SEARCH · Engineering Papers

Results for “Knowledge bases”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

NASA NTRS2018

Stirling Convertor Controller Development at NASA Glenn Research Center

For nearly two decades, NASA Glenn Research Center (GRC) has been supporting the development of Radioisotope Power Systems (RPS). NASA desires higher conversion efficiency RPS options that are reliable and robust with long life design. Dynamic conversion, such as Stirling and Brayton, offer the potential for higher conversion efficiencies than current RPS but have yet to be demonstrated in a flight application. The RPS program sent out a solicitation to investigate options for dynamic conversion technologies. As a result of this solicitation, four dynamic power convertor (DPC) technologies were selected for design and three are proceeding to the fabrication phase of prototype dynamic convertors. One lesson learned from the Advanced Stirling Radioisotope Generator (ASRG) project is that controller development should be coordinated with the development of a dynamic convertor. As a result of this, NASA GRC has been utilizing hardware from past Stirling convertor projects including that of the ASRG to support controller development for the DPC's. NASA GRC has developed a strong knowledge base on both analog and digital Stirling dynamic power convertor controllers and will continue to expand and apply that knowledge to the DPC's. Over the past 15 years, controllers were developed at GRC, at Lockheed Martin (LM) and by the Johns Hopkins University/Applied Physics Laboratory (JHU/APL). Various generations of the controllers have been developed as lessons were learned through various component and system level tests. Some of the tests performed were fault tolerance, flight acceptance vibration, electromagnetic interference (EMI), spacecraft integration, and extended operation. The fault tolerance test characterized the controller's ability to handle various fault conditions, including high or low bus power consumptions, total open load or short circuit, and replacing a failed controller card while the backup maintains control of the Stirling convertor. The vibration test confirms the controller's ability to control an ASC during launch. The EMI test characterized the AC and DC magnetic and electric fields emitted by the single ASC and if the controller has an impact on the radiated EMI. Spacecraft integration testing in the Radioisotope Power Systems System Integration Laboratory (RSIL) provided insight into the electrical interactions between the representative RPS, its associated control schemes, and realistic electric system loads. The extended operation test allows data to be collected over a period of thousands of hours to obtain long term performance data of the system. This paper describes the history of controller development at NASA GRC, tests performed on these controllers, and lessons learned.

Dugala, Gina M.↗

NASA NTRS2018

Stirling Convertor Controller Development at NASA Glenn Research Center

Over the past decade, NASA Glenn Research Center (GRC) has been supporting the development of Radioisotope Power Systems (RPS). NASA desires higher conversion efficiency RPS options that are reliable and robust with long life design. Dynamic conversion, such as Stirling and Brayton, offer the potential for higher conversion efficiencies but have yet to be demonstrated in a flight application. The RPS program sent out a solicitation to investigate options for dynamic conversion technologies. As a result of this solicitation, four dynamic power convertor (DPC) technologies were selected for design and fabrication of a prototype dynamic convertor. One lesson learned from the Advanced Stirling Radioisotope Generator (ASRG) project is that controller development should start early in the development of a dynamic convertor. As a result of this, NASA GRC has been utilizing hardware from past Stirling convertor projects including that of the ASRG to support controller development for the DPC's. NASA GRC has developed a strong knowledge base on both analog and digital Stirling dynamic power convertor controllers and will continue to expand and apply that knowledge to the four DPC's. Over the past 15 years, controllers were developed in-house at GRC, at Lockheed Martin Coherent Technologies (LMCT) and by the Johns Hopkins University/Applied Physics Laboratory (JHU/APL). Various generations of the controllers, have been developed as lessons were learned through various component and system level tests. Some of the tests performed were fault tolerance, qualification vibration level, electromagnetic interference, Radioisotope Power System Systems Integration (RSIL) tests, and extended operation. The fault tolerance test characterized the controller's ability to handle various fault conditions, including high or low bus power consumptions, total open load or short circuit, and replacing a failed controller card while the backup maintains control of the ASC. The vibration test confirms the controller's ability to control an ASC during launch. The EMI test characterized the AC and DC magnetic and electric fields emitted by the single ASC and if the controller has an impact on the radiated EMI. RSIL testing provided insight into the electrical interactions between the representative RPS, its associated control schemes, and realistic electric system loads. The extended operation test allows data to be collected over a period of thousands of hours to obtain long term performance data of the system. This paper describes the history of controller development at NASA GRC, tests performed on these controllers, and lessons learned.

Dugala, Gina M.↗

NASA NTRS1990

An application of object-oriented knowledge representation to engineering expert systems

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

D S Logie↗

NASA NTRS1985

USL NASA/RECON project presentations at the 1985 ACM Computer Science Conference: Abstracts and visuals

This Working Paper Series entry represents the abstracts and visuals associated with presentations delivered by six USL NASA/RECON research team members at the above named conference. The presentations highlight various aspects of NASA contract activities pursued by the participants as they relate to individual research projects. The titles of the six presentations are as follows: (1) The Specification and Design of a Distributed Workstation; (2) An Innovative, Multidisciplinary Educational Program in Interactive Information Storage and Retrieval; (3) Critical Comparative Analysis of the Major Commercial IS and R Systems; (4) Design Criteria for a PC-Based Common User Interface to Remote Information Systems; (5) The Design of an Object-Oriented Graphics Interface; and (6) Knowledge-Based Information Retrieval: Techniques and Applications.

Dominick, Wayne D.↗

NASA NTRS1989

TRUSS: An intelligent design system for aircraft wings

Competitive leadership in the international marketplace, superiority in national defense, excellence in productivity, and safety of both private and public systems are all national defense goals which are dependent on superior engineering design. In recent years, it has become more evident that early design decisions are critical, and when only based on performance often result in products which are too expensive, hard to manufacture, or unsupportable. Better use of computer-aided design tools and information-based technologies is required to produce better quality United States products. A program is outlined here to explore the use of knowledge based expert systems coupled with numerical optimization, database management techniques, and designer interface methods in a networked design environment to improve and assess design changes due to changing emphasis or requirements. The initial structural design of a tiltrotor aircraft wing is used as a representative example to demonstrate the approach being followed.

Bates, Preston R.↗

NASA NTRS2022

3D-CHESS: Decentralized, Distributed, Dynamic, and Context-aware Heterogeneous Sensor Systems

This paper describes the objectives and current status of the 3D-CHESS project which aims to demonstrate a new Earth observing strategy based on a context-aware Earth observing sensor web. This sensor web consists of a set of nodes with a knowledge base, heterogeneous sensors, edge computing, and autonomous decision-making capabilities. Context awareness is defined as the ability for the nodes to gather, exchange, and leverage contextual information (e.g., state of the Earth system, state and capabilities of itself and of other nodes in the network, and how those states relate to the dy- namic mission objectives) to improve decision making and planning. The current goal of the project is to demonstrate proof of concept by comparing the performance of a 3D- CHESS sensor web with that of status quo architectures in the context of a multi-sensor inland hydrologic and ecologic monitoring system.

David, Cedric H.↗

NASA NTRS1994

Automated analysis of complex data

We have examined some of the issues involved in automating exploratory data analysis, in particular the tradeoff between control and opportunism. We have proposed an opportunistic planning solution for this tradeoff, and we have implemented a prototype, Igor, to test the approach. Our experience in developing Igor was surprisingly smooth. In contrast to earlier versions that relied on rule representation, it was straightforward to increment Igor's knowledge base without causing the search space to explode. The planning representation appears to be both general and powerful, with high level strategic knowledge provided by goals and plans, and the hooks for domain-specific knowledge are provided by monitors and focusing heuristics.

Saintamant, Robert↗

NASA NTRS1994

KATE: From the lab to the firing room

For the past 9 years, the AI group at NASA's Kennedy Space Center (KSC) has been developing a real-time model-based reasoning (MBR) system that can diagnose faults and provide control advisories. The system resulting from this effort is called KATE (Knowledge-based Autonomous Test Engineer). This article describes the transition of KATE from the applied research lab to the firing room (the firing room is the main control and monitoring center for all Shuttle ground support and launch processing). Because the problems that were countered along the way are not unique, we decided to share some of our experiences. This article also includes a brief overview of the latest application of KATE.

Pepe, Charles↗

NASA NTRS1999

Prototype and Evaluation of AutoHelp: A Case-based, Web-accessible Help Desk System for EOSDIS

AutoHelp is a case-based, Web-accessible help desk for users of the EOSDIS. Its uses a combination of advanced computer and Web technologies, knowledge-based systems tools, and cognitive engineering to offload the current, person-intensive, help desk facilities at the DAACs. As a case-based system, AutoHelp starts with an organized database of previous help requests (questions and answers) indexed by a hierarchical category structure that facilitates recognition by persons seeking assistance. As an initial proof-of-concept demonstration, a month of email help requests to the Goddard DAAC were analyzed and partially organized into help request cases. These cases were then categorized to create a preliminary case indexing system, or category structure. This category structure allows potential users to identify or recognize categories of questions, responses, and sample cases similar to their needs. Year one of this research project focused on the development of a technology demonstration. User assistance 'cases' are stored in an Oracle database in a combination of tables linking prototypical questions with responses and detailed examples from the email help requests analyzed to date. When a potential user accesses the AutoHelp system, a Web server provides a Java applet that displays the category structure of the help case base organized by the needs of previous users. When the user identifies or requests a particular type of assistance, the applet uses Java database connectivity (JDBC) software to access the database and extract the relevant cases. The demonstration will include an on-line presentation of how AutoHelp is currently structured. We will show how a user might request assistance via the Web interface and how the AutoHelp case base provides assistance. The presentation will describe the DAAC data collection, case definition, and organization to date, as well as the AutoHelp architecture. It will conclude with the year 2 proposal to more fully develop the case base, the user interface (including the category structure), interface with the current DAAC Help System, the development of tools to add new cases, and user testing and evaluation at (perhaps) the Goddard DAAC.

Mitchell, Christine M.↗

NASA NTRS1987

Implementing clips on a parallel computer

The C language integrated production system (CLIPS) is a forward chaining rule based language to provide training and delivery for expert systems. Conceptually, rule based languages have great potential for benefiting from the inherent parallelism of the algorithms that they employ. During each cycle of execution, a knowledge base of information is compared against a set of rules to determine if any rules are applicable. Parallelism also can be employed for use with multiple cooperating expert systems. To investigate the potential benefits of using a parallel computer to speed up the comparison of facts to rules in expert systems, a parallel version of CLIPS was developed for the FLEX/32, a large grain parallel computer. The FLEX implementation takes a macroscopic approach in achieving parallelism by splitting whole sets of rules among several processors rather than by splitting the components of an individual rule among processors. The parallel CLIPS prototype demonstrates the potential advantages of integrating expert system tools with parallel computers.

Riley, Gary↗

NASA NTRS1987

An expert system that performs a satellite station keepimg maneuver

The development and characteristics of a prototype expert system, Expert System for Satellite Orbit Control (ESSOC), capable of providing real-time spacecraft system analysis and command generation for a geostationary satellite are described. The ESSOC recommends appropriate commands that reflect both the changing spacecraft condition and previous procedural action. An internal knowledge base stores satellite status information and is updated with processed spacecraft telemetry. Procedural structure data are encoded in production rules. Structural methods of knowledge acquisition and the design and performance-enhancing techniques that enable ESSOC to operate in real time are also considered.

Linesbrowning, M. Kate↗

NASA NTRS1991

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

Rolincik, Mark J.↗

NASA NTRS1992

An expert system for diagnosing environmentally induced spacecraft anomalies

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).

Rolincik, Mark↗

NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗

NASA NTRS1991

Systems engineering studies of on-orbit assembly operation

While the practice of construction has a long history, the underlying theory of construction is relatively young. Very little has been documented as to techniques of logistic support, construction planning, construction scheduling, construction testing, and inspection. The lack of 'systems approaches' to construction processes is certainly one of the most serious roadblocks to the construction of space structures. System engineering research efforts at CSC are aimed at developing concepts and tools which contribute to a systems theory of space construction. The research is also aimed at providing means for trade-offs of design parameters for other research areas in CSC. Systems engineering activity at CSC has divided space construction into the areas of orbital assembly, lunar base construction, interplanetary transport vehicle construction, and Mars base construction. A brief summary of recent results is given. Several models for 'launch-on-time' were developed. Launch-on-time is a critical concept to the assembly of such Earth-orbiting structures as the Space Station Freedom, and to planetary orbiters such as the Mars transfer vehicle. CSC has developed a launch vehicle selection model which uses linear programming to find optimal combinations of launch vehicles of various sizes (Atlas, Titan, Shuttles, HLLV's) to support SEI missions. Recently, the Center developed a cost trade-off model for studying on orbit assembly logistics. With this model it was determined that the most effective size of the HLLV would be in the range of 120 to 200 metric tons to LEO, which is consistent with the choices of General Stafford's Synthesis Group Report. A second-generation Dynamic Construction Activities Model ('DYCAM') process model has been under development, based on our past results in interruptability and our initial DYCAM model. This second-generation model is built on the paradigm of knowledge-based expert systems. It is aimed at providing answers to two questions: (1) what are some necessary or sufficient conditions for judging conceptual designs of spacecraft?, and (2) can a methodology be formulated such that these conditions may be used to provide computer-aided tools for evaluating conceptual designs and planning for space assembly sequences? Early simulation results indicate that the DYCAM model has a clear ability to emulate and simulate human orbital construction processes.

Morgenthaler, George W.↗

NASA NTRS1977

Robot learning and error correction

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Friedman, L.↗

NASA NTRS1990

A diagnosis system using object-oriented fault tree models

Spaceborne computing systems must provide reliable, continuous operation for extended periods. Due to weight, power, and volume constraints, these systems must manage resources very effectively. A fault diagnosis algorithm is described which enables fast and flexible diagnoses in the dynamic distributed computing environments planned for future space missions. The algorithm uses a knowledge base that is easily changed and updated to reflect current system status. Augmented fault trees represented in an object-oriented form provide deep system knowledge that is easy to access and revise as a system changes. Given such a fault tree, a set of failure events that have occurred, and a set of failure events that have not occurred, this diagnosis system uses forward and backward chaining to propagate causal and temporal information about other failure events in the system being diagnosed. Once the system has established temporal and causal constraints, it reasons backward from heuristically selected failure events to find a set of basic failure events which are a likely cause of the occurrence of the top failure event in the fault tree. The diagnosis system has been implemented in common LISP using Flavors.

Iverson, David L.↗

NASA NTRS1995

A software tool to design thermal barrier coatings

This paper summarizes work completed for a NASA Phase 1 SBIR program which demonstrated the feasibility of developing a software tool to aid in the design of thermal barrier coating (TBC) systems. Toward this goal, three tasks were undertaken and completed. Task 1 involved the development of a database containing the pertinent thermal and mechanical property data for the top coat, bond coat and substrate materials that comprise a TBC system. Task 2 involved the development of an automated set-up program for generating two dimensional (2D) finite element models of TBC systems. Most importantly, Task 3 involved the generation of a rule base to aid in the design of a TBC system. These rules were based on a factorial design of experiments involving FEM results, and were generated using a Yates analysis. A previous study has indicated the suitability and benefit of applying finite element analysis to perform computer based experiments to decrease but not eliminate physical experiments on TBC's. This program proved feasibility by expanding on these findings by developing a larger knowledge base and developing a procedure to extract rules to aid in TBC design.

Petrus, G.↗