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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

DuraMAT Data Hub

The DuraMAT Data Hub has been supporting the consortium for the past six years. The Data Hub has had success in supporting the projects, providing a platform for sharing data within projects and to the public, and learning how to better leverage the existing software platform and the available Amazon Web Services environment. During this new generation of the Data Hub, we are looking at ways to help improve the data hub architecture, user experience, and improve operations by taking advantage of new technology platforms and software that will be more impactful on the consortium researchers and the broader scientific community. In this poster we will look at the current operational capabilities, data dissemination, and development that will improve the system in the near and far future.

14 SOLAR ENERGY↗
NASA NTRS2009

The Status of the Mock LISA Data Challenges

For the last four years, many gravitational-wave researchers around the world have participated in the Mock LISA Data Challenges (MLDCs), a program to demonstrate and encourage the development of LISA data-analysis capabilities, tools and techniques. In this poster, we present a summary of the results of MLDC 3, which was completed in 2009. During MLDC 3, 27 participants from 15 institutions successfully analyzed data sets that included Galactic binaries, coalescing spinning massive black holes, extreme-mass-ratio inspirals, cosmic-string cusp bursts and a stochastic gravitational-wave background. We also describe the technical and scientific challenges that will be addressed by future MLI)Cs, starting with MLDC 4, which is currently in progress.

Baker, John↗
NASA NTRSDate not supplied

Earth Science Data Processing With Nextflow

Earth science data processing tasks present many challenges. These tasks often process large input datasets and require scores of CPU-hours to generate results. All but the simplest tasks will be decomposed into a series of computational or data manipulation steps, also known as a scientific workflow. In order to reduce the burden of orchestrating and running the dependent processing steps, a workflow execution engine is required. This poster describes the lessons learned by the CLARREO Pathfinder (CPF) team while developing multiple scientific workflows and utilizing the open-source Nextflow engine to execute them in a cloud computing environment. The Nextflow engine is designed with the following stated goals: first, the engine does not dictate how individual steps in the task are implemented (i.e. it is language and interface agnostic); second, the engine supports easy configuration and modularity at the workflow level so that others can easily execute our workflows to reproduce results; lastly, the engine eases development by transparently scaling execution from local to remote environments. Nextflow was developed for the bioinformatics domain but is a good fit for other scientific workflows where the overall task is well-described by a dataflow diagram. The CPF team has developed Nextflow pipelines (i.e. scientific workflows) to simulate CLARREO radiance, generate large look-up tables for inter-calibration algorithms, and generate L4 intercalibration data products. These pipelines consume from single-digits to hundreds of thousands of CPU-hours. In the development and evolution of these pipelines we have discovered many design patterns, pitfalls, and solutions to common problems. Our goal is to demonstrate important aspects of how to design, implement, run, and ultimately share Nextflow pipelines in the domain of Earth science.

Aron D Bartle↗
DOE OSTI2024

Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2011

Development Roadmap for an Adjustable X-Ray Optics Observatory

We are developing adjustable X-ray optics to use on a mission such as SMART-X (see posters 38.02, 38.03 and Presentation 30.03). To satisfy the science problems expected to be posed by the next decadal survey, we anticipate requiring effective area greater than 1 square meter and Chandra-like angular resolution: approximately equal to 0.5 inches. To achieve such precise resolution we are developing adjustable mirror technology for X-ray astronomy application. This uses a thin film of piezoelectric material deposited on the back surface of the mirror to correct for figure distortions, including manufacturing errors and deflections due to gravity and thermal effects. We present here a plan to raise this technology from its current Level 2, to Level 6, by 2018.

Schwartz, Dan↗
NASA NTRS2009

Validating Solar and Heliospheric Models at the CCMC

The Community Coordinated Modeling Center (CCMC) hosts a growing number of models of the ambient and transient corona and heliosphere which are ultimately intended for use in space weather forecasting. independent validation of these models is a critical step in their development as potential forecasting tools for the space weather operations community. In this poster we report on validation studies of these models, all of which are also available for use by the research community through our runs-on-request system.

MacNeice, P. J.↗
NASA NTRS2011

HEASARC - The High Energy Astrophysics Science Archive Research Center

The High Energy Astrophysics Science Archive Research Center (HEASARC) is NASA's archive for high-energy astrophysics and cosmic microwave background (CMB) data, supporting the broad science goals of NASA's Physics of the Cosmos theme. It provides vital scientific infrastructure to the community by standardizing science data formats and analysis programs, providing open access to NASA resources, and implementing powerful archive interfaces. Over the next five years the HEASARC will ingest observations from up to 12 operating missions, while serving data from these and over 30 archival missions to the community. The HEASARC archive presently contains over 37 TB of data, and will contain over 60 TB by the end of 2014. The HEASARC continues to secure major cost savings for NASA missions, providing a reusable mission-independent framework for reducing, analyzing, and archiving data. This approach was recognized in the NRC Portals to the Universe report (2007) as one of the HEASARC's great strengths. This poster describes the past and current activities of the HEASARC and our anticipated developments in coming years. These include preparations to support upcoming high energy missions (NuSTAR, Astro-H, GEMS) and ground-based and sub-orbital CMB experiments, as well as continued support of missions currently operating (Chandra, Fermi, RXTE, Suzaku, Swift, XMM-Newton and INTEGRAL). In 2012 the HEASARC (which now includes LAMBDA) will support the final nine-year WMAP data release. The HEASARC is also upgrading its archive querying and retrieval software with the new Xamin system in early release - and building on opportunities afforded by the growth of the Virtual Observatory and recent developments in virtual environments and cloud computing.

Smale, Alan P.↗
NASA NTRS2012

Modeling Active Region Evolution - A New LWS TR and T Strategic Capability Model Suite

In 2006 the LWS TR&T Program funded us to develop a strategic capability model of slowly evolving coronal active regions. In this poster we report on the overall design, and status of our new modeling suite. Our design features two coronal field models, a non-linear force free field model and a global 3D MHD code. The suite includes supporting tools and a user friendly GUI which will enable users to query the web for relevant magnetograms, download them, process them to synthesize a sequence of photospheric magnetograms and associated photospheric flow field which can then be applied to drive the coronal model innner boundary, run the coronal models and finally visualize the results.

MacNeice, Peter↗
NASA NTRS2013

Development of FIAT-Based Parametric Thermal Protection System Mass Estimating Relationships for NASA's Multi-Mission Earth Entry Concept

Part of NASAs In-Space Propulsion Technology (ISPT) program is the development of the tradespace to support the design of a family of multi-mission Earth Entry Vehicles (MMEEV) to meet a wide range of mission requirements. An integrated tool called the Multi Mission System Analysis for Planetary Entry Descent and Landing or M-SAPE tool is being developed as part of Entry Vehicle Technology project under In-Space Technology program. The analysis and design of an Earth Entry Vehicle (EEV) is multidisciplinary in nature, requiring the application many disciplines. Part of M-SAPE's application required the development of parametric mass estimating relationships (MERs) to determine the vehicle's required Thermal Protection System (TPS) for safe Earth entry. For this analysis, the heat shield was assumed to be made of a constant thickness TPS. This resulting MERs will then e used to determine the pre-flight mass of the TPS. Two Mers have been developed for the vehicle forebaody. One MER was developed for PICA and the other consisting of Carbon Phenolic atop an Advanced Carbon-Carbon composition. For the the backshell, MERs have been developed for SIRCA, Acusil II, and LI-900. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed in this poster.

Sepka, Steven A.↗
NASA NTRSDate not supplied

Inflatable Habitat Testing Capabilities at MSFC

Since early 2022 Marshall Space Flight Center’s (MSFC) Test Lab (ET) has been the premier inflatable habitat testing organization for NASA. In the past two years the Center has strategically invested in this thriving business unit; bringing to life four distinct facilities and a dozen unique capabilities. The Center has been successful in partnering with companies developing softgoods architectures and has already executed several test campaigns for them. This poster gives an overview of the Test Lab’s capabilities and the facilities used for inflatable habitat testing.

Inflatable↗
NASA NTRSDate not supplied

Upgrades to the Mars Global Reference Atmospheric Model (Mars-GRAM)

The inability to test planetary spacecraft in the flight environment prior to a mission requires engineers to rely on ground-based testing and models of the vehicle and expected environments. One of the most widely used engineering reference models of planetary atmospheres are the Global Reference Atmospheric Models (GRAMs). The NASA Science Mission Directorate (SMD) has provided funding support to upgrade the GRAMs since Fiscal Year 2018. The GRAM upgrades are being developed by NASA Marshall Space Flight Center and NASA Langley Research Center. This poster provides details regarding recent MarsGRAM upgrades.

atmospheric models↗
DOE OSTI2025

STARTR: An Open-Source MARVEL model for the NRIC Virtual Test Bed [Poster]

The National Reactor Innovation Center (NRIC) seeks to improve the understanding of microreactor physics in industry and academia through the development of a Microreactor Applications Research Validation and Evaluation (MARVEL) reactor-based model, published on the Virtual Test Bed (VTB). To achieve this goal, the Sodium-cooled Thermal-spectrum Advanced Research Test Reactor (STARTR) model was built using publicly available MARVEL specifications where possible and approximations where applicable, and was optimized for fast runtimes for researchers to receive rapid simulation feedback. STARTR will fill a gap between stakeholder interest and available models, as the first Sodium-cooled Thermal Reactor (STR) hosted on the VTB with baseline performance sanctioned by INL. This project involved the definition of all materials used in the reactor, geometry and all reactor subcomponents, and assertion of tallies and simulation settings within OpenMC 0.13.3. This poster details a small subset of the overall reactor physics testing: the two-dimensional power peaking factors and the flux energy spectrum, as well as plots of the created geometry. Future work includes code-to-code verification between the OpenMC-based model and a separately designed MCNP 6.2-based model.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
NASA NTRSDate not supplied

Crustal Dynamics Data Information System (CDDIS) Contributions to GGOS

The Crustal Dynamics Data Information System (CDDIS) provides essential support for the Global Geodetic Observing System (GGOS) by operating a data and product archive for the main geodetic techniques. As GGOS matures and grows, the CDDIS adopts the latest data practices to strengthen its support for the community and ensure quality products are available in a timely manner. To this end, the CDDIS is continually refining its software backend, performing developments such as the 2023 implementation of a middleware processing system, which is successfully being used in operation to provide GNSS-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) and Global Differential GPS System (GDGPS) products. In addition, the CDDIS has 1) released new data and products, 2) performed updates to facilitate navigation of the archive, and 3) made it easier to cite the data and products being added. This poster explores the breadth of work done at the CDDIS and provides highlights of the latest developments.

Justine Woo↗
NASA NTRSDate not supplied

NASA’s Data Preservation Strategies for Ensuring Ongoing Use and Access: Leveraging the Capabilities at the NASA DAACs

As NASA prepares for the follow on to EOS through the deployment of many new space and airborne-based assets envisioned under the ESO initiative, the need for ensuring user access to the very large and diverse archive of past missions remains a critical endeavor for current and future research. The ESDIS team has been working for many years on developing strategies and implementations that will make the linkage between the data held in our archives and the emerging missions possible. The focus on how best to preserve these past data has proven to be a collaborative effort, and one that may well benefit from the adoption of innovative technical tools that enable organizational efficiencies. This poster reveals both aspects of NASA’s EOS data repository strategy by discussing the collaborative community efforts of development of ISO 19165-2 – an international standard supported by a team from many countries around the world, the use by EOSDIS DAACs of a Preservation Content Specification, and ongoing work with mission teams to ensure mission data and all associated information are preserved and available for current and future use.

Francis Lindsay↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗