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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Ada and the rapid development lifecycle

JPL is under contract, through NASA, with the US Army to develop a state-of-the-art Command Center System for the US European Command (USEUCOM). The Command Center System will receive, process, and integrate force status information from various sources and provide this integrated information to staff officers and decision makers in a format designed to enhance user comprehension and utility. The system is based on distributed workstation class microcomputers, VAX- and SUN-based data servers, and interfaces to existing military mainframe systems and communication networks. JPL is developing the Command Center System utilizing an incremental delivery methodology called the Rapid Development Methodology with adherence to government and industry standards including the UNIX operating system, X Windows, OSF/Motif, and the Ada programming language. Through a combination of software engineering techniques specific to the Ada programming language and the Rapid Development Approach, JPL was able to deliver capability to the military user incrementally, with comparable quality and improved economies of projects developed under more traditional software intensive system implementation methodologies.

Deforrest, Lloyd↗
NASA NTRS1996

An optimal user-interface for EPIMS database conversions and SSQ 25002 EEE parts screening

The Electrical, Electronic, and Electromechanical (EEE) Parts Information Management System (EPIMS) database was selected by the International Space Station Parts Control Board for providing parts information to NASA managers and contractors. Parts data is transferred to the EPIMS database by converting parts list data to the EP1MS Data Exchange File Format. In general, parts list information received from contractors and suppliers does not convert directly into the EPIMS Data Exchange File Format. Often parts lists use different variable and record field assignments. Many of the EPES variables are not defined in the parts lists received. The objective of this work was to develop an automated system for translating parts lists into the EPIMS Data Exchange File Format for upload into the EPIMS database. Once EEE parts information has been transferred to the EPIMS database it is necessary to screen parts data in accordance with the provisions of the SSQ 25002 Supplemental List of Qualified Electrical, Electronic, and Electromechanical Parts, Manufacturers, and Laboratories (QEPM&L). The SSQ 2S002 standards are used to identify parts which satisfy the requirements for spacecraft applications. An additional objective for this work was to develop an automated system which would screen EEE parts information against the SSQ 2S002 to inform managers of the qualification status of parts used in spacecraft applications. The EPIMS Database Conversion and SSQ 25002 User Interfaces are designed to interface through the World-Wide-Web(WWW)/Internet to provide accessibility by NASA managers and contractors.

Watson, John C.↗
DOE OSTI2022

Design Philosophy for Accelerator Control Rooms

This report describes the foundational human factors principles needed to design user interfaces for accelerator control rooms. These principles are presented as recommendations for accelerator control system interface design and are illustrated with examples drawn from accelerator operations at Fermi National Accelerator Laboratory (Fermilab). These high-level principles are intended to serve as design objectives that apply generally across all control system interfaces developed for the accelerator complex. This design philosophy document is a high-level roadmap to approach the general interface design for the accelerator complex. This philosophy applies state-of-the-art human factors principles and evidence-based design standards to an accelerator environment, which will transform the next era of accelerator interfaces as outlined by the Accelerator Controls Operations Research Network (ACORN) Project. Further work will include mapping the general design principles included in this report to more specific guidance in the form of a user interface style guide.

43 PARTICLE ACCELERATORS↗
NASA NTRS2002

The spacecraft onboard interface standardization activity

The Consultative Committee for Space Data Systems (CCSDS) is an international organization of national space agencies (such as NASA in the United States) that is organized to promote the interchange of space related information. Now, CCSDS is branching out to provide new standards for the interchange of information, and the interconnection of subsystems and devices onboard of a spacecraft. This effort is know as Spacecraft Onboard Interface (SOIF). SOIF will publish standards that will allow for the enhanced reuse of spacecraft equipment and software. SOIF expects that these standards will be well known and used within the space community, and that they will be based on or similar to the well-known Internet protocols. This paper will provide a description of the SOIF work by reviewing this work with three orthogonal views. The first of these views is the Protocol view, which describes the protocols and services that are to be implemented in order to provide the users with the advantages of the SOIF architecture. The second of these views is the Services View, which describes the data communications services that are provided to the users. And finally, the Interoperability view provides a description to users how SOIF can be used to interchange between different spacecraft data busses. This paper will give the reader an excellent introduction to the work of the international SOIF team.

spacecraft interfaces standard interfaces CCSDS↗
NASA NTRS1991

Higher-order neural network software for distortion invariant object recognition

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Reid, Max B.↗
NASA NTRS1994

Common modeling system for digital simulation

The Joint Modeling and Simulation System is a tri-service investigation into a common modeling framework for the development digital models. The basis for the success of this framework is an X-window-based, open systems architecture, object-based/oriented methodology, standard interface approach to digital model construction, configuration, execution, and post processing. For years Department of Defense (DOD) agencies have produced various weapon systems/technologies and typically digital representations of the systems/technologies. These digital representations (models) have also been developed for other reasons such as studies and analysis, Cost Effectiveness Analysis (COEA) tradeoffs, etc. Unfortunately, there have been no Modeling and Simulation (M&S) standards, guidelines, or efforts towards commonality in DOD M&S. The typical scenario is an organization hires a contractor to build hardware and in doing so an digital model may be constructed. Until recently, this model was not even obtained by the organization. Even if it was procured, it was on a unique platform, in a unique language, with unique interfaces, and, with the result being UNIQUE maintenance required. Additionally, the constructors of the model expended more effort in writing the 'infrastructure' of the model/simulation (e.g. user interface, database/database management system, data journalizing/archiving, graphical presentations, environment characteristics, other components in the simulation, etc.) than in producing the model of the desired system. Other side effects include: duplication of efforts; varying assumptions; lack of credibility/validation; and decentralization in policy and execution. J-MASS provides the infrastructure, standards, toolset, and architecture to permit M&S developers and analysts to concentrate on the their area of interest.

Painter, Rick↗
NASA NTRS2014

Using Social Media and Mobile Devices to Discover and Share Disaster Data Products Derived From Satellites

Data products derived from Earth observing satellites are difficult to find and share without specialized software and often times a highly paid and specialized staff. For our research effort, we endeavored to prototype a distributed architecture that depends on a standardized communication protocol and applications program interface (API) that makes it easy for anyone to discover and access disaster related data. Providers can easily supply the public with their disaster related products by building an adapter for our API. Users can use the API to browse and find products that relate to the disaster at hand, without a centralized catalogue, for example floods, and then are able to share that data via social media. Furthermore, a longerterm goal for this architecture is to enable other users who see the shared disaster product to be able to generate the same product for other areas of interest via simple point and click actions on the API on their mobile device. Furthermore, the user will be able to edit the data with on the ground local observations and return the updated information to the original repository of this information if configured for this function. This architecture leverages SensorWeb functionality [1] presented at previous IGARSS conferences. The architecture is divided into two pieces, the frontend, which is the GeoSocial API, and the backend, which is a standardized disaster node that knows how to talk to other disaster nodes, and also can communicate with the GeoSocial API. The GeoSocial API, along with the disaster node basic functionality enables crowdsourcing and thus can leverage insitu observations by people external to a group to perform tasks such as improving water reference maps, which are maps of existing water before floods. This can lower the cost of generating precision water maps. Keywords-Data Discovery, Disaster Decision Support, Disaster Management, Interoperability, CEOS WGISS Disaster Architecture

0↗
NASA NTRS2003

Standard user data services for spacecraft applications

The Consultative Committee for Space Data Systems is an international organization of national space agencies that is branching out to provide new standards to enhanced reuse of spacecraft equiptment and software. These Spacecraft Onboard Interface (SOIF) standards will be based on the well-known Internet protocols. this paper will review the SOIF standards by looking at the services that are being proposed for SOIF.

space interfaces avionics interfaces standard inte↗
DOE OSTI2024

DOE BSSD Performance Management Metrics Report Q1

Microbes play key roles in our biosphere, from driving global nutrient cycling to impacting plant, animal and human health and disease. Complex data from microbial genomes, proteins, and metabolites provide a window into these tiny engines that drive life on our planet. Yet these data are dispersed among researchers’ laboratories and various repositories, making it difficult to access. This calls for new ways of managing data, improving data interoperability, advancing community standards, and creating an infrastructure where data are shared efficiently. We have built the National Microbiome Data Collaborative (NMDC) to advance how scientists create, use, and reuse data to redefine the way we understand and harness the power of microbes. The vision of the National Microbiome Data Collaborative (NMDC) is to drive a microbiome data sharing network connecting data, people, and ideas to advance microbiome innovation and discovery. The NMDC was launched in 2019 and brought together DOE National Laboratories to collaborate across resources, capabilities, and expertise. The NMDC team was strategically assembled to include software developers, microbial researchers, metadata experts, and multi-omics specialists. The diversity of the NMDC team reflects the inherently interdisciplinary nature of microbiome science, and we leverage the strengths of the DOE National Laboratory system. Towards BER’s goal of advancing an iterative systems biology approach to the understanding of microbial genomes, the NMDC serves as a foundation for infrastructure, data standards, and community building. Together with the flagship DOE User Facilities, the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), we are developing core capabilities in metadata standards for environmental descriptors and sample handling and processing; standardized bioinformatic workflows; an interface for data search and access; and robust community engagement activities. The NMDC production platform supports long-term data infrastructure and community building for BER’s bioenergy and environmental research goals. Our approach leverages lessons learned and an ambitious framework for collaborative, interdisciplinary data infrastructure to support microbiome research. The NMDC supports data, information, and knowledge access through three defined software tools – the Submission Portal, NMDC EDGE, and the Data Portal – driven by community needs. Herein, we describe the value proposition for the microbiome research community, our overarching strategy, and challenges and opportunities for developing the NMDC as both an infrastructure and community engagement program.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

Harmony: Bringing Data Together by Bringing Services Together

As Earth observation data volume, velocity, and variety continues to accelerate, so do the challenges of working with those data. The computation, storage, and network transfer requirements for multi-petabyte datasets demand solutions that allow users to process, store, and move fewer bytes while still finding the valuable insights they seek. Our cloud-based data transformation framework, Harmony, tackles these challenges by providing consistent, standards-based interface to multiple disparate backend processors collocated with NASA EOSDIS data. It allows data scientists to perform data processing and harmonization activities across many datasets through familiar tooling. Simultaneously, it provides a clear, consistent interface for data providers to expose new or customized backend services for their data. This talk will discuss Harmony, its architecture and interface, and the path forward for cloud-based NASA EOSDIS data harmonization services.

Quinn, Patrick↗
DOE OSTI2021

Building Performance Database API (BPD API) v2.1

The Building Performance Database (BPD) is the largest publicly-available source of measured energy performance data for buildings in the United States. It contains information about the building's energy use, location, and physical and operational characteristics. The BPD can be used by building owners, operators, architects and engineers to compare a building's energy efficiency against customized peer groups, identify energy efficiency opportunities, and set energy efficiency targets. It can also be used by energy efficiency program implementers and policymakers to analyze energy efficiency features and trends in the building stock. The BPD compiles data from various data sources, converts it into a standard format, cleanses and quality checks the data, and provides users with access to the data in a way that maintains anonymity for data providers. This software is the database and the Application Programming Interface (API). Users can utilize the BPD's data to develop their own applications using the API. Version 2.1 included a major update for multiple years of data and refactoring of code for faster queries.

Mathew, Paul↗
NASA NTRS2010

The Evolvable Advanced Multi-Mission Operations System (AMMOS): Making Systems Interoperable

The Advanced Multi-Mission Operations System (AMMOS) provides a common Mission Operation System (MOS) infrastructure to NASA deep space missions. The evolution of AMMOS has been driven by two factors: increasingly challenging requirements from space missions, and the emergence of new IT technology. The work described in this paper focuses on three key tasks related to IT technology requirements: first, to eliminate duplicate functionality; second, to promote the use of loosely coupled application programming interfaces, text based file interfaces, web-based frameworks and integrated Graphical User Interfaces (GUI) to connect users, data, and core functionality; and third, to build, develop, and deploy AMMOS services that are reusable, agile, adaptive to project MOS configurations, and responsive to industrially endorsed information technology standards.

MGSS↗
NASA NTRS2006

Tool for Statistical Analysis and Display of Landing Sites

MarsLS is a software tool for analyzing statistical dispersion of spacecraft-landing sites and displaying the results of its analyses. Originally intended for the Mars Explorer Rover (MER) mission, MarsLS is also applicable to landing sites on Earth and non-MER sites on Mars. MarsLS is a collection of interdependent MATLAB scripts that utilize the MATLAB graphical-user-interface software environment to display landing-site data (see figure) on calibrated image-maps of the Martian or other terrain. The landing-site data comprise latitude/longitude pairs generated by Monte Carlo runs of other computer programs that simulate entry, descent, and landing. Using these data, MarsLS can compute a landing-site ellipse a standard means of depicting the area within which the spacecraft can be expected to land with a given probability. MarsLS incorporates several features for the user s convenience, including capabilities for drawing lines and ellipses, overlaying kilometer or latitude/longitude grids, drawing and/or specifying lines and/or points, entering notes, defining and/or displaying polygons to indicate hazards or areas of interest, and evaluating hazardous and/or scientifically interesting areas. As part of such an evaluation, MarsLS can compute the probability of landing in a specified polygonal area.

Wawrzyniak, Geoffrey↗
DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗
NASA NTRS1978

The Seasat algorithm development facility at JPL

The Seasat-A spacecraft, scheduled for launch in May 1978, will produce a global ocean data set covering a one-year nominal mission. Because this is a proof-of-concept mission, data processing algorithms are expected to evolve as the data base grows. To support the evolution and evaluation of algorithms, and to experiment with various techniques for processing the data, an algorithm development facility (ADF) is being developing. The ADF will provide access to the data base and to highly modularized processing programs. The processing programs will be subject to easy and frequent modification by a remote user community of sensor managers and experiment teams, who will use this capability to evaluate the overall performance of the sensors and the algorithms using surface truth data. The ADF concepts of software standardization and interface control are expected to have general applicability for adaptive data processing systems.

Brown, J. W.↗
NASA NTRS1987

NESSUS/expert and NESSUS/FPI in the Probabilistic Structural Analysis Methods (PSAM) program

The Numerical Evaluation of Stochastic Structures under Stress (NESSUS) is the primary computer code being developed in the NASA Probabilistic Structural Analysis Methods (PSAM) project. It consists of four modules NESSUS/EXPERT, NESSUS/FPI, NESSUS/PRE and NESSUS/FEM. This presentation concentrates on EXPERT and FPI. To provide an effective interface between NESSUS and the user, an expert system module called NESSUS/EXPERT is being developed. That system uses the CLIPS artificial intelligence code developed to NASA-JSC. The code is compatible with FORTRAN, the standard language for codes in PSAM. The user interacts with the CLIPS inference engine, which is linked to the knowledge database. The perturbation database generated by NESSUS/FEM and managed in EXPERT is used to develop the so-called response or performance model in the random variables. Two independent probabilistic methods are available in PSAM for the computation of the probabilistic structural response. These are the Fast Probability Integration (FPI) method and Monte Carlo simulation. FPI is classified as an advanced reliability method and has been developed over the past ten years by researchers addressing the reliability of civil engineering structures. Monte Carlo is a well-established technique for computing probabilities by conducting a number of deterministic analyses with specified input distributional information.

Burnside, O. H.↗
NASA NTRS1995

Generalized Support Software: Domain Analysis and Implementation

For the past five years, the Flight Dynamics Division (FDD) at NASA's Goddard Space Flight Center has been carrying out a detailed domain analysis effort and is now beginning to implement Generalized Support Software (GSS) based on this analysis. GSS is part of the larger Flight Dynamics Distributed System (FDDS), and is designed to run under the FDDS User Interface / Executive (UIX). The FDD is transitioning from a mainframe based environment to systems running on engineering workstations. The GSS will be a library of highly reusable components that may be configured within the standard FDDS architecture to quickly produce low-cost satellite ground support systems. The estimates for the first release is that this library will contain approximately 200,000 lines of code. The main driver for developing generalized software is development cost and schedule improvement. The goal is to ultimately have at least 80 percent of all software required for a spacecraft mission (within the domain supported by the GSS) to be configured from the generalized components.

Stark, Mike↗