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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Field Validation of a Building Operating System Platform

The U.S General Services Administration's (GSA's) Green Proving Ground program, in partnership with the National Renewable Energy Laboratory. completed a large pilot study of an Energy Management Information Systems (EMIS) with Automated System Optimization (ASO). Four test bed facilities, each with different building characteristics and systems, were chosen for the implementation of cloud-based EMIS with ASO. Depending on functionality, this tool can be extremely effective in energy management and energy optimization in buildings. The capabilities evaluated in the pilot ranged from energy savings and energy consumption predictions to evaluations of user acceptance, operability, and ease of installation. This report presents the methodology, lessons learned and best practices, and deployment recommendations for the GSA's portfolio of commercial office space, comprising more than 8,500 properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1992

Development of vendor evaluation criteria and post-implementation considerations for MSFC center-wide executive information system

In June 1991, the MITRE Corporation submitted a series of recommendations as part of a Marshall Space Flight Center (MSFC) Management Information System Requirements Study, initiated by the Information Systems Office (ISO). A major recommendation of the study was to develop an Executive Information System (EIS) for MSFC executives. ISO was directed, by center management, to proceed with the development of a Center-Wide Executive Information System. Existing EIS prototypes, developed by the Space Shuttle Projects Office and the Payload Projects Office, were reviewed. These existing MSFC prototypes were considered not to encompass the required functionality needed on a center-wide basis. A follow-up study by MITRE provided top-level system requirements. These were later incorporated into a final requirements specification document by Boeing Computer Support Services.

Moynihan, Gary P.↗
NASA NTRS1990

Using expert systems to implement a semantic data model of a large mass storage system

The successful development of large volume data storage systems will depend not only on the ability of the designers to store data, but on the ability to manage such data once it is in the system. The hypothesis is that mass storage data management can only be implemented successfully based on highly intelligent meta data management services. There now exists a proposed mass store system standard proposed by the IEEE that addresses many of the issues related to the storage of large volumes of data, however, the model does not consider a major technical issue, namely the high level management of stored data. However, if the model were expanded to include the semantics and pragmatics of the data domain using a Semantic Data Model (SDM) concept, the result would be data that is expressive of the Intelligent Information Fusion (IIF) concept and also organized and classified in context to its use and purpose. The results are presented of a demonstration prototype SDM implemented using the expert system development tool NEXPERT OBJECT. In the prototype, a simple instance of a SDM was created to support a hypothetical application for the Earth Observing System, Data Information System (EOSDIS). The massive amounts of data that EOSDIS will manage requires the definition and design of a powerful information management system in order to support even the most basic needs of the project. The application domain is characterized by a semantic like network that represents the data content and the relationships between the data based on user views and the more generalized domain architectural view of the information world. The data in the domain are represented by objects that define classes, types and instances of the data. In addition, data properties are selectively inherited between parent and daughter relationships in the domain. Based on the SDM a simple information system design is developed from the low level data storage media, through record management and meta data management to the user interface.

Roelofs, Larry H.↗
NASA NTRS2009

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

Arnold, Steven M.↗
NASA NTRS2009

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

Arnold, Steven M.↗
DOE OSTI2022

Best Practices to Support EMIS Operation at Federal Facilities

The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of Energy Management Information Systems (EMIS) at federal facilities, as detailed in the EMIS Technical Resources Report. A series of best practices documents was created by FEMP to help accelerate the market adoption and use of EMIS in the federal sector. This document highlights best practices for supporting EMIS use at federal facilities.

EMIS↗
NASA NTRS1973

Managemant of NASA's major projects

Approaches used to manage major projects are studied and the existing documents on NASA management are reviewed. The work consists of: (1) the project manager's role, (2) request for proposal, (3) project plan, (4) management information system, (5) project organizational thinking, (6) management disciplines, (7) important decisions, and (8) low cost approach.

James, L. B.↗
NASA NTRS1984

The pilot climate data system

The Pilot Climate Data System (PCDS) is an interactive scientific information management system for locating, obtaining, manipulating, and displaying climate-research data. The PCDS was developed to manage a large collection of data of interest to the National Aeronautics and Space Administration's (NASA) research community and currently provides such support for approximately twenty data sets. In order to provide the PCDS capabilities, NASA's Goddard Space Flight Center (NASA/GSFC) has integrated the capabilities of several general-purpose software packages with specialized software for reading and reformatting the supported data sets. These capabilities were integrated in a manner which allows the PCDS to be easily expanded, either to provide support for additional data sets or to provide additional functional capabilities. This also allows the PCDS to take advantage of new technology as it becomes available, since parts of the system can be replaced with more powerful components without significantly affecting the user interface.

Reph, M. G.↗
NASA NTRS1989

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗
DOE OSTI2021

Y-12 Groundwater Protection Program Data Management Plan

This Data Management Plan (DMP) describes the processes in place to ensure the integrity of groundwater monitoring information collected by the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA), Y-12 National Security Complex (Y-12), Groundwater Protection Program (GWPP). This information includes program plans, reports, and computer systems used to capture monitoring station information and analytical data. The primary computer system used by the GWPP is the Groundwater Information Management System (GIMS). Procedures used to ensure the integrity of the data are included in this document by reference.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

R and D Productivity: New Challenges for the US Space Program

Various topics related to research and development activities applicable to their U.S. space program are discussed. Project management, automatic control technology, human resources, management information systems, computer aided design, systems engineering, and personnel management were among the topics covered.

Otis W Baskin↗
NASA NTRS1989

Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and synergistically-related infectious diseases.

Rochon, Gilbert L.↗
NASA NTRS1984

Concepts for a global resources information system

The objective of the Global Resources Information System (GRIS) is to establish an effective and efficient information management system to meet the data access requirements of NASA and NASA-related scientists conducting large-scale, multi-disciplinary, multi-mission scientific investigations. Using standard interfaces and operating guidelines, diverse data systems can be integrated to provide the capabilities to access and process multiple geographically dispersed data sets and to develop the necessary procedures and algorithms to derive global resource information.

Billingsley, F. C.↗
DOE OSTI2021

VizEng

VisEng is a data presentation and display system directed at presenting information generated by a plant information management system. This system allows multiple levels of drilldown from a high level system management interface down to technical implementation details of the actual system. This is a system awareness infrastructure application, which is meant to bridge the role based knowledge gap and give all operation room workers understandable and actionable complete state awareness. The aggregated system resources create an expandable and scalable display methodology that can fit any use case.

Lehmer, JacobP.↗
NASA NTRS1992

The function of the earth observing system - Data information system Distributed Active Archive Centers

The functionality of the Distributed Active Archive Centers (DAACs) which are significant elements of the Earth Observing System Data and Information System (EOSDIS) is discussed. Each DAAC encompasses the information management system, the data archival and distribution system, and the product generation system. The EOSDIS DAACs are expected to improve the access to earth science data set needed for global change research.

Lapenta, C. C.↗