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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The Hubble Space Telescope quasar absorption line key project. II - Data calibration and absorption-line selection

We present the observational and data processing aspects of the Hubble Space Telescope Quasar Absorption Line Key Project. Topics discussed include the observational technique, calibration of the data, software that simulates the data, the automated procedure used to identify and characterize the absorption features, and the determination of the sensitivity limits of the survey.

Schneider, Donald P.↗
DOE OSTI2024

Forcing data (CESM2/CMIP6) for projection of drought impacts (2015-2100) at the K34 site in Manaus, Brazil

Historical and projected output data variables extracted and derived from Community Earth System Model 2 (CESM2) runs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive. CESM2 is a fully coupled Earth system model used in simulations of Earth's past, present, and future climates (Danabasoglu et al., 2020). Variables in this dataset are in six-hourly resolution, and include air temperature (both in K and ℃), specific humidity (kg kg-1), air pressure (Pa), relative humidity (%), and vapor pressure deficit (kPa). CESM2 was the only CMIP6 model that provided VPD at the high temporal resolution required for this analysis. Data are included in .csv files, and the text file CESM2-CMIP6_forcing_K34-Manaus_headers.txt provides descriptions of data file headers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Murray J. Martin (1935–2022)

The field of nuclear data lost a pioneer with the passing of Murray Martin on March 9, 2022. Born in Regina, Canada in 1935, Murray Martin received his B.A. and M.A. in experimental physics from the University of Saskatchewan and his PhD in theoretical nuclear physics in 1962 from McMaster Univ. His thesis was entitled “A Study of the Low-Lying Excited Levels in the Even Lead Isotopes”. Additionally, he joined the NSF Data Project in 1962 in Washington, DC, and then followed that project as it moved to ORNL in 1964 as the Nuclear Data Project (NDP). Murray stayed with the NDP until his retirement in 1997 but resumed his work on a part-time basis in 2004 as a subcontractor to ORNL, which he continued until his last days.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2024

Crew Health and Performance Integrated Data Architecture Project Updates

Future Human Exploration missions will face new constraints as crews move further from terrestrial communication, resupply, and the real-time support enjoyed by Low Earth Orbit missions today. Exploration crews will need to be more self-reliant and able to respond to emergencies without immediate support from ground-based personnel. A new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to assist the crew’s work, help maintain their health, and inform the decisions they make on these future Exploration missions. The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project is laying a foundation for these future technologies by integrating sources of data generated by and around the crew and then providing them though common data models and Application Programming Interfaces to external systems. The combined data model makes comprehensive Crew Health and Performance data accessible and more meaningful to the decision-making process. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software, current integrations, updates to the architecture, and examples of exploration scenarios in which CHP-IDA would be used.

B Schmitt↗
NASA NTRS2024

Crew Health and Performance Integrated Data Architecture Project Update

Future Human Exploration missions will face new constraints as crews move further from terrestrial communication, resupply, and the real-time support enjoyed by Low Earth Orbit missions today. Exploration crews will need to be more self-reliant and able to respond to emergencies without immediate support from ground-based personnel. A new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to assist the crew’s work, help maintain their health, and inform the decisions they make on these future Exploration missions. The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project is laying a foundation for these future technologies by integrating sources of data generated by and around the crew then providing them though common data models and Application Programming Interfaces to external systems. The combined data model makes comprehensive Crew Health and Performance data accessible and more meaningful to the decision-making process. This presentation will describe the currently ongoing effort to develop a path-to-flight concept of the CHP-IDA software, current integrations that have been developed, updates to the architecture, and examples of the corresponding exploration scenarios in which CHP-IDA would be used.

Exploration↗
NASA NTRS1993

Software quality: Process or people

This paper will present data related to software development processes and personnel involvement from the perspective of software quality assurance. We examine eight years of data collected from six projects. Data collected varied by project but usually included defect and fault density with limited use of code metrics, schedule adherence, and budget growth information. The data are a blend of AFSCP 800-14 and suggested productivity measures in Software Metrics: A Practioner's Guide to Improved Product Development. A software quality assurance database tool, SQUID, was used to store and tabulate the data.

Palmer, Regina↗
DOE OSTI2026

AI-Ready Data Pilot Project Report

The proliferation of artificial intelligence in scientific research has created an urgent need to define "AI-ready data" for researchers and, more importantly, provide resources to help them produce AI-ready data. At Pacific Northwest National Laboratory, we conducted a pilot study with three data scientists evaluating three CSV datasets from different scientific domains, followed by semi-structured interviews capturing assessment practices. Our findings reveal that AI-readiness evaluation is intuition-based, with practitioners asking "How fast can I go from raw data to my machine learning pipeline?" Data scientists consistently prioritized workflow efficiency, human interpretability, and quality stewardship signals. From these insights, we developed a practical evaluation framework comprising data requirements, metadata standards, and validation tests that provides actionable criteria for producing and curating AI-ready datasets, addressing the gap between theoretical understanding and practical implementation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

IUS/TUG orbital operations and mission support study. Volume 4: Project planning data

Planning data are presented for the development phases of interim upper stage (IUS) and tug systems. Major project planning requirements, major event schedules, milestones, system development and operations process networks, and relevant support research and technology requirements are included. Topics discussed include: IUS flight software; tug flight software; IUS/tug ground control center facilities, personnel, data systems, software, and equipment; IUS mission events; tug mission events; tug/spacecraft rendezvous and docking; tug/orbiter operations interface, and IUS/orbiter operations interface.

Source record↗
DOE OSTI2022

Data Catalog Project - A Browsable, Searchable, Metadata System

Modern experiments are typically conducted by large, extended, where researchers rely on other team members to produce much of the data they use. The experiments record very large numbers of measurements which can be difficult for users to find, access and understand. We are developing a system for users to annotate their data products with structured metadata, providing data consumers with a discoverable, browsable data index. Machine understandable metadata captures the underlying semantics of the recorded data, which can then be consumed by both programs, and interactively by users. Collaborators can use these metadata to select and understand recorded measurements.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC), a time projection chamber is used as the main tracking detector, which records particle trajectories in a volume of three-dimensional (3D) cylinder. The resulting data are usually very sparse with occupancy around 10.8%. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE), outperforms traditional methods both in compression rate and reconstruction accuracy. BCAE can also utilize the computation power of graphical processing units suitable for deployment in a modern heterogeneous highperformance computing environment. This work introduces two BCAE variants: BCAE++ and BCAE-2D. BCAE++ achieves a 15% better compression ratio and a 77% better reconstruction accuracy measured in mean absolute error compared with BCAE. BCAE-2D treats the radial direction as the channel dimension of an image, resulting in a 3× speedup in compression throughput. In addition, we demonstrate an unbalanced autoencoder with a larger decoder can improve reconstruction accuracy without significantly sacrificing throughput. Lastly, we observe both the BCAE++ and BCAE-2D can benefit more from using half-precision mode in throughput (76 - 79% increase) without loss in reconstruction accuracy. The source code and links to data and pretrained models can be found at https://github.com/BNL-DAQ-LDRD/NeuralCompression_v2

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Distributed Optimization for Nonrigid Nano-Tomography

Resolution level and reconstruction quality in nano-computed tomography (nano-CT) are in part limited by the stability of microscopes, because the magnitude of mechanical vibrations during scanning becomes comparable to the imaging resolution, and the ability of the samples to resist radiation induced deformations during data acquisition. In such cases, there is no incentive in recovering the sample state at different time steps like in time-resolved reconstruction methods, but instead the goal is to retrieve a single reconstruction at the highest possible spatial resolution and without any imaging artifacts. Here we propose a distributed optimization solver for tomographic imaging of samples at the nanoscale. Our approach solves the tomography problem jointly with projection data alignment, nonrigid sample deformation correction, and regularization. Projection data consistency is regulated by dense optical flow estimated by Farneback's algorithm, leading to sharp sample reconstructions with less artifacts. Synthetic data tests show robustness of the method to Poisson and low-frequency background noise. We accelerated the solver on multi-GPU systems and validated the method on three nano-imaging experimental data sets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

A Predictive Approach to Eliminating Errors in Software Code

NASA s Metrics Data Program Data Repository is a database that stores problem, product, and metrics data. The primary goal of this data repository is to provide project data to the software community. In doing so, the Metrics Data Program collects artifacts from a large NASA dataset, generates metrics on the artifacts, and then generates reports that are made available to the public at no cost. The data that are made available to general users have been sanitized and authorized for publication through the Metrics Data Program Web site by officials representing the projects from which the data originated. The data repository is operated by NASA s Independent Verification and Validation (IV&V) Facility, which is located in Fairmont, West Virginia, a high-tech hub for emerging innovation in the Mountain State. The IV&V Facility was founded in 1993, under the NASA Office of Safety and Mission Assurance, as a direct result of recommendations made by the National Research Council and the Report of the Presidential Commission on the Space Shuttle Challenger Accident. Today, under the direction of Goddard Space Flight Center, the IV&V Facility continues its mission to provide the highest achievable levels of safety and cost-effectiveness for mission-critical software. By extending its data to public users, the facility has helped improve the safety, reliability, and quality of complex software systems throughout private industry and other government agencies. Integrated Software Metrics, Inc., is one of the organizations that has benefited from studying the metrics data. As a result, the company has evolved into a leading developer of innovative software-error prediction tools that help organizations deliver better software, on time and on budget.

Source record↗
NASA NTRS2008

Modifying the Heliophysics Data Policy to Better Enable Heliophysics Research

The Heliophysics (HP) Science Data Management Policy, adopted by HP in June 2007, has helped to provide a structure for the HP data lifecycle. It provides guidelines for Project Data Management Plans and related documents, initiates Resident Archives to maintain data services after a mission ends, and outlines a route to the unification of data finding, access, and distribution through Virtual observatories. Recently we have filled in missing pieces that assure more coherence and a home for the VxOs (through the 'Heliophsyics Data and Model Consortium'), and provide greater clarity with respect to long term archiving. In particular, the new policy which has been vetted with many community members, details the 'Final Archives' that are to provide long-term data access. These are distinguished from RAs in that they provide little additional service beyond servicing data, but critical to their success is that the final archival materials include calibrated data in useful formats such as one finds in CDAWeb and various ASCII or FITS archives. Having a clear goal for legacy products, to be detailed as part of the Mission Archives Plans presented at Senior Reviews, will help to avoid the situation so common in the past of having archival products that preserve bits well but not readily usable information. We hope to avoid the need for the large numbers of 'data upgrade' projects that have been necessary in recent years.

Hayes, Jeffrey↗
NASA NTRS2019

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗
DOE OSTI2023

Scaling Outlooks on Integrated Energy Systems

The report provides research summaries of two developed theories: data projection to enable multi-scale facility digital interactions and introducing the Evaluation Model Development and Assessment Process (EMDAP) approach to Integrated Energy Systems (IES) design. For the data projection, a two-system scaling case including interactions between thermal storage and hydrogen production is provided. The corresponding facilities are the thermal energy distribution system (TEDS) facility and high temperature steam electrolysis (HTSE) facility at the Dynamic Energy Transport and Integration Laboratory (DETAIL) in Idaho National Laboratory (INL). For the EMDAP adaption to system design, a modified process of the EMDAP was developed and applied to indirect two-tank heat storage system design. System phenomena were identified, ranked, and scaled to discover helpful key relations that would determine the ideal component geometry.

08 HYDROGEN↗
DOE OSTI2023

ASC Data Science Infrastructure Project June 2023 [Slides]

Data Science Infrastructure (DSI) Project offers a standardized but flexible way of storing data and associated metadata to support AI/ML and data intensive scientific workflows: Establish requirements via use case interviews; Develop DSI framework to support flexible, secure, and accessible data stores tailored to researcher needs; Augment existing institutional frameworks for code management, performance testing and file indexing via automated DSI interfaces; Deploy DSI framework to support key use cases in collaboration with domain scientists.

97 MATHEMATICS AND COMPUTING↗