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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 127 records · Page 7

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NASA NTRS2021

An Ontology-Based Virtual Orrery

Tutorials in this technical memorandum explain how to use the Protégé ontology editor to import data from Excel and export data from Protégé in the JavaScript Object Notation Linked Data (JSON-LD) format then how to transform the JSON-LD file into variables for web apps. These tutorials apply JavaScript and R programming languages and 3D graphics libraries. Ontologies enable standardization, data sharing, and semantic interoperability. An ontology models a domain of knowledge as taxonomies of annotated classes, data properties, relational object properties, and inference rules. This technical memorandum includes a data dictionary for a subset of the Space Situational Awareness Ontology (SSAO).

Ontologies↗

DOE OSTI2025

The Artificial Intelligence Ontology: LLM-Assisted Construction of AI Concept Hierarchies

The Artificial Intelligence Ontology (AIO) is a systematization of artificial intelligence (AI) concepts, methodologies, and their interrelations. Developed via manual curation, with the additional assistance of large language models (LLMs), AIO aims to address the rapidly evolving landscape of AI by providing a comprehensive framework that encompasses both technical and ethical aspects of AI technologies. The primary audience for AIO includes AI researchers, developers, and educators seeking standardized terminology and concepts within the AI domain. We use the term “branches” for classes, and their subclasses, in our ontology that are subclasses of owl:Thing. AIO contains eight branches: Bias, Layer, Machine Learning Task, Mathematical Function, Model, Network, Preprocessing, and Training Strategy, each designed to support the modular composition of AI methods and facilitate a deeper understanding of deep learning architectures and ethical considerations in AI. AIO uses the Ontology Development Kit (ODK) for its creation and maintenance, with its content being more easily updated through AI-driven curation support. This approach not only ensures the ontology's relevance amidst the fast-paced advancements in AI but also significantly enhances its utility for researchers, developers, and educators by simplifying the integration of new AI concepts and methodologies. The ontology's utility is demonstrated through the annotation of AI methods data in a catalog of AI research publications and the integration into the BioPortal ontology resource, highlighting its potential for cross-disciplinary research. The AIO ontology is open source and is available on GitHub ( https://w3id.org/aio/ ) and BioPortal ( https://bioportal.bioontology.org/ontologies/AIO ).

Joachimiak, Marcin P. [Biosystems Data Science Dep↗

NASA NTRS1976

Creative revision - From rough draft to published paper

The process of revising a technical or scientific paper can be performed more efficiently by the people involved (author, co-author, supervisor, editor) when the revision is controlled by breaking it into a series of steps. The revision process recommended here is based on the levels-of-edit concept that resulted from a study of the technical editorial function at the Jet Propulsion Laboratory of the California Institute of Technology. Types of revision discussed are Substantive, Policy, Language, Mechanical Style, Format, Integrity, and Copy Clarification.

Buehler, M. F.↗

NASA NTRS2025

Detangling Safety Knowledge with Contextualism

We have contradictory intuitions about knowing that things are safe: on the one hand, we claim to have knowledge that many systems (even complex ones) are safe in ordinary language. On the other hand, when challenged by an expert, we easily admit that we do not, in fact, possess very much safety knowledge at all. This Technical Memorandum (TM) attempts to reconcile these two competing intuitions using a philosophical view called epistemic contextualism. We can use epistemic contextualism to explain the importance of safety regulations and the goal in implementing them: first, to differentiate types of disagreement and establish a common basis upon which regulators and regulatees can know that a system is safe; second, to raise ordinary consumers’ standards for safety knowledge (given adequate knowledge of the comprehensiveness of the regulation). This TM also uses the contextualist framework of relevant alternatives to elucidate types of failure possibilities and explain complications in attempts to prevent common mode failures.

language↗

NASA NTRS2007

Panel Resource Management (PRM) Implementation and Effects within Safety Review Panel Settings and Dynamics

While technical training and advanced degree's assure proficiency at specific tasks within engineering disciplines, they fail to address the potential for communication breakdown and decision making errors familiar to multicultural environments where language barriers, intimidating personalities and interdisciplinary misconceptions exist. In an effort to minimize these pitfalls to effective panel review, NASA's lead safety engineers to the ISS Safety Review Panel (SRP), and Payload Safety Review Panel (PSRP) initiated training with their engineers, in conjunction with the panel chairs, and began a Panel Resource Management (PRM) program. The intent of this program focuses on the ability to reduce the barriers inhibiting effective participation from all panel attendees by bolstering participants confidence levels through increased communication skills, situational awareness, debriefing, and a better technical understanding of requirements and systems.

Taylor, Robert W.↗

DOE OSTI2024

Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation

The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. However, addressing complex urban and environmental management challenges often demands deep expertise in domain science and informatics. This expertise is essential for deriving data and simulation-driven insights that support informed decision-making. In this context, we investigate the potential of leveraging the pre-trained Large Language Models (LLMs) to create knowledge representations for supporting operations research. By adopting ChatGPT-4 API as the reasoning core, we outline an applied workflow that encompasses natural language processing, Methontology-based prompt tuning, and Generative Pre-trained Transformer (GPT), to automate the construction of scenario-based ontologies using existing research articles and technical manuals of urban datasets and simulations. From these ontologies, knowledge graphs can be derived using widely adopted formats and protocols, guiding various tasks towards data-informed decision support. The performance of our methodology is evaluated through a comparative analysis that contrasts our AI-generated ontology with the widely recognized pizza ontology, commonly used in tutorials for popular ontology software. We conclude with a real-world case study on optimizing the complex system of multi-modal freight transportation. Our approach advances urban decision support systems by enhancing data and metadata modeling, improving data integration and simulation coupling, and guiding the development of decision support strategies and essential software components.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS2007

Program Management Tool

The Program Management Tool (PMT) is a comprehensive, Web-enabled business intelligence software tool for assisting program and project managers within NASA enterprises in gathering, comprehending, and disseminating information on the progress of their programs and projects. The PMT provides planning and management support for implementing NASA programmatic and project management processes and requirements. It provides an online environment for program and line management to develop, communicate, and manage their programs, projects, and tasks in a comprehensive tool suite. The information managed by use of the PMT can include monthly reports as well as data on goals, deliverables, milestones, business processes, personnel, task plans, monthly reports, and budgetary allocations. The PMT provides an intuitive and enhanced Web interface to automate the tedious process of gathering and sharing monthly progress reports, task plans, financial data, and other information on project resources based on technical, schedule, budget, and management criteria and merits. The PMT is consistent with the latest Web standards and software practices, including the use of Extensible Markup Language (XML) for exchanging data and the WebDAV (Web Distributed Authoring and Versioning) protocol for collaborative management of documents. The PMT provides graphical displays of resource allocations in the form of bar and pie charts using Microsoft Excel Visual Basic for Application (VBA) libraries. The PMT has an extensible architecture that enables integration of PMT with other strategic-information software systems, including, for example, the Erasmus reporting system, now part of the NASA Integrated Enterprise Management Program (IEMP) tool suite, at NASA Marshall Space Flight Center (MSFC). The PMT data architecture provides automated and extensive software interfaces and reports to various strategic information systems to eliminate duplicative human entries and minimize data integrity issues among various NASA systems that impact schedules and planning.

Gawadiak, Yuri↗

NASA NTRS2011

Flight Simulation Model Exchange

The NASA Engineering and Safety Center Review Board sponsored an assessment of the draft Standard, Flight Dynamics Model Exchange Standard, BSR/ANSI-S-119-201x (S-119) that was conducted by simulation and guidance, navigation, and control engineers from several NASA Centers. The assessment team reviewed the conventions and formats spelled out in the draft Standard and the actual implementation of two example aerodynamic models (a subsonic F-16 and the HL-20 lifting body) encoded in the Extensible Markup Language grammar. During the implementation, the team kept records of lessons learned and provided feedback to the American Institute of Aeronautics and Astronautics Modeling and Simulation Technical Committee representative. This document contains the results of the assessment.

Murri, Daniel G.↗

NASA NTRS2011

Flight Simulation Model Exchange: Appendices - Volume 2

Murri, Daniel G.↗

NASA NTRS1980

The levels of edit, second edition

The editorial process is analyzed, and five levels of edit are identified. These levels represent cumulative combinations of nine types of edit: Coordination, Policy, Integrity, Screening, Copy Clarification, Format, Mechanical Style, Language, and Substantive. The levels and types of edit, although developed for specific use with external reports at the Jet Propulsion Laboratory, cover the general range of technical editing, especially as it applies to an in-house technical publications organization. Each type of edit is set forth in terms of groups of actions to be performed by editor. The edit-level concept has enhanced understanding and communication among editors, authors, and publications managers concerning the specific editorial work to be done on each manuscript. It has also proved useful as a management tool for estimating and monitoring cost.

Vanburen, R.↗

NASA NTRS2002

Language translation, doman specific languages and ANTLR

We will discuss the features of ANTLR that make it an attractive tool for rapid developement of domain specific language translators and present some practical examples of its use: extraction of information from the Cassini Command Language specification, the processing of structured binary data, and IVL--an English-like language for generating VRML scene graph, which is used in configuring the jGuru.com server.

technical keywords↗

NASA NTRS2007

Plants Clean Air and Water for Indoor Environments

Wolverton Environmental Services Inc., founded by longtime government environmental scientist B.C. "Bill" Wolverton, is an environmental consulting firm that gives customers access to the results of his decades of cutting-edge bioremediation research. Findings about how to use plants to improve indoor air quality have been published in dozens of NASA technical papers and in the book, "How to Grow Fresh Air: 50 Houseplants That Purify Your Home or Office." The book has now been translated into 12 languages and has been on the shelves of bookstores for nearly 10 years. A companion book, "Growing Clean Water: Nature's Solution to Water Pollution," explains how plants can clean waste water. Other discoveries include that the more air that is allowed to circulate through the roots of the plants, the more effective they are at cleaning polluted air; and that plants play a psychological role in welfare in that people recover from illness faster in the presence of plants. Wolverton Environmental is also working in partnership with Syracuse University, to engineer systems consisting of modular wicking filters tied into duct work and water supplies, essentially tying plant-based filters into heating, ventilation, and air conditioning (HVAC) systems. Also, the company has recently begun to assess the ability of the EcoPlanter to remove formaldehyde from interior environments. Wolverton Environmental is also in talks with designers of the new Stennis Visitor's Center, who are interested in using its designs for indoor air-quality filters

Source record↗

NASA NTRS1976

The levels of edit

The editorial process is analyzed, and five levels of edit are identified. These levels represent cumulative combinations of nine types of edit: (1) coordination, (2) policy, (3) integrity, (4) screening, (5) copy clarification, (6) Mechanical Style, (7) Language, and (9) substantive. The levels and types of edit, although developed for specific use with external reports at the Jet Propulsion Laboratory, cover the general range of technical editing, especially as it applies to an in-house technical publications organization. Each type of edit is set forth in terms of groups of actions to be performed by the editor. The edit-level concept has enhanced understanding and communication among editors, authors, and publications managers concerning the specific editorial work to be done on each manuscript. It has also proved useful as a management tool for estimating and monitoring cost.

Vanburen, R.↗

NASA NTRS1986

GSFC Ada programming guidelines

A significant Ada effort has been under way at Goddard for the last two years. To ease the center's transition toward Ada (notably for future space station projects), a cooperative effort of half a dozen companies and NASA personnel was started in 1985 to produce programming standards and guidelines for the Ada language. The great richness of the Ada language and the need of programmers for good style examples makes Ada programming guidelines an important tool to smooth the Ada transition. Because of the natural divergence of technical opinions, the great diversity of our government and private organizations and the novelty of the Ada technology, the creation of an Ada programming guidelines document is a difficult and time consuming task. It is also a vital one. Steps must now be taken to ensure that the guide is refined in an organized but timely manner to reflect the growing level of expertise of the Ada community.

Roy, Daniel M.↗

NASA NTRS1994

How to use the WWW to distribute STI

This presentation explains how to use the World Wide Web (WWW) to distribute scientific and technical information as hypermedia. WWW clients and servers use the HyperText Transfer Protocol (HTTP) to transfer documents containing links to other text, graphics, video, and sound. The standard language for these documents is the HyperText MarkUp Language (HTML). These are simply text files with formatting codes that contain layout information and hyperlinks. HTML documents can be created with any text editor or with one of the publicly available HTML editors or convertors. HTML can also include links to available image formats. This presentation is available online. The URL is http://sti.larc.nasa. (followed by) gov/demos/workshop/introtext.html.

Roper, Donna G.↗

DOE OSTI2026

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

DOE OSTI2026

AI-Ready Control System for the Fermilab Accelerator Complex

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation illustrate the technical requirements across the complex.

43 PARTICLE ACCELERATORS↗

NASA NTRS2005

Decision Facilitator for Launch Operations using Intelligent Agents

Launch operations require millions of micro-decisions which contribute to the macro decision of 'Go/No-Go' for a launch. Knowledge workers"(such as managers and technical professionals) need information in a timely precise manner as it can greatly affect mission success. The intelligent agent (web search agent) uses the words of a hypertext markup language document which is connected through the internet. The intelligent agent's actions are to determine if its goal of seeking a website containing a specified target (e.g., keyword or phrase), has been met. There are few parameters that should be defined for the keyword search like "Go" and "No-Go". Instead of visiting launch and range decision making servers individually, the decision facilitator constantly connects to all servers, accumulating decisions so the final decision can be decided in a timely manner. The facilitator agent uses the singleton design pattern, which ensures that only a single instance of the facilitator agent exists at one time. Negotiations could proceed between many agents resulting in a final decision. This paper describes details of intelligent agents and their interaction to derive an unified decision support system.

Thirumalainambi, Rajkumar↗