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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 379 records · Page 21

Flow Regime Based Climatologies of Lightning Probabilities for Spaceports and Airports

Objective: provide forecasters with a "first guess" climatological lightning probability tool (1) Focus on Space Shuttle landings and NWS T AFs (2) Four circles around sites: 5-, 10-, 20- and 30 n mi (4) Three time intervals: hourly, every 3 hr and every 6 hr It is based on: (1) NLDN gridded data (2) Flow regime (3) Warm season months of May-Sep for years 1989-2004 Gridded data and available code yields squares, not circles Over 850 spread sheets converted into manageable user-friendly web-based GUI

Bauman, William H., III↗

Business Systems Branch Abilities, Capabilities, and Services Web Page

During the INSPIRE summer internship I acted as the Business Systems Branch Capability Owner for the Kennedy Web-based Initiative for Communicating Capabilities System (KWICC), with the responsibility of creating a portal that describes the services provided by this Branch. This project will help others achieve a clear view ofthe services that the Business System Branch provides to NASA and the Kennedy Space Center. After collecting the data through the interviews with subject matter experts and the literature in Business World and other web sites I identified discrepancies, made the necessary corrections to the sites and placed the information from the report into the KWICC web page.

Cortes-Pena, Aida Yoguely↗

NASA Range Safety Annual Report 2007

As always, Range Safety has been involved in a number of exciting and challenging activities and events. Throughout the year, we have strived to meet our goal of protecting the public, the workforce, and property during range operations. During the past year, Range Safety was involved in the development, implementation, and support of range safety policy. Range Safety training curriculum development was completed this year and several courses were presented. Tailoring exercises concerning the Constellation Program were undertaken with representatives from the Constellation Program, the 45th Space Wing, and the Launch Constellation Range Safety Panel. Range Safety actively supported the Range Commanders Council and it subgroups and remained involved in updating policy related to flight safety systems and flight safety analysis. In addition, Range Safety supported the Space Shuttle Range Safety Panel and addressed policy concerning unmanned aircraft systems. Launch operations at Kennedy Space Center, the Eastern and Western ranges, Dryden Flight Research Center, and Wallops Flight Facility were addressed. Range Safety was also involved in the evaluation of a number of research and development efforts, including the space-based range (formerly STARS), the autonomous flight safety system, the enhanced flight termination system, and the joint advanced range safety system. Flight safety system challenges were evaluated. Range Safety's role in the Space Florida Customer Assistance Service Program for the Eastern Range was covered along with our support for the Space Florida Educational Balloon Release Program. We hope you have found the web-based format both accessible and easy to use. Anyone having questions or wishing to have an article included in the 2008 Range Safety Annual Report should contact Alan Dumont, the NASA Range Safety Program Manager located at the Kennedy Space Center, or Michael Dook at NASA Headquarters.

Dumont, Alan G.↗

Tower Mesonetwork Climatology and Interactive Display Tool

Forecasters at the 45th Weather Squadron and Spaceflight Meteorology Group use data from the tower network over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to evaluate Launch Commit Criteria, and issue and verify forecasts for ground operations. Systematic biases in these parameters could adversely affect an analysis, forecast, or verification. Also, substantial geographical variations in temperature and wind speed can occur under specific wind directions. To address these concerns, the Applied Meteorology Unit (AMU) developed a climatology of temperatures and winds from the tower network, and identified the geographical variation and significant tower biases. The mesoclimate is largely driven by the complex land-water interfaces across KSC/CCAFS. Towers with close proximity to water typically had much warmer nocturnal temperatures and higher wind speeds throughout the year. The strongest nocturnal wind speeds occurred from October to March whereas the strongest mean daytime wind speeds occurred from February to May. These results of this project can be viewed by forecasters through an interactive graphical user interface developed by the AMU. The web-based interface includes graphical and map displays of mean, standard deviation, bias, and data availability for any combination of towers, variables, months, hours, and wind directions.

Case, Jonathan L.↗

NASA's Integrated Instrument Simulator Suite for Atmospheric Remote Sensing from Spaceborne Platforms (ISSARS) and Its Role for the ACE and GPM Missions

Forward simulation is an indispensable tool for evaluation of precipitation retrieval algorithms as well as for studying snow/ice microphysics and their radiative properties. The main challenge of the implementation arises due to the size of the problem domain. To overcome this hurdle, assumptions need to be made to simplify compiles cloud microphysics. It is important that these assumptions are applied consistently throughout the simulation process. ISSARS addresses this issue by providing a computationally efficient and modular framework that can integrate currently existing models and is also capable of expanding for future development. ISSARS is designed to accommodate the simulation needs of the Aerosol/Clouds/Ecosystems (ACE) mission and the Global Precipitation Measurement (GPM) mission: radars, microwave radiometers, and optical instruments such as lidars and polarimeter. ISSARS's computation is performed in three stages: input reconditioning (IRM), electromagnetic properties (scattering/emission/absorption) calculation (SEAM), and instrument simulation (ISM). The computation is implemented as a web service while its configuration can be accessed through a web-based interface.

real-aperture instruments↗

Access Control of Web and Java Based Applications

Cyber security has gained national and international attention as a result of near continuous headlines from financial institutions, retail stores, government offices and universities reporting compromised systems and stolen data. Concerns continue to rise as threats of service interruption, and spreading of viruses become ever more prevalent and serious. Controlling access to application layer resources is a critical component in a layered security solution that includes encryption, firewalls, virtual private networks, antivirus, and intrusion detection. In this paper we discuss the development of an application-level access control solution, based on an open-source access manager augmented with custom software components, to provide protection to both Web-based and Java-based client and server applications.

cybersecurity↗

System Enhancements for Mechanical Inspection Processes

Quality inspection of parts is a major component to any project that requires hardware implementation. Keeping track of all of the inspection jobs is essential to having a smooth running process. By using HTML, the programming language ColdFusion, and the MySQL database, I created a web-based job management system for the 170 Mechanical Inspection Group that will replace the Microsoft Access based management system. This will improve the ways inspectors and the people awaiting inspection view and keep track of hardware as it is in the inspection process. In the end, the management system should be able to insert jobs into a queue, place jobs in and out of a bonded state, pre-release bonded jobs, and close out inspection jobs.

inspection processes↗

Request-Driven Schedule Automation for the Deep Space Network

The DSN Scheduling Engine (DSE) has been developed to increase the level of automated scheduling support available to users of NASA s Deep Space Network (DSN). We have adopted a request-driven approach to DSN scheduling, in contrast to the activity-oriented approach used up to now. Scheduling requests allow users to declaratively specify patterns and conditions on their DSN service allocations, including timing, resource requirements, gaps, overlaps, time linkages among services, repetition, priorities, and a wide range of additional factors and preferences. The DSE incorporates a model of the key constraints and preferences of the DSN scheduling domain, along with algorithms to expand scheduling requests into valid resource allocations, to resolve schedule conflicts, and to repair unsatisfied requests. We use time-bounded systematic search with constraint relaxation to return nearby solutions if exact ones cannot be found, where the relaxation options and order are under user control. To explore the usability aspects of our approach we have developed a graphical user interface incorporating some crucial features to make it easier to work with complex scheduling requests. Among these are: progressive revelation of relevant detail, immediate propagation and visual feedback from a user s decisions, and a meeting calendar metaphor for repeated patterns of requests. Even as a prototype, the DSE has been deployed and adopted as the initial step in building the operational DSN schedule, thus representing an important initial validation of our overall approach. The DSE is a core element of the DSN Service Scheduling Software (S(sup 3)), a web-based collaborative scheduling system now under development for deployment to all DSN users.

Johnston, Mark D.↗

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↗

Use of QuakeSim and UAVSAR for Earthquake Damage Mitigation and Response

Spaceborne, airborne, and modeling and simulation techniques are being applied to earthquake risk assessment and response for mitigation from this natural disaster. QuakeSim is a web-based portal for modeling interseismic strain accumulation using paleoseismic and crustal deformation data. The models are used for understanding strain accumulation and release from earthquakes as well as stress transfer to neighboring faults. Simulations of the fault system can be used for understanding the likelihood and patterns of earthquakes as well as the likelihood of large aftershocks from events. UAVSAR is an airborne L-band InSAR system for collecting crustal deformation data. QuakeSim, UAVSAR, and DESDynI (following launch) can be used for monitoring earthquakes, the associated rupture and damage, and postseismic motions for prediction of aftershock locations.

fault systems↗

Web Based Tool for Mission Operations Scenarios

A conventional practice for spaceflight projects is to document scenarios in a monolithic Operations Concept document. Such documents can be hundreds of pages long and may require laborious updates. Software development practice utilizes scenarios in the form of smaller, individual use cases, which are often structured and managed using UML. We have developed a process and a web-based scenario tool that utilizes a similar philosophy of smaller, more compact scenarios (but avoids the formality of UML). The need for a scenario process and tool became apparent during the authors' work on a large astrophysics mission. It was noted that every phase of the Mission (e.g., formulation, design, verification and validation, and operations) looked back to scenarios to assess completeness of requirements and design. It was also noted that terminology needed to be clarified and structured to assure communication across all levels of the project. Attempts to manage, communicate, and evolve scenarios at all levels of a project using conventional tools (e.g., Excel) and methods (Scenario Working Group meetings) were not effective given limitations on budget and staffing. The objective of this paper is to document the scenario process and tool created to offer projects a low-cost capability to create, communicate, manage, and evolve scenarios throughout project development. The process and tool have the further benefit of allowing the association of requirements with particular scenarios, establishing and viewing relationships between higher- and lower-level scenarios, and the ability to place all scenarios in a shared context. The resulting structured set of scenarios is widely visible (using a web browser), easily updated, and can be searched according to various criteria including the level (e.g., Project, System, and Team) and Mission Phase. Scenarios are maintained in a web-accessible environment that provides a structured set of scenario fields and allows for maximum visibility across the project. One key aspect is that the tool was built for a scenario process that accounts for stakeholder input, review, comment, and concurrence. By creating well-designed opportunities for stakeholder input and concurrence and by making the scenario content easily accessible to all project personnel, we maximize the opportunities for stakeholders to both understand and agree on the concepts for how their mission is to be carried out.

Boyles, Carole A.↗

Implementing distributed operations : a comparison of two Deep Space Missions

Two very different deep space exploration missions—Mars Exploration Rover and Cassini—have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a prime mission of four years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process.

Larsen, Barbara↗

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

Controls Status of Fermilab's PIP-II Project

The Fermilab Proton Improvement Project II (PIP-II) is building a new Super Conducting Linear Accelerator (SCL) accelerating protons to 800 MeV for injection into the rest of the FNAL beam complex. Key progress since the last status report given at ICALEPCS includes the adoption of modern DevOps practices with continuous integration and GitOps-based deployments, commissioning of EPICS-based systems at the Cryomodule Test Facility, and integration of a Virtual Accelerator framework for application development ahead of installation. In parallel, web-based applications using Dart and Flutter have matured, providing secure, unified access to both EPICS and legacy ACNET data. Data acquisition and timing systems have also evolved. This paper presents the current state of controls, emphasizing these recent developments and outlining upcoming milestones as PIP-II approaches commissioning of its cryoplant in 2026 and the Warm Front End in 2027.

Crisp, D. B. [Fermilab]↗

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗

Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics

The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Here, our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA’s petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Computer science↗

Deep Space Network equipment performance, reliability, and operations management information system

The Deep Space Mission System (DSMS) Operations Program Office and the DeepSpace Network (DSN) facilities utilize the Discrepancy Reporting Management System (DRMS) to collect, process, communicate and manage data discrepancies, equipment resets, physical equipment status, and to maintain an internal Station Log. A collaborative effort development between JPL and the Canberra Deep Space Communication Complex delivered a system to support DSN Operations.

discrepancy reporting DSN operations web-based too↗