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Computer programs to calculate the incompressible potential flow corrected for compressibility in axisymmetric inlets at arbitrary operating conditions are presented. Included are a statement of the problem to be solved, a description of each of the programs and sufficient documentation, including a test case, to enable a user to run the programs.
Incompressible potential flow calculations are presented that were corrected for compressibility in two-dimensional inlets at arbitrary operating conditions. Included are a statement of the problem to be solved, a description of each of the computer programs, and sufficient documentation, including a test case, to enable a user to run the program.
Computer programs to calculate the incompressible potential flow, corrected for compressibility, in two-dimensional nozzles at arbitrary operating conditions are presented. A statement of the problem to be solved, a description of each of the computer programs, and sufficient documentation, including a test case, to enable a user to run the program are included.
While verifying adherence to a specification (i.e., specification-based testing) is important, the results are only as valid as the specification itself. Problematically, verifying a system specification must be done within the context of changing or even unknown environmental domain knowledge that could render the specification ineffective or incorrect. This issue is even more apparent in the context of self-adaptive systems, where uncertainty in both the system configuration and environment can impact the validity of the system. This paper introduces a method to explicitly model domain knowledge of the environment as a secondary system to enable design-time verification against documented environmental assumptions (i.e., those elements external to the system). In addition, run-time monitors are used to detect scenarios in the actual environment not specified by the modeled environmental domain knowledge. Rather than simply identifying unexpected inputs, our approach is able to identify run-time violations of the environmental domain knowledge, even when inputs appear valid based on the domain assumptions embedded in the system specification. These violations can then be used to correspondingly update the system and environmental specifications via automated run-time adaptation or subsequent design-time revisions. We illustrate our approach by applying our method to a running example of a goal-based model of a baby monitor.
The contents of this document define the integrated performance and interface design for NASA Docking System (NDS) Block 1 and the International Docking Adapter. The intent of this IDD is to provide the interface design for using, installing, and interfacing to the NDS Block 1 that will enable successful docking to the IDA. This document is under the control of the ISS Development Projects Office (OG).
The purpose of this report is to provide an initial reference document to support further definition of science community needs for small-RPS flight systems. It describes the most recent results of the ongoing NASA/DOE studies, and provides information for review by potential users that might take advantage of these types of power systems. This is extremely important since any future decision to proceed with the development of such units will require a strong identified need from the space science community and a well-defined set of power and operational requirements. NASA and DOE intend to use this document as a basis for soliciting information on additional small-RPS-enabled mission concepts, along with their respective power and operational requirements. This report is a first step in fleshing out a roadmap for potential future development and acquisition.
This report documents technologies that have been commercialized by the private sector and other partners—such as technology developers in startups, companies, and universities—in part because of R&D funding from EERE. It also documents emerging technologies that have the potential to reach the market within the next three years with the support of EERE R&D investments. Commercial and emerging technology tracking in this manner assists EERE technology managers, analysts, communications staff, and senior management in describing and explaining the benefits of EERE-funded research. Policy- and decision-makers would then have the latest information to guide future program development and direction.
The Geospatial and Information Substitution and Anonymization Tool (GISA) incorporates techniques for obfuscating identifiable information from point data or documents, while simultaneously maintaining chosen variables to enable future use and meaningful analysis. This approach promotes collaboration and data sharing while also reducing the risk of exposure to sensitive information. GISA can be used in a number of different ways, including the anonymization of point spatial data, batch replacement/removal of user-specified terms from file names and from within file content, and aid with the selection and redaction of images and terms based on recommendations using natural language processing. Version 1 of the tool, published here, has updated functionality and enhanced capabilities to the beta version published in 2023. Please see User Documentation for further information on capabilities, as well as a guide for how to download and use the tool. If there are any feedback you would like to provide for the tool, please reach out with your feedback to edxsupport@netl.doe.gov. Disclaimer: This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. The Geospatial and Information Substitution and Anonymization Tool (GISA) was developed jointly through the U.S. DOE Office of Fossil Energy and Carbon Management’s EDX4CCS Project, in part, from the Bipartisan Infrastructure Law.
Kinetic metabolic models provide invaluable insights into cellular metabolism, supporting applications in synthetic biology, metabolic engineering, and systems biology. However, reproducibility and utility of these models hinge on clear and rigorous documentation, standardized annotation, and accessible visualization. This paper presents a workflow for building, annotating, visualizing, and sharing kinetic metabolic models. Our method integrates community standards and open-source tools to ensure reproducibility, interoperability, and user accessibility. This procedure enables researchers to produce reusable and well-documented kinetic models, advancing their role as powerful tools in metabolic research.
Systems analysis develops and documents candidate mission and architectures, associated system concepts, enabling capabilities and investment strategies to achieve NASA s strategic objectives. The technology assessment process connects the mission and architectures to the investment strategies. In order to successfully implement a technology assessment, there is a need to collect, manipulate, analyze, document, and disseminate technology-related information. Information must be collected and organized on the wide variety of potentially applicable technologies, including: previous research results, key technical parameters and characteristics, technology readiness levels, relationships to other technologies, costs, and potential barriers and risks. This information must be manipulated to facilitate planning and documentation. An assessment is included of the programmatic and technical risks associated with each technology task as well as potential risk mitigation plans. Risks are assessed and tracked in terms of likelihood of the risk occurring and consequences of the risk if it does occur. The risk assessments take into account cost, schedule, and technical risk dimensions. Assessment data must be simplified for presentation to decision makers. The Systems Analysis and Concepts Directorate (SACD) at NASA Langley Research Center has a wealth of experience in performing Technology Assessment and Portfolio Analysis as this has been a business line since 1978.
Machine Aided Indexing (MAI) is a Web-based application program for aiding the indexing of literature in the NASA Scientific and Technical Information (STI) Database. MAI was designed to be a convenient, fully interactive tool for determining the subject matter of documents and identifying keywords. The heart of MAI is a natural-language processor that accepts, as input, any user-supplied text, including abstracts, full documents, and Web pages. Within seconds, the text is analyzed and a ranked list of terms is generated. The 17,800 terms of the NASA Thesaurus serve as the foundation of the knowledge base used by MAI. The NASA Thesaurus defines a standard vocabulary, the use of which enables MAI to assist in ensuring that STI documents are uniformly and consistently accessible. Of particular interest to traditional users of the NASA Thesaurus, MAI incorporates a fully searchable thesaurus display module that affords word-search and hierarchy- navigation capabilities that make it much easier and less time-consuming to look up terms and browse, relative to lookup and browsing in older print and Portable Document Format (PDF) digital versions of the Thesaurus. In addition, because MAI is centrally hosted, the Thesaurus data are always current.
ScienceOrganizer is a specialized knowledge management tool designed to enhance the information storage, organization, and access capabilities of distributed NASA science teams. Users access ScienceOrganizer through an intuitive Web-based interface that enables them to upload, download, and organize project information - including data, documents, images, and scientific records associated with laboratory and field experiments. Information in ScienceOrganizer is "threaded", or interlinked, to enable users to locate, track, and organize interrelated pieces of scientific data. Linkages capture important semantic relationships among information resources in the repository, and these assist users in navigating through the information related to their projects.
Special Programs are additional survey areas and/or observing strategies that are driven by specific science goals which build on, or are beyond, the core science pillars of the Wide Fast Deep Main Survey. In order to meet the requirements and enable science related to Special Programs, this document provides recommendations for Rubin Data Management regarding processing and serving data products for Special Programs. Hardware and processing boundaries on the potential diversity of data from Special Programs are discussed along with scenarios in which user-generated processing and data products might be needed to meet Special Programs' science goals.
BEACON-Archives, the JPL Archives electronic catalog, is now online. It enables researchers to find a collection or document description using title, author, documnet number, subject terms, or any words and phrases appearing in the catalog entry.
NASA is committed to building an inclusive open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI is made up of a number of activities including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to the wealth of NASA’s open science data and information. In this presentation, we will present our collaborative work to date to build the SDE and our vision for empowering open source science in the future.
Transformative science often occurs at the boundaries of different disciplines. Making interdisciplinary science data, software and documentation discoverable and accessible is essential to enabling transformative science. However, connecting this diverse and heterogeneous information is often a challenge due to several factors including the dispersed and sometimes isolated nature of data and the semantic differences between topical areas. NASA’s Science Discovery Engine (SDE) has developed several approaches to tackling these challenges. The SDE is a unified, insightful search experience that enables discovery of NASA’s open science data across five topical areas: astrophysics, biological and physical sciences, Earth science, heliophysics and planetary science. In this presentation, we will discuss our efforts to develop a systematic scientific curation workflow to integrate diverse content into a single search environment. We will also share lessons learned from our work to create a metadata crosswalk across the five disciplines.
The Mars Cost Tracking Model is a computer program that administers a system set up for tracking the costs of future NASA projects that pertain to Mars. Previously, no such tracking system existed, and documentation was written in a variety of formats and scattered in various places. It was difficult to justify costs or even track the history of costs of a spacecraft mission to Mars. The present software enables users to maintain all cost-model definitions, documentation, and justifications of cost estimates in one computer system that is accessible via the Internet. The software provides sign-off safeguards to ensure the reliability of information entered into the system. This system may eventually be used to track the costs of projects other than only those that pertain to Mars.
The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment that will generate an unprecedented volume of heterogeneous information-from documentation and technical notes to experimental data and reconstruction pipelines. Efficient knowledge retrieval and contextual understanding are increasingly critical for collaboration-wide productivity and onboarding. In this work, we present DUNE-GPT, a prototype framework that leverages large language models (LLMs) and retrieval-augmented generation (RAG) to enable natural-language querying of DUNE's internal documentation and technical resources. The system provides an intelligent interface for DUNE collaborators to interact with experiment-specific knowledge while maintaining data privacy and infrastructure compliance within Fermilab computing resources.