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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The road plan model: Information model for planning road building activities

The general building contractor is presented with an information model as an approach for deriving a high-level work plan of construction activities applied to road building. Road construction activities are represented in a Road Plan Model (RPM), which is modeled in the ISO standard STEP/EXPRESS and adopts various concepts from the GARM notation. The integration with the preceding road design stage and the succeeding phase of resource scheduling is discussed within the framework of a Road Construction Model. Construction knowledge is applied to the road design and the terrain model of the surrounding road infrastructure for the instantiation of the RPM. Issues regarding the implementation of a road planner application supporting the RPM are discussed.

Azinhal, Rafaela K.↗
NASA NTRS1973

Designing control system information models

Problems encountered in modeling information models are discussed, Data cover condition, functioning of the object of control, and the environment involved in the control. Other parameters needed for the model include: (1) information for forming an image of the real situation, (2) data for analyzing and evaluating an evolving situation, (3) planning actions, and (4) data for observing and evaluating the results of model realization.

Panin, K. I.↗
NASA NTRS1991

Spiral model pilot project information model

The objective was an evaluation of the Spiral Model (SM) development approach to allow NASA Marshall to develop an experience base of that software management methodology. A discussion is presented of the Information Model (IM) that was used as part of the SM methodology. A key concept of the SM is the establishment of an IM to be used by management to track the progress of a project. The IM is the set of metrics that is to be measured and reported throughout the life of the project. These metrics measure both the product and the process to ensure the quality of the final delivery item and to ensure the project met programmatic guidelines. The beauty of the SM, along with the IM, is the ability to measure not only the correctness of the specification and implementation of the requirements but to also obtain a measure of customer satisfaction.

Source record↗
NASA NTRS2008

An Ontology-Based Archive Information Model for the Planetary Science Community

The Planetary Data System (PDS) information model is a mature but complex model that has been used to capture over 30 years of planetary science data for the PDS archive. As the de-facto information model for the planetary science data archive, it is being adopted by the International Planetary Data Alliance (IPDA) as their archive data standard. However, after seventeen years of evolutionary change the model needs refinement. First a formal specification is needed to explicitly capture the model in a commonly accepted data engineering notation. Second, the core and essential elements of the model need to be identified to help simplify the overall archive process. A team of PDS technical staff members have captured the PDS information model in an ontology modeling tool. Using the resulting knowledge-base, work continues to identify the core elements, identify problems and issues, and then test proposed modifications to the model. The final deliverables of this work will include specifications for the next generation PDS information model and the initial set of IPDA archive data standards. Having the information model captured in an ontology modeling tool also makes the model suitable for use by Semantic Web applications.

Information Model↗
DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

The PDS4 Information Model Design Principles - How Well Did They Work?

The Planetary Data System (PDS) recently released Version 1.5 of the PDS4 Information Model, the primary component of the PDS4 Information Architecture. The Information Model is now stable and is in use by three active missions and several missions in various phases of development. The Information Model drives the PDS4 Information System using a multi-level governance structure that provides for common, discipline, and mission level management of the system’s information standards. For the development of the PDS4 Information Model several design principles were adopted. This paper will describe each design principle and then explain how well they worked, problems encountered during development and their solutions, and how well the results meet the requirements of the multi-discipline planetary science community.

Martin, Michael↗
NASA NTRS2013

Virtual Construction of Space Habitats: Connecting Building Information Models (BIM) and SysML

Current trends in design, construction and management of complex projects make use of Building Information Models (BIM) connecting different types of data to geometrical models. This information model allow different types of analysis beyond pure graphical representations. Space habitats, regardless their size, are also complex systems that require the synchronization of many types of information and disciplines beyond mass, volume, power or other basic volumetric parameters. For this, the state-of-the-art model based systems engineering languages and processes - for instance SysML - represent a solid way to tackle this problem from a programmatic point of view. Nevertheless integrating this with a powerful geometrical architectural design tool with BIM capabilities could represent a change in the workflow and paradigm of space habitats design applicable to other aerospace complex systems. This paper shows some general findings and overall conclusions based on the ongoing research to create a design protocol and method that practically connects a systems engineering approach with a BIM architectural and engineering design as a complete Model Based Engineering approach. Therefore, one hypothetical example is created and followed during the design process. In order to make it possible this research also tackles the application of IFC categories and parameters in the aerospace field starting with the application upon the space habitats design as way to understand the information flow between disciplines and tools. By building virtual space habitats we can potentially improve in the near future the way more complex designs are developed from very little detail from concept to manufacturing.

space architecture↗
DOE OSTI2023

A Power Application Developer’s Guide to the Common Information Model: An Introduction for Power Systems Engineers and Application Developers – CIM17v40

A key issue in creating the next generation of energy management system (EMS) and advanced distribution management system (ADMS) platforms will be the ability to represent and exchange power system network model data in a consistent manner. To this end, the Common Information Model (CIM) stands out as the only standardized vocabulary (or ontology) for defining power system network models and asset data in a comprehensive, consistent manner across the generation-transmission-distribution boundary. The CIM is freely available to use and extend. The CIM is maintained by the UCAiug (informally known as the CIM User’s Group) under an Apache 2.0 license. The CIM Users Group collaborates with the IEC and other standards communities for the development of technical and informative specifications. Although portions of the information model are referred to by the corresponding IEC standards naming, it is not necessary to purchase any of the IEC standards to use the CIM information model. This document provides a roadmap for power system engineers and application developers not familiar with semantic modeling to start using the CIM for modeling, simulation, optimization, and development of advanced power applications. The key classes needed for defining power system topology and equipment are explained systematically. Key focus areas include modeling of lines, transformers, generators, switching equipment, loads, and distributed energy resources (DERs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Comprehensive Review of Practical Issues for Interoperability Using the Common Information Model in Smart Grids

Smart grids with interoperability improve grid reliability by collecting system information and transferring it to an energy management system and associated applications through a seamless end-to-end connection. To achieve interoperability, it is required to exchange the semantic information within the different domains. The international electrotechnical commission has established the Common Information Model (CIM) tool, which is a standard application programming interface for the exchange of semantic information in power systems. CIM provides a robust framework for accurate data sharing, merging, and transformation into reusable information. However, as CIM provides a basic framework for information exchange, various practical issues arise in establishing an energy management system capable of exchanging information using CIM. This paper aims to offer a comprehensive understanding by summarizing and categorizing the research on the practical use of CIM for interoperability in smart grids. Many papers are analyzed and the issues are classified into CIM extension, harmonization, and validation to address the issues that arise when establishing an integrated information exchange system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1995

An object-oriented, technology-adaptive information model

The primary objective was to develop a computer information system for effectively presenting NASA's technologies to American industries, for appropriate commercialization. To this end a comprehensive information management model, applicable to a wide variety of situations, and immune to computer software/hardware technological gyrations, was developed. The model consists of four main elements: a DATA_STORE, a data PRODUCER/UPDATER_CLIENT and a data PRESENTATION_CLIENT, anchored to a central object-oriented SERVER engine. This server engine facilitates exchanges among the other model elements and safeguards the integrity of the DATA_STORE element. It is designed to support new technologies, as they become available, such as Object Linking and Embedding (OLE), on-demand audio-video data streaming with compression (such as is required for video conferencing), Worldwide Web (WWW) and other information services and browsing, fax-back data requests, presentation of information on CD-ROM, and regular in-house database management, regardless of the data model in place. The four components of this information model interact through a system of intelligent message agents which are customized to specific information exchange needs. This model is at the leading edge of modern information management models. It is independent of technological changes and can be implemented in a variety of ways to meet the specific needs of any communications situation. This summer a partial implementation of the model has been achieved. The structure of the DATA_STORE has been fully specified and successfully tested using Microsoft's FoxPro 2.6 database management system. Data PRODUCER/UPDATER and PRESENTATION architectures have been developed and also successfully implemented in FoxPro; and work has started on a full implementation of the SERVER engine. The model has also been successfully applied to a CD-ROM presentation of NASA's technologies in support of Langley Research Center's TAG efforts.

Anyiwo, Joshua C.↗
NASA NTRS2009

AP233: An Information Model for Systems Engineering

In today's world, information is abundant. We have no problems generating it. But we are challenged to find, organize, and exchange information. center dot A standardized model of information can help. Such a model nearly completed its development for Systems Engineering. It is referred to as AP233 (AP = Application Protocol).

Siebes, Georg↗
NASA NTRS2007

International Planetary Data Alliance (IPDA) Information Model

This document is the third deliverable of the International Planetary Data Alliance (IPDA) Archive Data Standards Requirements Identification project. The goal of the project is to identify a subset of the standards currently in use by NASAs Planetary Data System (PDS) that are appropriate for internationalization. As shown in the highlighted sections of Figure 1, the focus of this project is the Information Model component of the Data Architecture Standards, namely the object models, a data dictionary, and a set of data formats.

information model↗
DOE OSTI2026

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

An information model for use in software management estimation and prediction

This paper describes the use of cluster analysis for determining the information model within collected software engineering development data at the NASA/GSFC Software Engineering Laboratory. We describe the Software Management Environment tool that allows managers to predict development attributes during early phases of a software project and the modifications we propose to allow it to develop dynamic models for better predictions of these attributes.

Li, Ningda R.↗
DOE OSTI2024

Modeling information flow in a computer processor with a multi-stage queuing model

In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into stages, and information can flow from one stage to another. The model is formulated as a spatially-extended, continuous-time Markov chain where space represents different stages. This model is equivalent to a spatially-extended version of the M/M/s queue. The main modeling feature is the throttling function which describes the processor slowdown when the amount of information falls below a certain threshold. We derive the stationary distribution for this stochastic model and develop a closure for a deterministic ODE system that approximates the evolution of the mean and variance of the stochastic model. In conclusion, we demonstrate the validity of the closure with numerical simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Automated Progress Monitoring in Modular Construction Factories Using Computer Vision and Building Information Modeling

Modular construction methods have recently gained interest due to the advantages offered in terms of safety, quality, and productivity for projects. In this method, a significant portion of the construction is performed off-site in factories where modular components are built in different workstations, assembled on the production line, and shipped to the site for installation. Due to the labor-intensive nature of tasks, cycle times in modular construction factories are highly variable, which commonly leads to major bottlenecks and delays in construction projects. To remedy this effect, recent methods rely on sensors such as RFID to monitor the production process, which is reportedly expensive, and intrusive to the work process. Recently, computer vision-based methods have been proposed to track the production process in modular construction factories. However, these methods overlook monitoring the assembly process on the production line. Therefore, this paper presents a method to monitor the assembly process by integrating computer vision-based methods with Building Information Modeling (BIM). The proposed method detects the modular units using object segmentation; superimposes the installation area with the corresponding 2D region using BIM, and identifies the installation of the components using image processing techniques. The proposed method has been validated using surveillance videos captured from a modular construction factory in the US. Successful implementation of the proposed method can lead to timely identification of delays during the assembly process and reduce delays in modular integrated construction projects.

building information modeling↗
DOE OSTI2025

Enhancing occupant behavior representation for interoperability between building information modeling and building energy modeling

Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities, and implementation of a standardized model documentation framework. To facilitate seamless data transformation between gbXML and obXML schemas, we developed a publicly available gb-obXML Schema Converter. Three case studies demonstrate the enhanced schema’s capabilities: representation of building information using a two-story office building model, documentation of a window operation behavior model, and validation of the schema converter’s functionality. The enhanced obXML schema v1.4 enables sophisticated modeling of occupant-building interactions while maintaining consistency with industry-standard BIM schemas. The standardized documentation framework facilitates reproducibility and knowledge sharing in the OB research community, while the schema converter automates the integration of building information into OB simulation workflows. These enhancements establish a foundation for more accurate building performance simulation by supporting sophisticated representation of occupant behavior within the BIM-to-BEM simulation workflows.

Chung, Jihoon↗