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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics

The scientific community is currently experiencing unprecedented amounts of data generated by cutting-edge science facilities. Soon facilities will be producing up to 1 PB/s which will force scientist to use more autonomous techniques to learn from the data. The adoption of machine learning methods, like deep learning techniques, in large-scale workflows comes with a shift in the workflow’s computational and I/O patterns. These changes often include iterative processes and model architecture searches, in which datasets are analyzed multiple times in different formats with different model configurations in order to find accurate, reliable and efficient learning models. This shift in behavior brings changes in I/O patterns at the application level as well at the system level. These changes also bring new challenges for the HPC I/O teams, since these patterns contain more complex I/O workloads. In this paper we discuss the I/O patterns experienced by emerging analytical codes that rely on machine learning algorithms and highlight the challenges in designing efficient I/O transfers for such workflows. We comment on how to leverage the data access patterns in order to fetch in a more efficient way the required input data in the format and order given by the needs of the application and how to optimize the data path between collaborative processes. We will motivate our work and show performance gains with a study case of medical applications.

Gainaru, Ana↗
DOE OSTI2022

EXFOR-NSR PDF database: a system for nuclear knowledge preservation and data curation

Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Additionally, experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications. The Web interfaces for authorized and public access to the EXFOR-NSR nuclear publications database were implemented at the U.S. National Nuclear Data Center, https://www.nndc.bnl.gov/ and IAEA Nuclear Data Section, https://www-nds.iaea.org/ . The current system is complementary to major nuclear libraries and narrowly focused on nuclear data compilation and evaluation procedures. The contents of the PDF database, details of implementation, and Web interface are described. New capabilities for data curation, knowledge preservation, worldwide dissemination, and natural language processing (NLP) applications are given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Digital holography for real-time non-invasive monitoring of larval fish at power plant intakes

Effective evaluation of technological and operational approaches to reduce entrainment of marine organisms at cooling water intake structures (CWIS) requires accurate organism-sensing systems. Current detection methods lead to large temporal data gaps, require tedious manual analysis, and are fatal to organisms. In this report we describe integrating deep learning with a non-lethal, non-intrusive imaging method—digital holography—to rapidly detect fish larvae. Laboratory experiments demonstrated that the instrument could successfully image fish larvae at flow rates exceeding ranges seen in CWIS. Holograms of two fish larvae species, in the presence of bubbles and detritus, were collected to build a large database for training a lightweight convolutional neural network. The model achieves 97% extraction accuracy in quantifying larvae, and distinguishing them from other particles, including detritus and bubbles, when applied to a dataset of manually classified images, exceeding previous metrics for non-lethal, accurate, and real-time detection. These results demonstrate the potential of in situ holographic imaging for monitoring endangered larval fish species at power plant intake structures, and for high-fidelity, real-time applications in monitoring aquatic ichthyoplankton.

endangered species↗
DOE OSTI2024

Developing a Database of Bio-based Materials for Building Envelope Applications

Oak Ridge National Laboratory (ORNL) has been funded by the Department of Energy (DOE) to help accelerate the introduction of building envelope materials that would reduce the carbon footprint of the buildings sector. The DOE’s Building Technologies Office has historically sought to resolve the knowledge gaps regarding the energy efficiency and moisture durability of building envelope systems and to develop the data, guidance, and tools needed to facilitate rapid industry adoption of high-performance, moisture-managed envelope systems. This project will help accelerate the widespread acceptance of a new generation of building materials developed specifically with the intent of reducing the carbon footprint of buildings. We have produced a database of hygrothermal transport properties on low embodied carbon building materials that can be added to energy and durability simulation tools. Properties that were measured include density, heat capacity, thermal conductivity as a function of temperature and relative humidity, moisture dependent permeance, and sorption isotherms as a function of relative humidity. These data sets were measured following consensus national standards using state-of-the-art facilities. The data has been compiled and is being made available to building designers who require these data to assess these new materials in their designs. We will publish the data and seek its addition to reference databases such as the ASHRAE Handbook of Fundamentals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

CO2 laser communication systems for near-earth space applications

Projections of the growth of earth-sensing systems for the latter half of the 1980's show a data-transmission requirement of 300 Mbit/s and above. The most efficient technique to return the data from a sensing satellite to a ground station is through a geosynchronous data relay satellite. A laser system is most attractive for the space-to-space link. A five-year program was conducted which has shown the basic technical feasibility of accomplishing this link with a CO2 laser system operating at a wavelength near 10 microns. The system uses a mercury-cadmium-telluride infrared mixer cooled to approximately 100 K by a radiative cooler. The laser local oscillator and coupling-modulated laser transmitter use conductively cooled beryllium oxide construction. The optical antenna for transmission and reception has a gain of nominally 92 dB with a 3-dB beamwidth of 80 microrad. Tracking jitter is less than ten microrad, and signal acquisition occurs in less than 1 min. The receiver subsystem has a sensitivity of 10 to the -19th power W/Hz, accommodates a 300-Mbit/s data rate, and can track Doppler frequency variations over a + or - 700-MHz range.

Mcelroy, J. H.↗
NASA NTRS1980

Stereosat - A global digital stereo imaging mission

The objectives of the Stereosat mission are to obtain worldwide cloud-free stereo coverage at two base-height ratios and with a ground IFOV of 15 m; and to obtain stereo data in digital form that can be merged with monoscopic digital terrain models derived directly from the image data stream. This paper reviews Stereosat, with consideration given to the geological mapping requirements, digital data bases, the mission concept, system lifetime, instrument parameters, spacecraft parameters, and geometric accuracy.

Goetz, A. F. H.↗
NASA NTRS1992

A comparison of LOWTRAN-7 corrected Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data with ground spectral measurements

Atmospheric correction of imaging spectroscopy data is required for quantitative analysis. Different models were proposed for atmospheric correction of these data. LOWTRAN-7 is a low-resolution model and computer code for predicting atmospheric transmittance and background radiance from 0 to 50,00 cm(sup -1) which was developed by the Air Force Geophysics Laboratory. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data used are radiometrically calibrated and include the 28 Sep. 1989 Providence Fan flight line segment 07, California. It includes a dark gravel surface defined as a calibration site by the Geologic Remote Sensing Field Experiment (GRSFE). Several ground measurements of portable spectrometer DAEDALUS AA440 Spectrafax were taken during the GRSFE, July 1989 field campaign. Comparisons of the LOWTRAN-7 corrected AVIRIS data with the ground spectrometer measurement were made.

Xu, Peng-Yang↗
NASA NTRS1999

Basic Hitchhiker Payload Requirements

This document lists the requirements for the NMSU Hitchhiker experiment payload that were developed as part of the EE 498/499 Capstone Design class during the 1999-2000 academic year. This document is used to describe the system needs as described in the mission document. The requirements listed here are those primarily used to generate the basic electronic and data processing requirements developed in the class design document. The needs of the experiment components are more fully described in the draft NASA hitchhiker customer requirements document. Many of the details for the overall payload are given in full detail in the NASA hitchhiker documentation.

Horan, Stephen↗
DOE OSTI2021

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure formation are used to generate a large synthetic dataset of line-of-sight absorption spectra paired with 1-dimensional fluid quantities along the same line-of-sight, such as the total density of matter and the density of neutral atomic hydrogen. With this dataset, we build a series of data-driven models to predict the power spectrum of total matter density. We are able to produce models which yield reconstruction to accuracy of about 1% for wavelengths $k \leq 2 h Mpc^{-1}$, while the error increases at larger $k$. We show the size of data sample required to reach a particular error rate, giving a sense of how much data is necessary to reach a desired accuracy. This work provides a foundation for developing methods to analyse very large upcoming datasets with the next-generation observational facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Lunar lander stage requirements based on the Civil Needs Data Base

This paper examines the lunar lander stages that will be necessary for the future exploration and development of the Moon. Lunar lander stage sizing is discussed based on the projected lunar payloads listed in the Civil Needs Data Base. Factors that will influence the lander stage design are identified and discussed. Some of these factors are (1) lunar orbiting and lunar surface lander bases; (2) implications of direct landing trajectories and landing from a parking orbit; (3) implications of landing site and parking orbit; (4) implications of landing site and parking orbit selection; (5) the use of expendable and reusable lander stages; and (6) the descent/ascent trajectories. Data relating the lunar lander stage design requirements to each of the above factors and others are presented in parametric form. These data will provide useful design data that will be applicable to future mission model modifications and design studies.

Mulqueen, John A.↗
NASA NTRS1976

Space shuttle engineering and operations support. Avionics system engineering

The shuttle avionics integration laboratory (SAIL) requirements for supporting the Spacelab/orbiter avionics verification process are defined. The principal topics are a Spacelab avionics hardware assessment, test operations center/electronic systems test laboratory (TOC/ESL) data processing requirements definition, SAIL (Building 16) payload accommodations study, and projected funding and test scheduling. Because of the complex nature of the Spacelab/orbiter computer systems, the PCM data link, and the high rate digital data system hardware/software relationships, early avionics interface verification is required. The SAIL is a prime candidate test location to accomplish this early avionics verification.

Broome, P. A.↗
NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗
NASA NTRS1976

Investigation of a Real-time Processing System for the NASA Multifrequency Microwave Radiometer

A study was conducted to investigate the data reduction and processing requirements for the multifrequency microwave radiometer system (MFMR). The objectives were to develop and evaluate algorithms and processing techniques which might provide for dedicated real time or near real time data processing and to develop a configuration design and processor recommendation to accomplish the data reduction. An analysis of the required data reduction and calibration equations was included along with the identification of sources of error which may be present in the (MFMR) data. The definition and evaluation of the significance of effects introduced by aircraft perturbation was given.

Source record↗
NASA NTRS2006

Paradigm Shift in Data Content and Informatics Infrastructure Required for Generalized Constitutive Modeling of Materials Behavior

Materials property information such as composition and thermophysical/mechanical properties abound in the literature. Oftentimes, however, the corresponding response curves from which these data are determined are missing or at the very least difficult to retrieve. Further, the paradigm for collecting materials property information has historically centered on (1) properties for materials comparison/selection purposes and (2) input requirements for conventional design/analysis methods. However, just as not all materials are alike or equal, neither are all constitutive models (and thus design/ analysis methods) equal; each model typically has its own specific and often unique required materials parameters, some directly measurable and others indirectly measurable. Therefore, the type and extent of materials information routinely collected is not always sufficient to meet the current, much less future, needs of the materials modeling community. Informatics has been defined as the science concerned with gathering, manipulating, storing, retrieving, and classifying recorded information. A key aspect of informatics is its focus on understanding problems and applying information technology as needed to address those problems. The primary objective of this article is to highlight the need for a paradigm shift in materials data collection, analysis, and dissemination so as to maximize the impact on both practitioners and researchers. Our hope is to identify and articulate what constitutes "sufficient" data content (i.e., quality and quantity) for developing, characterizing, and validating sophisticated nonlinear time- and history-dependent (hereditary) constitutive models. Likewise, the informatics infrastructure required for handling the potentially massive amounts of materials data will be discussed.

Arnold, S. M.↗
NASA NTRS1992

CEOS Committee on Earth Observations Satellites Consolidated Report, 1992

A concise overview of the committee on Earth Observations Satellites (CEOS) and its Working Groups, covering the history and purpose of the Committee and its accomplishments to date are provided. The report will be updated annually before each Plenary meeting, and as developments in the Working Groups warrant. The committee on Earth Observations Satellites (originally named the International Earth Observations Satellite committee, IEOS) was treated in 1984, in response to a recommendation from the Economic Summit of Industrialized Nations Working Group on Growth, Technology, and Employment's Panel of Experts on Satellite Remote Sensing. This group recognized the multidisciplinary nature of satellite Earth observations, and the value of coordinating across all proposed missions. Thus, CEOS combined the previously existing groups for coordination on Ocean Remote-Sensing Satellites (CORSS) and coordination on Land Remote-Sensing Satellites (CLRSS), and established a broad framework for coordination across all spaceborne Earth observations missions. The first three LEOS Plenary meetings focused on treating and guiding the Working Groups deemed necessary to carry out the objectives of the CEOS members. After the third meeting, it was agreed that a more active orientation was required by the Plenary, and additional issues were brought before the group at the fourth meeting. At the fifth Plenary, international scientific programs and relevant intergovernmental organizations accepted invitations and participated as affiliate members of CEOS. This enabled progress toward integrating satellite data users' requirements into the CEOS process. Data exchange principles for global change research were also adopted. An interim CEOS Plenary meeting was held in April 1992, in preparation for the United Nations Conference on Environment and Development (UNCED). Brief encapsulations of the Plenary sessions immediately follow the Terms of Reference that govern the activities of CEOS as a whole; Terms of Reference for the individual Working Groups are included as Appendix A. A complete listing of CEOS members is offered as Appendix B.

Source record↗
DOE OSTI2023

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗
NASA NTRS1988

Loads and low frequency dynamics - An ENVIRONET data base

The loads and low frequency dynamics data base, part of Environet, is described with particular attention given to its development and contents. The objective of the data base is to provide the payload designer with design approaches and design data to meet STS safety requirements. Currently the data base consists of the following sections: abstract, scope, glossary, requirements, interaction with other environments, summary of the loads analysis process, design considerations, guidelines for payload design loads, information data base, and references.

Garba, John A.↗
DOE OSTI2022

Machine Learning Modeling for Accelerated Battery Materials Design in the Small Data Regime

Abstract Machine learning (ML)‐based approaches to battery design are relatively new but demonstrate significant promise for accelerating the timeline for new materials discovery, process optimization, and cell lifetime prediction. Battery modeling represents an interesting and unconventional application area for ML, as datasets are often small but some degree of physical understanding of the underlying processes may exist. This review article provides discussion and analysis of several important and increasingly common questions: how ML‐based battery modeling works, how much data are required, how to judge model performance, and recommendations for building models in the small data regime. This article begins with an introduction to ML in general, highlighting several important concepts for small data applications. Previous ionic conductivity modeling efforts are discussed in depth as a case study to illustrate these modeling concepts. Finally, an overview of modeling efforts in major areas of battery design is provided and several areas for promising future efforts are identified, within the context of typical small data constraints.

Sendek, Austin D.↗