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At least 73 records · Page 4

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NASA NTRS1990

Advanced software development workstation project ACCESS user's guide

ACCESS is a knowledge based software information system designed to assist the user in modifying retrieved software to satisfy user specifications. A user's guide is presented for the knowledge engineer who wishes to create for ACCESS a knowledge base consisting of representations of objects in some software system. This knowledge is accessible to an end user who wishes to use the catalogued software objects to create a new application program or an input stream for an existing system. The application specific portion of an ACCESS knowledge base consists of a taxonomy of object classes, as well as instances of these classes. All objects in the knowledge base are stored in an associative memory. ACCESS provides a standard interface for the end user to browse and modify objects. In addition, the interface can be customized by the addition of application specific data entry forms and by specification of display order for the taxonomy and object attributes. These customization options are described.

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NASA NTRS1993

An expert system shell for inferring vegetation characteristics: Interface for the addition of techniques (Task H)

All the NASA VEGetation Workbench (VEG) goals except the Learning System provide the scientist with several different techniques. When VEG is run, rules assist the scientist in selecting the best of the available techniques to apply to the sample of cover type data being studied. The techniques are stored in the VEG knowledge base. The design and implementation of an interface that allows the scientist to add new techniques to VEG without assistance from the developer were completed. A new interface that enables the scientist to add techniques to VEG without assistance from the developer was designed and implemented. This interface does not require the scientist to have a thorough knowledge of Knowledge Engineering Environment (KEE) by Intellicorp or a detailed knowledge of the structure of VEG. The interface prompts the scientist to enter the required information about the new technique. It prompts the scientist to enter the required Common Lisp functions for executing the technique and the left hand side of the rule that causes the technique to be selected. A template for each function and rule and detailed instructions about the arguments of the functions, the values they should return, and the format of the rule are displayed. Checks are made to ensure that the required data were entered, the functions compiled correctly, and the rule parsed correctly before the new technique is stored. The additional techniques are stored separately from the VEG knowledge base. When the VEG knowledge base is loaded, the additional techniques are not normally loaded. The interface allows the scientist the option of adding all the previously defined new techniques before running VEG. When the techniques are added, the required units to store the additional techniques are created automatically in the correct places in the VEG knowledge base. The methods file containing the functions required by the additional techniques is loaded. New rule units are created to store the new rules. The interface that allow the scientist to select which techniques to use is updated automatically to include the new techniques. Task H was completed. The interface that allows the scientist to add techniques to VEG was implemented and comprehensively tested. The Common Lisp code for the Add Techniques system is listed in Appendix A.

Harrison, P. Ann↗

NASA NTRS1990

Developments in REDES: The rocket engine design expert system

The Rocket Engine Design Expert System (REDES) is being developed at the NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP, a nozzle design program named RAO, a regenerative cooling channel performance evaluation code named RTE, and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES is built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

Davidian, Kenneth O.↗

NASA NTRS1990

Developments in REDES: The Rocket Engine Design Expert System

The Rocket Engine Design Expert System (REDES) was developed at NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP; a nozzle design program named RAO; a regenerative cooling channel performance evaluation code named RTE; and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES was built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

Davidian, Kenneth O.↗

NASA NTRS1993

Autonomously acquiring declarative and procedural knowledge for ICAT systems

The construction of Intelligent Computer Aided Training (ICAT) systems is critically dependent on the ability to define and encode knowledge. This knowledge engineering effort can be broadly divided into two categories: domain knowledge and expert or task knowledge. Domain knowledge refers to the physical environment or system with which the expert interacts. Expert knowledge consists of the set of procedures and heuristics employed by the expert in performing their task. Both these areas are a significant bottleneck in the acquisition of knowledge for ICAT systems. This paper presents a research project in the area of autonomous knowledge acquisition using a passive observation concept. The system observes an expert and then generalizes the observations into production rules representing the domain expert's knowledge.

Kovarik, Vincent J., Jr.↗

DOE OSTI2017

Development of a utility computer-based training program on setpoint methodology for nuclear power plants - 129

The purpose of this paper is to provide an overview of the development of the Computer- Based Training (CBT) Program for utility engineers on Setpoint Methodology for nuclear power plants. This computer based training module was prepared by the Advanced Engineering Training initiative. The Advanced Engineering Training initiative is a nuclear industry effort to develop technical computer-based training modules for targeted areas of engineering expertise. The target audience is engineers at commercial nuclear power facilities in the U. S. These modules are being developed using the systematic approach to training and are being designed to maintain industry engineering expertise and to facilitate engineering knowledge transfer. The objective of this training effort is to support the development of the next generation of site technical experts for specific topic areas. The training is one part of three key components that would facilitate knowledge transfer to the future site Subject Matter Expert (SME). The following are the major focus areas covered in the Setpoint Methodology CBT: Chapter 1 provides an overview of the role instrument setpoints perform in the defense-in-depth safety analysis for the plant as well introducing key definitions related to setpoints. Chapter 2 provides the history and current regulatory requirements related to setpoint control including the laws and guidance provided by the U.S. NRC. Chapter 3 provides describes the setpoint methodology including terms, formulae, methods of combination, graded approach and methods for drift analysis. This is a major part of the training module in covering the incremental uncertainty terms that need to be considered and how they are combined. Chapter 4 provides and overview of the role of setpoints in Technical Specifications and associated documents. Chapter 5 describes how the regulatory process, related to setpoint control, has been implemented in NRC inspections and how the major elements of the 10 CFR 50.59 reviews apply to the performance of a new or revised setpoint calculation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1986

Development of an expert system prototype for determining software functional requirements for command management activities at NASA Goddard

The development of an expert system prototype for software functional requirement determination for NASA Goddard's Command Management System, as part of its process of transforming general requests into specific near-earth satellite commands, is described. The present knowledge base was formulated through interactions with domain experts, and was then linked to the existing Knowledge Engineering Systems (KES) expert system application generator. Steps in the knowledge-base development include problem-oriented attribute hierarchy development, knowledge management approach determination, and knowledge base encoding. The KES Parser and Inspector, in addition to backcasting and analogical mapping, were used to validate the expert system-derived requirements for one of the major functions of a spacecraft, the solar Maximum Mission. Knowledge refinement, evaluation, and implementation procedures of the expert system were then accomplished.

Liebowitz, J.↗

NASA NTRS1994

Delivering spacecraft control centers with embedded knowledge-based systems: The methodology issue

Matra Marconi Space (MMS) occupies a leading place in Europe in the domain of satellite and space data processing systems. The maturity of the knowledge-based systems (KBS) technology, the theoretical and practical experience acquired in the development of prototype, pre-operational and operational applications, make it possible today to consider the wide operational deployment of KBS's in space applications. In this perspective, MMS has to prepare the introduction of the new methods and support tools that will form the basis of the development of such systems. This paper introduces elements of the MMS methodology initiatives in the domain and the main rationale that motivated the approach. These initiatives develop along two main axes: knowledge engineering methods and tools, and a hybrid method approach for coexisting knowledge-based and conventional developments.

Ayache, S.↗

NASA NTRS1989

Reusable rocket engine turbopump health monitoring system, part 3

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Perry, John G.↗

NASA NTRS1990

Machine learning research 1989-90

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base.

Porter, Bruce W.↗

NASA NTRS1986

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

Liebowitz, Jay↗

NASA NTRS2016

Enhancing Systems Engineering Education Through Case Study Writing

Developing and refining methods for teaching systems engineering is part of Systems Engineering grand challenges and agenda for research in the SE research community. Retention of systems engineering knowledge is a growing concern in the United States as the baby boom generation continues to retire and the faster pace of technology development does not allow for younger generations to gain experiential knowledge through years of practice. Government agencies, including the National Aeronautics and Space Administration (NASA), develop their own curricula and SE leadership development programs to "grow their own" systems engineers. Marshall Space Flight Center (MSFC) conducts its own Center-focused Marshall Systems Engineering Leadership Development Program (MSELDP), a competitive program consisting of coursework, a guest lecture series, and a rotational assignment into an unfamiliar organization engaged in systems engineering. Independently, MSFC developed two courses to address knowledge retention and sharing concerns: Real World Marshall Mission Success course and its Case Study Writers Workshop and Writers Experience. Teaching case study writing and leading students through a hands-on experience at writing a case study on an SE topic can enhance SE training and has the potential to accelerate the transfer of experiential knowledge. This paper is an overview of the pilot experiences with teaching case study writing, its application in case study-based learning, and identifies potential areas of research and application for case study writing in systems engineering education.

Stevens, Jennifer Stenger↗

DOE OSTI2018

Extracting Knowledge from Data through Catalysis Informatics

Catalysis informatics is a distinct sub-field that lies at the intersection of cheminformatics and materials informatics, but with unique challenges arising from the dynamic, surface-sensitive, multi-scale nature of heterogeneous catalysis. The ideas behind catalysis informatics can be traced back decades, but the field is only recently emerging due to advances in data infrastructure, statistics, machine learning, and computational methods. In this work we review the field from early works on expert systems and knowledge engines to more recent approaches utilizing machine-learning and uncertainty quantification. The data-information-knowledge hierarchy is introduced and used to classify various developments. The chemical master equation and micro-kinetic models are proposed as a quantitative representation of catalysis knowledge, which can be used to generate explanative and predictive hypotheses for the understanding and discovery of catalytic materials. We discuss future prospects for the field, including improved quantitative coupling of experiment/theory, advanced micro-kinetic models, and the development of open-source software tools. As a result, integration of existing chemical and physical models with emerging statistical and computational tools presents a promising route toward the automated design, discovery, and optimization of heterogeneous catalytic processes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2010

Developing Systems Engineering Skills Through NASA Summer Intern Project

During the Formulation phases of the NASA Project Life Cycle, communication systems engineers are responsible for designing space communication links and analyzing their performance to ensure that the proposed communication architecture is capable of satisfying high-level mission requirements. Senior engineers with extensive experience in communications systems perform these activities. However, the increasing complexity of space systems coupled with the current shortage of communications systems engineers has led to an urgent need for expedited training of new systems engineers. A pilot program, in which college-bound high school and undergraduate students studying various engineering disciplines are immersed in NASA s systems engineering practices, was conceived out of this need. This rapid summerlong training approach is feasible because of the availability of advanced software and technology tools and the students inherent ability to operate such tools. During this pilot internship program, a team of college-level and recently-hired engineers configured and utilized various software applications in the design and analysis of communication links for a plausible lunar sortie mission. The approach taken was to first design the direct-to-Earth communication links for the lunar mission elements, then to design the links between lunar surface and lunar orbital elements. Based on the data obtained from these software applications, an integrated communication system design was realized and the students gained valuable systems engineering knowledge. This paper describes this approach to rapidly training college-bound high school and undergraduate engineering students from various disciplines in NASA s systems engineering practices and tools. A summary of the potential use of NASA s emerging systems engineering internship program in broader applications is also described.

Bhasin, Kul↗

NASA NTRS1990

Software support environment design knowledge capture

The objective of this task is to assess the potential for using the software support environment (SSE) workstations and associated software for design knowledge capture (DKC) tasks. This assessment will include the identification of required capabilities for DKC and hardware/software modifications needed to support DKC. Several approaches to achieving this objective are discussed and interim results are provided: (1) research into the problem of knowledge engineering in a traditional computer-aided software engineering (CASE) environment, like the SSE; (2) research into the problem of applying SSE CASE tools to develop knowledge based systems; and (3) direct utilization of SSE workstations to support a DKC activity.

Dollman, Tom↗

NASA NTRS2013

Spring 2013 Graduate Engineering Internship Summary

In the spring of 2013, I participated in the National Aeronautics and Space Administration (NASA) Pathways Intern Employment Program at the Kennedy Space Center (KSC) in Florida. This was my final internship opportunity with NASA, a third consecutive extension from a summer 2012 internship. Since the start of my tenure here at KSC, I have gained an invaluable depth of engineering knowledge and extensive hands-on experience. These opportunities have granted me the ability to enhance my systems engineering approach in the field of payload design and testing as well as develop a strong foundation in the area of composite fabrication and testing for repair design on space vehicle structures. As a systems engineer, I supported the systems engineering and integration team with final acceptance testing of the Vegetable Production System, commonly referred to as Veggie. Verification and validation (V and V) of Veggie was carried out prior to qualification testing of the payload, which incorporated the process of confirming the system's design requirements dependent on one or more validation methods: inspection, analysis, demonstration, and testing.

Ehrlich, Joshua↗

NASA NTRS1994

Merging Intelligent Systems Technologies with CFD Analysis Strategies: Prototype Development at NASA Ames

A collaborative team of researchers from fields of Computational Fluid Dynamics (CFD), fluid physics, computer architectures, and computer science and knowledge engineering have begun work on a prototype system that addresses several of industry's concerns in using NASA-developed CFD codes as part of the design cycle. A major problem exists in the application of CFD technologies within the aeronautics design cycle due primarily to misunderstandings in the ranges of applicability of the various solver codes or turbulence models. Features that arise during the CFD solution process need to be discriminated and recognized as actual flow features with physical support in the geometry and flow conditions of the problem being solved, or as numerical or non-physical errors arising from mis-application of solver code and its parameters, gridding strategies, or discretization. interpolations. The fundamental concept is to develop an intelligent computational system that can accept the engineer's definition of the problem and construct an optimal CFD solution. To do this requires capturing both the knowledge of how to apply the various CFD tools and how to adapt the application of those tools to flow structures as they evolve during the flow simulation. Embedded within this adaptive system approach is the additional desire to automatically identify and quantify the quality of resolution of the pertinent flow structures, be they genuine or error-induced, and then to adjust the solution strategy accordingly. This paper discusses the status of that prototyping effort.

Thompson, David E.↗

NASA NTRS1992

Knowledge base methodology: Methodology for first Engineering Script Language (ESL) knowledge base

The primary goal of reusing software components is that software can be developed faster, cheaper and with higher quality. Though, reuse is not automatic and can not just happen. It has to be carefully engineered. For example a component needs to be easily understandable in order to be reused, and it has also to be malleable enough to fit into different applications. In fact the software development process is deeply affected when reuse is being applied. During component development, a serious effort has to be directed toward making these components as reusable. This implies defining reuse coding style guidelines and applying then to any new component to create as well as to any old component to modify. These guidelines should point out the favorable reuse features and may apply to naming conventions, module size and cohesion, internal documentation, etc. During application development, effort is shifted from writing new code toward finding and eventually modifying existing pieces of code, then assembling them together. We see here that reuse is not free, and therefore has to be carefully managed.

Peeris, Kumar↗