SEARCH · Search NASA

Results for “Knowledge Management”

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 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS2021

Future Model-Based Systems Engineering Vision and Strategy Bridge for NASA

A vision for the future of model-based systems engineering (MBSE) at NASA in 2029 and a strategy bridge towards that future are presented. Strategic thinking and leading change concepts were used to analyze reports and presentations on global trends and visionary thinking about the future of systems and digital engineering. The context, strategic time horizon, stakeholders, strategic challenges, strategic advantages, driving forces, and opportunities were considered. The analysis resulted in a future vision of MBSE that shows what NASA systems engineers and digital machines will do to perform rapid, extraordinary, and unprecedented missions. The NASA systems engineer, in this future vision, works with a global project team in a virtual and collaborative environment, engineers the system, and uses digital approaches as the routine and default way of working. The digital machines provide data-driven and automated mission designs; have a backbone of program and project management, systems engineering, and product life-cycle management; and are a knowledge-sharing infrastructure. The NASA systems engineer and the systems engineering team are envisioned to use digital machines to plan and perform rapid exploration missions, develop a digital twin that lasts across the life cycle, and develop enduring and adaptable systems. NASA has an engineering enterprise and a life-cycle management framework that endure, adapt, and respond. A strategy bridge based on the Baldrige Criteria for Performance Excellence Framework and lessons learned from a recent MBSE initiative illuminates a way forward from today to this desired future. The bridge lays out a strategy for leaders and recommends investments of today for immediate benefits and for benefits in 2029.

model-based systems engineering, digital engineeri↗

NASA NTRS1992

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMAID)

This paper discusses the addition of two new enhancements to the program Design Manager's Aide for Intelligent Decomposition (DeMAID). DeMAID is a knowledge-based tool used to aid a design manager in understanding the interactions among the tasks of a complex design problem. This is done by ordering the tasks to minimize feedback, determining the participating subsystems, and displaying them in an easily understood format. The two new enhancements include (1) rules for ordering a complex assembly process and (2) rules for determining which analysis tasks must be re-executed to compute the output of one task based on a change in input to that or another task.

Rogers, James L.↗

NASA NTRS1992

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMaid)

Rogers, James L.↗

NASA NTRS2008

2008 Year in Review

In February of 2008; NASA Stennis Space Center (SSC), NASA Kennedy Space Center (KSC), and The Applied Research Laboratory at Penn State University demonstrated a pilot implementation of an Integrated System Health Management (ISHM) capability at the Launch Complex 20 of KSC. The following significant accomplishments are associated with this development: (1) implementation of an architecture for ground operations ISHM, based on networked intelligent elements; (2) Use of standards for management of data, information, and knowledge (DIaK) leading to modular ISHM implementation with interoperable elements communicating according to standards (three standards were used: IEEE 1451 family of standards for smart sensors and actuators, Open Systems Architecture for Condition Based Maintenance (OSA-CBM) standard for communicating DIaK describing the condition of elements of a system, and the OPC standard for communicating data); (3) ISHM implementation using interoperable modules addressing health management of subsystems; and (4) use of a physical intelligent sensor node (smart network element or SNE capable of providing data and health) along with classic sensors originally installed in the facility. An operational demonstration included detection of anomalies (sensor failures, leaks, etc.), determination of causes and effects, communication among health nodes, and user interfaces.

Figueroa, Jorge Fernando↗

NASA NTRS2006

Bioinformatics for Exploration

For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

Johnson, Kathy A.↗

NASA NTRSDate not supplied

Using Artificial Intelligence (AI) and Machine Learning (ML) to conduct Space Missions Solid Waste Management Survey

The National Aeronautics and Space Administration (NASA) Solid Waste Management team has been focusing on technologies that can operate in microgravity. NASA aims to conduct both short and long-term transit and planetary missions on the lunar and Mars surfaces. Therefore, an updated waste survey is needed to explore technologies for operation in microgravity for transit missions and partial gravity for planetary missions. This paper will utilize Artificial Intelligence and Machine Learning techniques to conduct the survey and generate knowledge graphs for Spacecraft Waste Management.

Artificial Intelligence↗

NASA NTRS1992

Automated support for experience-based software management

To effectively manage a software development project, the software manager must have access to key information concerning a project's status. This information includes not only data relating to the project of interest, but also, the experience of past development efforts within the environment. This paper describes the concepts and functionality of a software management tool designed to provide this information. This tool, called the Software Management Environment (SME), enables the software manager to compare an ongoing development effort with previous efforts and with models of the 'typical' project within the environment, to predict future project status, to analyze a project's strengths and weaknesses, and to assess the project's quality. In order to provide these functions the tool utilizes a vast corporate memory that includes a data base of software metrics, a set of models and relationships that describe the software development environment, and a set of rules that capture other knowledge and experience of software managers within the environment. Integrating these major concepts into one software management tool, the SME is a model of the type of management tool needed for all software development organizations.

Valett, Jon D.↗

NASA NTRS1971

Introduction

Management of earth resources requires accurate knowledge of inventories. Developments of improved remote sensing devices and vehicles for their transport, and automatic data processing equipment and techniques are important management tools for an integrated earth resources survey in California.

Colwell, R. N.↗

NASA NTRS2003

Development of Management Metrics for Research and Technology

Professor Ted Sheskin from CSU will be tasked to research and investigate metrics that can be used to determine the technical progress for advanced development and research tasks. These metrics will be implemented in a software environment that hosts engineering design, analysis and management tools to be used to support power system and component research work at GRC. Professor Sheskin is an Industrial Engineer and has been involved in issues related to management of engineering tasks and will use his knowledge from this area to allow extrapolation into the research and technology management area. Over the course of the summer, Professor Sheskin will develop a bibliography of management papers covering current management methods that may be applicable to research management. At the completion of the summer work we expect to have him recommend a metric system to be reviewed prior to implementation in the software environment. This task has been discussed with Professor Sheskin and some review material has already been given to him.

Sheskin, Theodore J.↗

NASA NTRS2018

Model-Based Data Integration and Process Standardization Techniques for Fault Management: A Feasibility Study

This paper describes the theory and considerations in the application of model-based techniques to assimilate information from disjoint knowledge sources for performing NASA's Fault Management (FM)-related activities using the TEAMS® toolset. FM consists of the operational mitigation of existing and impending spacecraft failures. NASA's FM directives have both design-phase and operational-phase goals. This paper highlights recent studies by QSI and DST of the capabilities required in the TEAMS® toolset for conducting FM activities with the aim of reducing operating costs, increasing autonomy, and conforming to time schedules. These studies use and extend the analytic capabilities of QSI's TEAMS® toolset to conduct a range of FM activities within a centralized platform.

Haste, Deepak↗

DOE OSTI2026

The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts

Price dynamics in wholesale electricity markets are driven by supply and demand. In markets with hydroelectric dams, the timing and amount of hydropower offered can influence prices in similar ways to wind and solar power. Unlike variable renewable energy, however, the supply of hydropower in wholesale markets is a function of both water availability and operational decisions at dams. Dam operators maximize revenues in wholesale markets by aligning generation with the periods of highest expected prices, and these scheduling decisions may in turn influence prices. Here, we examine the relative importance of two types of information in predicting forward electricity prices: a) water availability at dams, in the form of short-to-medium-range hydrological forecasts; and b) hourly scheduling decisions at dams. Using softly coupled hydrologic, hydropower scheduling, and power systems models spanning the U.S. Western Interconnection, we quantify the importance of hydrologic forecast accuracy in correctly predicting wholesale electricity prices and compare this with the influence of dam operators’ own hourly scheduling decisions on realized market prices. We find that aligning hydropower generation schedules with the periods of high forecasted prices causes larger, inadvertent price forecast errors than imperfect hydrologic forecasts. This suggests that knowledge of how water is managed by dam operators within the week is more important than weekly inflow forecast errors when predicting forward electricity prices. Our findings have implications for optimal hydropower scheduling by region. Specifically, accounting for price effects is critical in markets dominated by hydropower capacity.

Electricity markets↗

NASA NTRS1985

Generative engineering databases - Toward expert systems

Engineering data management, incorporating concepts of optimization with data representation, is receiving increasing attention as the amount and complexity of information necessary for performing engineering operations increases and the need to coordinate its representation and use increases. Research in this area promises advantages for a wide variety of engineering applications, particularly those which seek to use data in innovative ways in the engineering process. This paper presents a framework for a comprehensive, relational database management system that combines a knowledge base of design constraints with a database of engineering data items in order to achieve a 'generative database' - one which automatically generates new engineering design data according to the design constraints stored in the knowledge base. The representation requires a database that is able to store all of the data normally associated with engineering design and to accurately represent the interactions between constraints and the stored data while guaranteeing its integrity. The representation also requires a knowledge base that is able to store all the constraints imposed upon the engineering design process.

Rasdorf, W. J.↗

NASA NTRS1985

DEASEL: An expert system for software engineering

For the past ten year, the Software Engineering Laboratory (SEL) has been collecting data on software projects carried out in the Systems Development Branch of the Flight Dynamics Division at NASA's Goddard Space Flight Center. Through a series of studies using this data, much knowledge has been gained on how software is developed within this environment. Two years ago work began on a software tool which would make this knowledge readily available to software managers. Ideally, the Dynamic Management Information Tool (DynaMITe) will aid managers in comparison across projects, prediction of a project's future, and assessment of a project's current state. This paper describes an effort to create the assessment portion of DynaMITe, called the DynaMITe Expert Advisor for the SEL (DEASEL).

Valett, J. D.↗

NASA NTRS1987

Space power system automation approaches at the George C. Marshall Space Flight Center

This paper discusses the automation approaches employed in various electrical power system breadboards at the Marshall Space Flight Center. Of particular interest is the application of knowledge-based systems to fault management and dynamic payload scheduling. A description of each major breadboard and the automation approach taken for each is given.

Weeks, D. J.↗

NASA NTRS1988

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.

Odell, Stephen L.↗

NASA NTRS2007

ISHM Anomaly Lexicon for Rocket Test

Integrated Systems Health Management (ISHM) is a comprehensive capability. An ISHM system must detect anomalies, identify causes of such anomalies, predict future anomalies, help identify consequences of anomalies for example, suggested mitigation steps. The system should also provide users with appropriate navigation tools to facilitate the flow of information into and out of the ISHM system. Central to the ability of the ISHM to detect anomalies is a clearly defined catalog of anomalies. Further, this lexicon of anomalies must be organized in ways that make it accessible to a suite of tools used to manage the data, information and knowledge (DIaK) associated with a system. In particular, it is critical to ensure that there is optimal mapping between target anomalies and the algorithms associated with their detection. During the early development of our ISHM architecture and approach, it became clear that a lexicon of anomalies would be important to the development of critical anomaly detection algorithms. In our work in the rocket engine test environment at John C. Stennis Space Center, we have access to a repository of discrepancy reports (DRs) that are generated in response to squawks identified during post-test data analysis. The DR is the tool used to document anomalies and the methods used to resolve the issue. These DRs have been generated for many different tests and for all test stands. The result is that they represent a comprehensive summary of the anomalies associated with rocket engine testing. Fig. 1 illustrates some of the data that can be extracted from a DR. Such information includes affected transducer channels, narrative description of the observed anomaly, and the steps used to correct the problem. The primary goal of the anomaly lexicon development efforts we have undertaken is to create a lexicon that could be used in support of an associated health assessment database system (HADS) co-development effort. There are a number of significant byproducts of the anomaly lexicon compilation effort. For example, (1) Allows determination of the frequency distribution of anomalies to help identify those with the potential for high return on investment if included in automated detection as part of an ISHM system, (2) Availability of a regular lexicon could provide the base anomaly name choices to help maintain consistency in the DR collection process, and (3) Although developed for the rocket engine test environment, most of the anomalies are not specific to rocket testing, and thus can be reused in other applications.

Schmalzel, John L.↗

NASA NTRS2008

SERVIR: Environmental Decision Making in the Americas

SERVIR is a regional visualization and monitoring system for Mesoamerica that integrates satellite and other geospatial data for improved scientific knowledge and decision making by managers, researchers, students, and the general public. SERVIR addresses the nine societal benefit areas of the Global Earth Observation System of Systems (GEOSS). This talk will provide an overview of products and services available through SERVIR.

Lapenta, William↗

NASA NTRS2009

Integrated System Health Management: Foundational Concepts, Approach, and Implementation

Implementation of integrated system health management (ISHM) capability is fundamentally linked to the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system. It is akin to having a team of experts who are all individually and collectively observing and analyzing a complex system, and communicating effectively with each other in order to arrive to an accurate and reliable assessment of its health. This paper presents concepts, procedures, and a specific approach as a foundation for implementing a credible ISHM capability. The capability stresses integration of DIaK from all elements of a subsystem. The intent is also to make possible implementation of on-board ISHM capability, in contrast to a remote capability. The information presented is the result of many years of research, development, and maturation of technologies, and of prototype implementations in operational systems (rocket engine test facilities). The paper will address the following topics: ISHM Model of a system; detection of anomaly indicators; determination and confirmation of anomalies; diagnostic of causes and determination of effects; consistency checking cycle; sharing of health information; sharing of display information; storage and retrieval of health information; and example implementation.

Figueroa, Fernando↗