDG against a version of AML and against human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements.

Mcmanus, John W.↗

Advanced NSTS propulsion system verification study

The merits of propulsion system development testing are discussed. The existing data base of technical reports and specialists is utilized in this investigation. The study encompassed a review of all available test reports of propulsion system development testing for the Saturn stages, the Titan stages, and the Space Shuttle main propulsion system. The knowledge on propulsion system development and system testing available from specialists and managers was also 'tapped' for inclusion.

Wood, Charles↗

Transport aircraft loading and balancing system: Using a CLIPS expert system for military aircraft load planning

The requirement for improving aircraft utilization and responsiveness in airlift operations has been recognized for quite some time by the Canadian Forces. To date, the utilization of scarce airlift resources has been planned mainly through the employment of manpower-intensive manual methods in combination with the expertise of highly qualified personnel. In this paper, we address the problem of facilitating the load planning process for military aircraft cargo planes through the development of a computer-based system. We introduce TALBAS (Transport Aircraft Loading and BAlancing System), a knowledge-based system designed to assist personnel involved in preparing valid load plans for the C130 Hercules aircraft. The main features of this system which are accessible through a convivial graphical user interface, consists of the automatic generation of valid cargo arrangements given a list of items to be transported, the user-definition of load plans and the automatic validation of such load plans.

Richardson, J.↗

Using Model-Based Reasoning for Autonomous Instrument Operation

Multiprobe missions are an important part of NASA's future: Cluster, Magnetospheric Multi Scale, Global Electrodynamics and Magnetospheric Constellation are representatives from the Sun-Earth Connections Theme. To make such missions robust, reliable, and affordable, ideally the many spacecraft of a constellation must be at least as easy to operate as one spacecraft is today. To support this need for scalability, science instrumentation must become increasingly easy to operate, even as this same instrumentation becomes more capable and advanced. Communication and control resources will be at a premium for future instruments. Many missions will be out of contact with ground operators for extended periods either to reduce operations cost or because of orbits that limit communication to weekly perigee transits. Autonomous capability is necessary if such missions are to effectively achieve their operational objectives. An autonomous system is one that acts given its situation in a mission appropriate manner without external direction to achieve mission goals. To achieve this capability autonomy must be built into the system through judicious design or through a built-in intelligence that recognizes system state and manages system response. To recognize desired or undesired system states, the system must have an implicit or explicit understanding of its expected states given its history and self observations. The systems we are concerned with, science instruments, can have stringent requirements for system state knowledge in addition to requirements driven by health and safety concerns. Without accurate knowledge of the system state, the usefulness of the science instrument may be severely limited. At the same time, health and safety concerns often lead to overly conservative instrument operations further reducing the effectiveness of the instrument. These requirements, coupled with overall mission requirements including lack of communication opportunities and tolerance of environmental hazards, frame the problem of constructing autonomous science instruments. we are developing a model of the Low Energy Neutral Atom instrument (LENA) that is currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. LENA is a particle detector that uses high voltage electrostatic optics and time-of-flight mass spectrometry to image neutral atom emissions from the denser regions of the Earth's magnetosphere. As with most spacecraft borne science instruments, phenomena in addition to neutral atoms are detected by LENA. Solar radiation and energetic particles from Earth's radiation belts are of particular concern because they may help generate currents that may compromise LENA's long term performance. An explicit model of the instrument response has been constructed and is currently in use on board IMAGE to dynamically adapt LENA to the presence or absence of energetic background radiations. The components of LENA are common in space science instrumentation, and lessons learned by modelling this system may be applied to other instruments. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. Our future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.

Johnson, Mike↗

Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

McManus, John W.↗

Anomaly Detection, Active Learning, Precursor Identification,and Human Knowledge for Autonomous System Safety

The project Autonomy Teaming and TRajectories for ComplexTrusted Operational Reliability (ATTRACTOR) researched and developed Artificial Intelligence with application to multi-Unmanned Aerial Systems (UAS) missions. Such missions, like other complex systems-of-systems, are likely to have previously-unknown, safety relevant anomalies occur due to many possible factors including system failures or degradations, emergent behavior, changes in the environment in which the systems operate, changes in the way the systems are operated. We discuss the application of anomaly detection, active learning, and precursor identification to identify such anomalies and the conditions under which they are more likely to appear. We demonstrate results on simulated multi-UAS missions that show promise to be applied to real missions.

machine learning↗

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↗

Expressing Functionality Using Design Patterns, A Real-World Example

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting tacit knowledge from existing systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. This study enables such a technique by demonstrating the use of architectural theory in expressing tacit knowledge from existing systems and presenting that knowledge according to the model-based view offered by the Functional Architecture of Systems methodology. By validating the functional information expressed by the design pattern, this work solidifies design patterns as a critical component of a technical architecture and proposes a functional architecture viewpoint for describing mined knowledge in a usable, model-based, way suitable for archival in a modern knowledge management system.

Systems Engineering↗

Development of an intelligent interface for adding spatial objects to a knowledge-based geographic information system

Earth Scientists lack adequate tools for quantifying complex relationships between existing data layers and studying and modeling the dynamic interactions of these data layers. There is a need for an earth systems tool to manipulate multi-layered, heterogeneous data sets that are spatially indexed, such as sensor imagery and maps, easily and intelligently in a single system. The system can access and manipulate data from multiple sensor sources, maps, and from a learned object hierarchy using an advanced knowledge-based geographical information system. A prototype Knowledge-Based Geographic Information System (KBGIS) was recently constructed. Many of the system internals are well developed, but the system lacks an adequate user interface. A methodology is described for developing an intelligent user interface and extending KBGIS to interconnect with existing NASA systems, such as imagery from the Land Analysis System (LAS), atmospheric data in Common Data Format (CDF), and visualization of complex data with the National Space Science Data Center Graphics System. This would allow NASA to quickly explore the utility of such a system, given the ability to transfer data in and out of KBGIS easily. The use and maintenance of the object hierarchies as polymorphic data types brings, to data management, a while new set of problems and issues, few of which have been explored above the prototype level.

Campbell, William J.↗

A knowledge-based object recognition system for applications in the space station

A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

Dhawan, Atam P.↗