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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 163 records · Page 9

The CEOS WGISS Atmospheric Composition Portal

Goal: Demonstrate the feasibility of connecting distributed atmospheric composition data and analysis tools into a common and shared web framework. Initial effort focused on: a) Collaboratively creating a web application within WDC-RSAT for comparison of satellite derived atmospheric composition datasets accessed from distributed data sources. b) Implementation of data access and interoperability standards. c) Sollicit feedback from paternal users; Especially from ACC participants.

Lynnes, Chris↗

NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data

There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.

soil moisture data↗

Hierarchical Data Formats (HDF) Update

In this presentation, we will talk about the latest releases of HDF4 and HDF5 software and tools, new features available in HDF5, and roadmap for the HDF software. We will also solicit feedback from the users of HDF data and HDF application developers on new features and new tools. The talk will cover: Difference between 1.8 and 1.10 releases and how and when to move to the latest release Features of the recent HDF5 1.8.19, 1.10.1 and HDF 4.2.13 Overview of HDF View 3.0 and other enhancements to tools Supported compilers and systems Open discussion of new requirements and wish list of the HDF features Compression library for interoperability with h5py and Pandas and better floating-point data compression.

HDFView↗

Supervisory Control of a Humanoid Robot in Microgravity for Manipulation Tasks

Teleoperation is the dominant form of dexterous robotic tasks in the field. However, there are many use cases in which direct teleoperation is not feasible such as disaster areas with poor communication as posed in the DARPA Robotics Challenge, or robot operations on spacecraft a large distance from Earth with long communication delays. Presented is a solution that combines the Affordance Template Framework for object interaction with TaskForce for supervisory control in order to accomplish high level task objectives with basic autonomous behavior from the robot. TaskForce, is a new commanding infrastructure that allows for optimal development of task execution, clear feedback to the user to aid in off-nominal situations, and the capability to add autonomous verification and corrective actions. This framework has allowed the robot to take corrective actions before requesting assistance from the user. This framework is demonstrated with Robonaut 2 removing a Cargo Transfer Bag from a simulated logistics resupply vehicle for spaceflight using a single operator command. This was executed with 80% success with no human involvement, and 95% success with limited human interaction. This technology sets the stage to do any number of high level tasks using a similar framework, allowing the robot to accomplish tasks with minimal to no human interaction.

Farrell, Logan C.↗

GES DISC Datalist Improves Earth Science Data Discoverability

At American Geophysical Union(AGU) 2016 Fall Meeting, Goddard Earth Sciences Data Information Services Center (GES DISC) unveiled a novel way to access data: Datalist. Currently, datalist is a collection of predefined data variables from one or more archived datasets, curated by our subject matter expert (SME). Our science support team has curated a predefined Hurricane Datalist and received very positive feedback from the user community. Datalist uses the same architecture our new website uses and have the same look and feel as other datasets on our web site. and also provides a one-stop shopping for data, metadata, citation, documentation, visualization and other available services. Since the last AGU Meeting, we have further developed a few new datalists corresponding to the Big Earth Data Initiative (BEDI) Societal Benefit Areas and A-Train data. We now have four datalists: Hurricane, Wind Energy, Greenhouse Gas and A-Train. We have also started working with our User Working Group members to create their favorite datalists and working with other DAAC to explore the possibility to include their products in our datalists that may also lead to a future of potential federated (cross-DAAC) datalists. Since our datalist prototype effort was a success, we are planning to make datalist operational. It's extremely important to have a common metadata model to support datalist, this will also be the foundation of federated datalist. We mapped our datalist metadata model to the unpublished UMM(Universal Metadata Model)-Var (Variable) (June version) and found that the UMM-var together with UMM-C (Collection) and possible UMM-S (Service) will meet our basic requirements. For example: Dataset shortname, and version are already specified in UMM-C, variable name, long name, units, dimensions are all specified in UMM-Var. UMM-Var also facilitates Science Keywords to allow tagging at variable level and Characteristics for optional variable characteristics. Measurements is useful for grouping of the variables and Set is promising to define datalist. And finally, the UMM-Service model to specify the available services for the variable will be very beneficial. In summary, UMM-Var, UMM-C and UMM-S are the basis of federated datalist and the development and deployment of datalist will contribute to the evolution of the UMM.

datalist↗

CAIDA CUI Confirmation for OMRS & LCC SOCRRATES Emulator and iSEE Upgrade, Operations, & Analysis

This internship has focused on providing solutions for the Customer Avionics Interface Development and Analysis (CAIDA) subsystem. The main emulator that has been used during this internship is the Software-Only CEV (Crew Exploration Vehicle) Risk Reduction Analysis and Test Engineering Simulator (SOCRRATES). This emulator uses advanced math and physics methods to simulate specific points in a mission, such as ascent, entry, and orbit. Exploration Ground Systems (EGS) must ensure that all KSC based ground systems can be properly integrated with the flight vehicle software, therefore, the Modeling and Simulation Branch (NE-XM) of the KSC (Kennedy Space Center) Engineering Directorate supports a virtual environment that simulates the interface between ground systems and the flight vehicle. A primary component in assuring that is knowing whether the emulators have incorporated the correct CUIs (Compact Unique Identifiers) into their system, as well as understanding both the static and dynamic responses of the individual CUIs. Also, an effort for verification of Operational Maintenance Requirements Specifications (OMRS) and Launch Commit Criteria (LCC) that are supported by SOCRRATES for the Orion Crew Module were part of the project tasks this semester. This internship also focused on comparing two different simulation Commercial-off-the-shelf (COTS) products and to determine whether or not a COTS package was a viable replacement for the current software that the iSEE (Immersive Simulations and Engineering Environment) lab uses. Upon research and testing, I found that this software was not feasible for the lab. It could not easily load CAD (Computer-Aided Design) or CREO models, give live feedback while the user is in the environment, and was not compatible with a virtual reality headset, all of which are necessary for the lab.

Bundy, Caleb↗

Human Landing System Lunar Thermal Analysis Guidebook

The purpose of the Human Landing System (HLS) Lunar Thermal Analysis Guidebook (L-TAG) is to provide guidance to experienced thermal engineering personnel on how to conduct worst-case hot and cold lunar thermal analyses for the design of HLS hardware in both lunar orbit and lunar surface environments. The HLS L-TAG will include pointers to the Cross-Program Design Specification for Natural Environments (DSNE), SLS-SPEC-159, and best practices/approaches for interpreting and complying with the DSNE lunar thermal environments in the analysis of HLS spacecraft, vehicles and systems. The HLS L-TAG is a reference document that is available to all HLS thermal analysts. In the event of a conflict with the descriptions provided herein, the DSNE takes precedence. This document represents the best available information at the time of publication and will undergo updates as the HLS program evolves. Feedback from the user community is encouraged to support further refinement of the Guidebook.

Thermal Analysis↗

NASA SPoRT Land Information System Products for Soil Moisture Analysis

The NASA Short-term Prediction Research and Transition (SPoRT) Program has been producing a near real-time instance of NASA’s Land Information System (hereafter known as SPoRT-LIS) since 2010, which contains output of soil moisture and temperature at layered depths. The unique configuration of the SPoRT-LIS enables decision-making on operational timescales since it assimilates near real-time observations such as Green Vegetation Fraction from the Visible Infrared Imaging Radiometer Suite and Quantitative Precipitation Estimates from the Multi-Radar Multi-Sensor System. The SPoRT-LIS was developed initially to provide land surface initialization variables for local numerical weather prediction models, such as the Weather Research and Forecasting (WRF) model. The earliest documented uses of the SPoRT-LIS as a tool for local drought analysis came from the National Weather Service Office in Huntsville, AL in 2011, in which data were used to provide recommendations for drought category changes to the U.S. Drought Monitor. Through engagement with SPoRT collaborative partners, use of the SPoRT-LIS has gradually expanded in recent years as a component of drought analysis and feedback to the U.S. Drought Monitor. This effort was aided by feedback from end users who expressed needs for specific soil moisture variables, which led to increased applicability for analysis by others in the drought community. This presentation will provide information on the SPoRT-LIS for drought analysis and the collaborative process that has led to changes in product output to meet user needs, with focus in the Southern Appalachian region. However, applications for hydrology and fire weather will also be discussed.

Land surface modeling↗

Lunar Thermal Analysis Guidebook (L-TAG): Thermo-physical and Optical Properties of Lunar Regolith

The purpose of the Human Landing System (HLS) Lunar Thermal Analysis Guidebook (L-TAG) is to provide guidance to experienced thermal engineering personnel on how to conduct worst-case hot and cold lunar thermal analyses for the design of HLS hardware in both lunar orbit and lunar surface environments. The HLS L-TAG will include pointers to the Cross-Program Design Specification for Natural Environments (DSNE), SLS-SPEC-159, and best practices/approaches for interpreting and complying with the DSNE lunar thermal environments in the analysis of HLS spacecraft, vehicles and systems. The HLS L-TAG is a reference document that is available to all HLS thermal analysts. In the event of a conflict with the descriptions provided herein, the DSNE takes precedence. This document represents the best available information at the time of publication and will undergo updates as the HLS program evolves. Feedback from the user community is encouraged to support further refinement of the Guidebook.

Thermal Analysis↗

Lunar Thermal Analysis Guidebook (L-TAG)

The purpose of the Human Landing System (HLS) Lunar Thermal Analysis Guidebook (L-TAG) is to provide guidance to experienced thermal engineering personnel on how to conduct worst-case hot and cold lunar thermal analyses for the design of HLS hardware in both lunar orbit and lunar surface environments. The HLS L-TAG will include pointers to the Cross-Program Design Specification for Natural Environments (DSNE), SLS-SPEC-159, and best practices/approaches for interpreting and complying with the DSNE lunar thermal environments in the analysis of HLS spacecraft, vehicles and systems. The HLS L-TAG is a reference document that is available to all HLS thermal analysts. In the event of a conflict with the descriptions provided herein, the DSNE takes precedence. This document represents the best available information at the time of publication and will undergo updates as the HLS program evolves. Feedback from the user community is encouraged to support further refinement of the Guidebook.

Thermal Analysis↗

Lunar Thermal Analysis Guidebook (L-TAG)

The purpose of the Human Landing System (HLS) Lunar Thermal Analysis Guidebook (L-TAG) is to provide guidance to experienced thermal engineering personnel on how to conduct worst-case hot and cold lunar thermal analyses for the design of HLS hardware in both lunar orbit and lunar surface environments. The HLS L-TAG will include pointers to the Cross-Program Design Specification for Natural Environments (DSNE), SLS-SPEC-159, and best practices/approaches for interpreting and complying with the DSNE lunar thermal environments in the analysis of HLS spacecraft, vehicles and systems. The HLS L-TAG is a reference document that is available to all HLS thermal analysts. In the event of a conflict with the descriptions provided herein, the DSNE takes precedence. This document represents the best available information at the time of publication and will undergo updates as the HLS program evolves. Feedback from the user community is encouraged to support further refinement of the Guidebook.

Thermal Analysis↗

Hourly Stream Heights – A Short-term Deep Learning Prediction Model

River flooding can have a detrimental impact on a community by causing loss of life, loss or damage to property, and damage to infrastructure. Having the capability to forecast flooding events can prevent the loss of life and mitigate damage to property. A programmatic, data-driven approach using deep learning to forecast a stream’s gauge height every 6 hours has been developed by NASA’s Short-term Prediction Research and Transition Center (SPoRT) and is currently in operation. Based on our end user engagement and feedback, this medium-term product has been successfully adopted by several National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC). SPoRT is currently researching and developing a short-term hourly deep learning model which will be useful in forecasting flash flood events.

Michael Antia↗

GeoBridge: Unearthing Insights from Connecting Communities to Geothermal Information and Opportunities: Preprint

Knowledge is essential for overcoming obstacles in the development and adoption of geothermal technologies, and the geothermal community is home to numerous tools, events and organizations dedicated to sharing knowledge. However, many of these tools can be difficult to find, their resources undiscoverable by search engines, available only to members, or hidden away behind pay walls (Weers et al., 2024). The Department of Energy's (DOE) GeoBridge was developed by the National Renewable Energy Laboratory (NREL) to help bridge gaps in information and connect the geothermal community to the resources it needs. Launched in October 2024, GeoBridge aspires to expand the pool of geothermal stakeholders by providing in-roads to geothermal information, tools, and community resources. It helps to make these resources available to the broader geothermal community as well as those looking to join, such as entrepreneurs or innovators in adjacent industries looking to expand into geothermal energy. This paper explores a post-launch analysis of GeoBridge including data from analytics, feedback from GeoBridge users, the geothermal community, and the GeoBridge Advisory Group as well as an analysis of efficacy of various promotions for GeoBridge.

15 GEOTHERMAL ENERGY↗

An Update on GPM and TRMM Data Services at NASA GES DISC

The Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to data archives of the NASA-JAXA Global Precipitation Measurement (GPM), the Tropical Rainfall Measuring Mission (TRMM), and other NASA missions and projects. To maximize the use of NASA data products in scientific research and applications as well as for societal benefits, we provide data and information services that make datasets easy to find and use through simplification of data access for users at all levels around the world. Over the years, user-friendly data services have been developed at GES DISC, including data subsetting, format conversion, online visualization and analysis (i.e. Giovanni), user support system, etc. We routinely analyze questions, feedback, and use cases from users and algorithm developers around the world as well as best practices and new technology to improve existing services and formulate new data services. Interaction between users and algorithm developers is an important process for identifying issues in products, collecting user requirements, and improving product quality and usability. Staff members regularly communicate with algorithm developers with user questions and concerns through conferences and workshops. We publish peer-reviewed papers and articles in major Earth science journals and book chapters to describe NASA global and regional precipitation datasets and services with examples. News articles about GPM and TRMM datasets associated with significant events are regularly posted in the GES DISC Web portal and social media. We also actively participate in training activities. In this presentation, we present our latest activities about GPM and TRMM data services, data/service metrics, and future plans at GES DISC.

Liu, Z.↗

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗

MOOSE-Workbench integration and MOOSE meshing capability enhancements to facilitate inputs and outputs for multiphysics modeling

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and out put inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

MOOSE–Workbench Integration and MOOSE Meshing Capability Enhancements to Facilitate Inputs and Outputs for Multiphysics Modeling

The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source framework that supports many of the US Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) technical areas (TA). These TAs develop and use NEAMS physics and coupling modules in multiple ways to enable the research and development of complex physics models. In addition to the MOOSE framework, the NEAMS Workbench user interface provides a common analysis environment with user-interaction accelerators that streamline the tasks of model creation, review, execution, and output inspection. In FY 2024, objectives were realized in the MOOSE framework application development support and user-oriented improvements. Application development improvements support both developers and users with an expanded Reactor Module and Mesh System, stateful material property support for mortar contact, and customizable convergence criteria. Additionally, new user-oriented features were implemented in the MOOSE framework language server, including autocompletion snippets, definition from source and find reference navigations, and syntax overrides. Lastly, improvements were made to the input interpreter necessary to support the MOOSE language server and the NEAMS Workbench so that they can interact with syntactically incomplete user inputs. These improvements and more were intended to address stakeholder feedback and improve developer and user ability to conduct advanced nuclear energy modeling and simulation in support of DOE and industry needs.

97 - MATHEMATICS AND COMPUTING↗