Effective techniques for capturing, creating, and management knowledge at NASA
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knowledge management↗
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Expert System Control of Plant Growth in an Enclosed Space
The Expert System is an enclosed, controlled environment for growing plants, which incorporates a computerized, knowledge-based software program that is designed to capture the knowledge, experience, and problem-solving skills of one or more human experts in a particular discipline. The Expert System is trained to analyze crop/plant status, to monitor the condition of the plants and the environment, and to adjust operational parameters to optimize the plant-growth process. This system is intended to provide a way to remotely control plant growth with little or no human intervention. More specifically, the term control implies an autonomous method for detecting plant states such as health (biomass) or stress and then for recommending and implementing cultivation and/or remediation to optimize plant growth and to minimize consumption of energy and nutrients. Because of difficulties associated with delivering energy and nutrients remotely, a key feature of this Expert System is its ability to minimize this effort and to achieve optimum growth while taking into account the diverse range of environmental considerations that exist in an enclosed environment. The plant-growth environment for the Expert System could be made from a variety of structures, including a greenhouse, an underground cavern, or another enclosed chamber. Imaging equipment positioned within or around the chamber provides spatially distributed crop/plant-growth information. Sensors mounted in the chamber provide data and information pertaining to environmental conditions that could affect plant development. Lamps in the growth environment structure supply illumination, and other additional equipment in the chamber supplies essential nutrients and chemicals.
May, George↗
On the acquisition and representation of procedural knowledge
Historically knowledge acquisition has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some of some types of knowledge, little attention has been devoted to procedural knowledge. NASA personnel frequently perform tasks that are primarily procedural in nature. Previous work is reviewed in the field of knowledge acquisition and then focus on knowledge acquisition for procedural tasks with special attention devoted to the Navy's VISTA tool. The design and development is described of a system for the acquisition and representation of procedural knowledge-TARGET (Task Analysis and Rule Generation Tool). TARGET is intended as a tool that permits experts to visually describe procedural tasks and as a common medium for knowledge refinement by the expert and knowledge engineer. The system is designed to represent the acquired knowledge in the form of production rules. Systems such as TARGET have the potential to profoundly reduce the time, difficulties, and costs of developing knowledge-based systems for the performance of procedural tasks.
Saito, T.↗
Knowledge Transfer Program for International Nuclear Safeguards
Nuclear safeguards were first announced in 1945 by the U.S., Canadian and British governments as a means to exchange scientific information about peaceful uses of atomic energy and prevent the use of nuclear material for weapons. International nuclear safeguards, now under the provision of the International Atomic Energy Agency (IAEA), serves to hold accountable the 140 member countries (States) that have entered into treaties and agreements against the spread of nuclear weapons. Most notably, the IAEA acts as a nuclear materials inspectorate under the global Nuclear Non-Proliferation Treaty, brought about in 1968, that specifies commitments member States make to the world?s non-proliferation regime. The Office of International Nuclear Safeguards (OINS) is part of the National Nuclear Security Administration, a semi-autonomous agency within the U.S. Department of Energy. Within OINS, the Human Capital Development program recognizes the need to build workforce capacity and safeguards expertise. This includes supporting the education and training of younger generations working in international nuclear safeguards. One of the program?s main concerns is core competencies being lost to retirement or attrition and building knowledge retention pipelines from senior to new professionals. One identified core competency is knowledge gained by individuals who have completed IAEA assignments such as missions to member States to conduct safeguards inspections. Such individuals possess unique knowledge, and efforts are being put forth to effectively capture this knowledge within the national laboratories complex. To this end, we report findings from a one-year mentor-mentee knowledge retention program in which an international safeguards subject matter expert imparted knowledge and skills to a willing professional mentee. The knowledge and skills stem from the mentor?s multi-year assignment at the IAEA in Vienna, Austria.
98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
EDNA: Expert fault digraph analysis using CLIPS
Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.
Dixit, Vishweshwar V.↗
Theory and ontology for sharing temporal knowledge
Using current technology, the sharing or re-using of knowledge-bases is very difficult, if not impossible. ARPA has correctly recognized the problem and funded a knowledge sharing initiative. One of the outcomes of this project is a formal language called Knowledge Interchange Format (KIF) for representing knowledge that could be translated into other languages. Capturing and representing design knowledge and reasoning with them have become very important for NASA who is a pioneer of innovative design of unique products. For upgrading an existing design for changing technology, needs, or requirements, it is essential to understand the design rationale, design choices, options and other relevant information associated with the design. Capturing such information and presenting them in the appropriate form are part of the ongoing Design Knowledge Capture project of NASA. The behavior of an object and various other aspects related to time are captured by the appropriate temporal knowledge. The captured design knowledge will be represented in such a way that various groups of NASA who are interested in various aspects of the design cycle should be able to access and use the design knowledge effectively. To facilitate knowledge sharing among these groups, one has to develop a very well defined ontology. Ontology is a specification of conceptualization. In the literature several specific domains were studied and some well defined ontologies were developed for such domains. However, very little, or no work has been done in the area of representing temporal knowledge to facilitate sharing. During the ASEE summer program, I have investigated several temporal models and have proposed a theory for time that is flexible to accommodate the time elements, such as, points and intervals, and is capable of handling the qualitative and quantitative temporal constraints. I have also proposed a primitive temporal ontology using which other relevant temporal ontologies can be built. I have investigated various issues of sharing knowledge and have proposed a formal framework for modeling the concept of knowledge sharing. This work may be implemented and tested in the software environment supplied by Knowledge Based System, Inc.
Loganantharaj, Rasiah↗
The nutrition advisor expert system
The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.
Huse, Scott M.↗
Automated knowledge base development from CAD/CAE databases
Knowledge base development requires a substantial investment in time, money, and resources in order to capture the knowledge and information necessary for anything other than trivial applications. This paper addresses a means to integrate the design and knowledge base development process through automated knowledge base development from CAD/CAE databases and files. Benefits of this approach include the development of a more efficient means of knowledge engineering, resulting in the timely creation of large knowledge based systems that are inherently free of error.
Wright, R. Glenn↗
Determining rules for closing customer service centers: A public utility company's fuzzy decision
In the present work, we consider the general problem of knowledge acquisition under uncertainty. Simply stated, the problem reduces to the following: how can we capture the knowledge of an expert when the expert is unable to clearly formulate how he or she arrives at a decision? A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision may have been made. Unique to our work is the fuzzy set representation of the conditions or attributes upon which the expert may possibly base his fuzzy decision. From our examples, we infer certain and possible fuzzy rules for closing a customer service center and illustrate the importance of having the decision closely relate to the conditions under consideration.
Dekorvin, Andre↗
How do we Remain Us in a Time of Change: Culture and Knowledge Management at NASA
This viewgraph representation presents an overview of findings of a NASA agency-wide Knowledge Management Team considering culture and knowledge management issues at the agency. Specific issues identified by the team include: (1) NASA must move from being a knowledge hoarding culture to a knowledge sharing culture; (2) NASA must move from being center focused to being Agency focused; (3) NASA must capture the knowledge of a departing workforce. Topics considered include: what must NASA know to remain NASA, what were previous forms of knowledge reproduction and how has technological innovations changed these systems, and what changes in funding and relationships between contractors and NASA affected knowledge reproduction.
Linde, Charlotte↗
Developing an Advanced Environment for Collaborative Computing
Knowledge management in general tries to organize and make available important know-how, whenever and where ever is needed. Today, organizations rely on decision-makers to produce "mission critical" decisions that am based on inputs from multiple domains. The ideal decision-maker has a profound understanding of specific domains that influence the decision-making process coupled with the experience that allows them to act quickly and decisively on the information. In addition, learning companies benefit by not repeating costly mistakes, and by reducing time-to-market in Research & Development projects. Group-decision making tools can help companies make better decisions by capturing the knowledge from groups of experts. Furthermore, companies that capture their customers preferences can improve their customer service, which translates to larger profits. Therefore collaborative computing provides a common communication space, improves sharing of knowledge, provides a mechanism for real-time feedback on the tasks being performed, helps to optimize processes, and results in a centralized knowledge warehouse. This paper presents the research directions. of a project which seeks to augment an advanced collaborative web-based environment called Postdoc, with workflow capabilities. Postdoc is a "government-off-the-shelf" document management software developed at NASA-Ames Research Center (ARC).
Becerra-Fernandez, Irma↗
Novel Problem Solving - The NASA Solution Mechanism Guide
Over the past five years, the Human Health and Performance (HH&P) Directorate at the NASA Johnson Space Center (JSC) has conducted a number of pilot and ongoing projects in collaboration and open innovation. These projects involved the use of novel open innovation competitions that sought solutions from "the crowd", non-traditional problem solvers. The projects expanded to include virtual collaboration centers such as the NASA Human Health and Performance Center (NHHPC) and more recently a collaborative research project between NASA and the National Science Foundation (NSF). These novel problem-solving tools produced effective results and the HH&P wanted to capture the knowledge from these new tools, to teach the results to the directorate, and to implement new project management tools and coursework. The need to capture and teach the results of these novel problem solving tools, the HH&P decided to create a web-based tool to capture best practices and case studies, to teach novice users how to use new problem solving tools and to change project management training/. This web-based tool was developed with a small, multi-disciplinary group and named the Solution Mechanism Guide (SMG). An alpha version was developed that was tested against several sessions of user groups to get feedback on the SMG and determine a future course for development. The feedback was very positive and the HH&P decided to move to the beta-phase of development. To develop the web-based tool, the HH&P utilized the NASA Tournament Lab (NTL) to develop the software with TopCoder under an existing contract. In this way, the HH&P is using one new tool (the NTL and TopCoder) to develop the next generation tool, the SMG. The beta-phase of the SMG is planed for release in the spring of 2014 and results of the beta-phase testing will be available for the IAC meeting in September. The SMG is intended to disrupt the way problem solvers and project managers approach problem solving and to increase the use of novel and more cost and time effective problem solving tools such as open innovation, collaborative research, and virtual collaborative project centers. The HH&P envisions changing project management coursework by including the SMG in the teaching of project management problem solving tools.
Keeton, Kathryn E.↗
Electrochemistry-based Battery Modeling for Prognostics
Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.
battery↗
Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach
With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.
97 - MATHEMATICS AND COMPUTING↗
Model-based diagnostics for Space Station Freedom
An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.
Fesq, Lorraine M.↗
Evaluation of Commercial-Off-The-Shelf (COTS) Electronics for Extreme Cold Environments
Deep space and Icy Moon missions (Titan, Enceladus, Ceres, Europa, & Ganymede) will need qualified extreme environment capable components for electronic systems located in extremities of their rovers and spacecraft. Commercial off the shelf (COTS) components would be advantageous to use for some aspects of such projects, given that they are easier to procure and offer a broad range of functionalities. Furthermore, theoretical and experimental data suggest that many COTS parts are capable of operation, and not just storage, at temperatures well beyond the manufacturer specified temperature limits. To help address the challenges presented at near cryogenic temperatures, a COTS selection knowledge base is being developed to estimate the performance of COTS components within cold environments. The knowledge base captures queries from a range of information sources such as cold functionality test results for part types and families, theoretical and experimental literature reviews and key findings are summarized here. In addition, a selection of components are planned to be examined for their performance to near cryogenic temperatures to generate a methodology for identification and verification of the COTS candidates. As the qualification of COTS parts for extreme environments can be very costly, this knowledge base can serve to reduce qualification time and cost by pre-selecting and limiting candidates.
Mojarradi, Mohammad↗
Enabling Innovation and Collaboration Across Geography and Culture: A Case Study of NASA's Systems Engineering Community of Practice
In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited personnel from sharing experiences and ideas. Mission failures and new directions for the agency demanded better collaborative tools. In addition, with the push to send astronauts back to the moon and to Mars, NASA recognized that systems engineering would have to improve across the agency. Of the ten field centers, seven had not built a spacecraft in over 30 years, and had lost systems engineering expertise. The Systems Engineering Community of Practice came together to capture the knowledge of its members using the suite of collaborative tools provided by the NASA Engineering Network (NEN.) The NEN provided a secure collaboration space for over 60 practitioners across the agency to assemble and review a NASA systems engineering handbook. Once the handbook was complete, they used the open community area to disseminate it. This case study explores both the technology and the social networking that made the community possible, describes technological approaches that facilitated rapid setup and low maintenance, provides best practices that other organizations could adopt, and discusses the vision for how this community will continue to collaborate across the field centers to benefit the agency as it continues exploring the solar system.
NEN↗
ACES: Space shuttle flight software analysis expert system
The Analysis Criteria Evaluation System (ACES) is a knowledge based expert system that automates the final certification of the Space Shuttle onboard flight software. Guidance, navigation and control of the Space Shuttle through all its flight phases are accomplished by a complex onboard flight software system. This software is reconfigured for each flight to allow thousands of mission-specific parameters to be introduced and must therefore be thoroughly certified prior to each flight. This certification is performed in ground simulations by executing the software in the flight computers. Flight trajectories from liftoff to landing, including abort scenarios, are simulated and the results are stored for analysis. The current methodology of performing this analysis is repetitive and requires many man-hours. The ultimate goals of ACES are to capture the knowledge of the current experts and improve the quality and reduce the manpower required to certify the Space Shuttle onboard flight software.
Satterwhite, R. Scott↗