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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

An image compression survey and algorithm switching based on scene activity

Data compression techniques are presented. A description of these techniques is provided along with a performance evaluation. The complexity of the hardware resulting from their implementation is also addressed. The compression effect on channel distortion and the applicability of these algorithms to real-time processing are presented. Also included is a proposed new direction for an adaptive compression technique for real-time processing.

Hart, M. M.↗
DOE OSTI2022

High Flux Isotope Reactor Neutron Spectrum Shape Estimation From Activation Experiment Data

Here, this article provides a comprehensive review of historical irradiation dosimetry available for different locations within the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). This article includes a summary of the available measured activation target data covering a span of over 15 years and 39 experimental campaigns, including 200 individual sample locations evaluated. Using this broad set of data, we reconstruct historic average neutron spectra shapes for HFIR at various locations, including within the flux trap region, beryllium reflectors, and hydraulic tube (HT) regions, at both the 100- and 85-MW operational power. Our findings indicate that the general axial flux distribution shows a relatively small change in transition from 100- to 85-MW operating power, with differences of -6% to +15% for the thermal energy range and around -16% to +8% for the fast range, indicating a sharper drop-off of the thermal neutron flux away from the axial center. Compared with historical dosimetry estimates of the HFIR flux shape, we generally find a moderately broader axial profile shape for thermal neutrons in the interior target regions for the 100-MW samples evaluated but relatively close agreement for the present 85-MW flux shape for both thermal and fast fluxes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1971

Correlation of irradiation data using activation fluences and irradiation temperature.

Nil-ductility transition temperature data for A302-B ferritic steel were analyzed by using multiple regression. Four independent variables were used - i.e., specimen temperature during irradiation, and time-integrated specific activations (activation fluences) of fast-, intermediate-, and thermal-neutron detectors. The results of these analyses were predictive equations having the increase in transition temperature as the dependent variable. For a reference point, a similar analysis was also performed using the flux integral above 1 MeV and the irradiation temperature as independent variables. Also, the effect of excluding irradiation temperature from these analyses was studied. The results of the analyses showed that excellent correlation was achieved by using activation fluences and irradiation temperature as the independent variables. Irradiation temperature was found to account for from 29 to 46% of the data variability depending on the model used.

Lynch, J. H.↗
DOE OSTI2025

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then, the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we demonstrate an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially benchmark in electrocatalysts research.

Science & Technology - Other Topics↗
NASA NTRS1972

Correlation of irradiation data using activation fluences and irradiation temperature.

A new method of correlating radiation damage data is tested using actual measured data taken from the open literature. This method, the activation fluence method, was found to be as accurate as other contemporary models with which it was compared. The new method also has several advantages over the other methods. The method employs a new entity, the activation fluence (time-integrated specific activation rate), as the independent variables in a regression model. Temperature at which the irradiation takes place is also a variable. Although the method was tested for a specific type of damage (change in nil-ductility transition temperature for A302-B steel) it has no inherent restrictions and is limited only by the imagination of the user.

Lynch, J. H.↗
DOE OSTI2022

DIAS: A Data-Informed Active Subspace Regularization Framework for Inverse Problems

This paper presents a regularization framework that aims to improve the fidelity of Tikhonov inverse solutions. At the heart of the framework is the data-informed regularization idea that only data-uninformed parameters need to be regularized, while the data-informed parameters, on which data and forward model are integrated, should remain untouched. We propose to employ the active subspace method to determine the data-informativeness of a parameter. The resulting framework is thus called a data-informed (DI) active subspace (DIAS) regularization. Four proposed DIAS variants are rigorously analyzed, shown to be robust with the regularization parameter and capable of avoiding polluting solution features informed by the data. They are thus well suited for problems with small or reasonably small noise corruptions in the data. Furthermore, the DIAS approaches can effectively reuse any Tikhonov regularization codes/libraries. Though they are readily applicable for nonlinear inverse problems, we focus on linear problems in this paper in order to gain insights into the framework. Various numerical results for linear inverse problems are presented to verify theoretical findings and to demonstrate advantages of the DIAS framework over the Tikhonov, truncated SVD, and the TSVD-based DI approaches.

Nguyen, Hai↗
NASA NTRS2023

Reports From EXPORTS Modeling and Data-Mining Activities

EXPORTS -EXport Processes in the Ocean from RemoTe Sensing is NASA’s large field campaign focusing on development of a predictive understanding of the export, fate and carbon cycle impacts of the global net primary production. This co-funded program (NSF, private funding1, and international participation) was conceived in 2013, with EXPORTS Science plan published in 2016 (Siegel et al 2016, EXPORTS Writing Team 2015) and its implementation plan finalized in 2016 (EXPORTS Science Definition Team 2016). More details are presented in Siegel et al (2021). EXPORTS campaign is structured as a multiyear effort (Figure 1). It started with “Pre-EXPORTS” modeling and data-mining activity followed by a first phase with two major field programs and a second synthesis and modeling phase. The “Pre-EXPORTS” projects, total of 6 of them (Table 1), funded under A.3 Ocean Biology and Biogeochemistry 2015 call, helped to plan the field campaign (Resplandy et al 2019, Rousseaux & Gregg 2017), and supporting further global synthesis with datasets mined from the literature (e.g. Bisson et al (2020), Bisson et al (2018), Kramer and Siegel (2019)), directly responding to objectives outlined in Science Plan (see section 6 in Team (2015)) and Implementation team (see Figure 1 in Team (2016)). This document presents a compilation of the final reports of the Pre-EXPORTS funded projects, in hope of synthesizing the outcomes, and insuring the legacy of this program. Each of these reports contains a list of published papers, and reader should refer to them to see results in details.

Brandi J. McCarty↗
DOE OSTI2020

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Evaluating Bay Area Methane Emission Inventory

As a regulatory agency, evaluating and improving estimates of methane (CH4) emissions from the San Francisco Bay Area is an area of interest to the Bay Area Air Quality Management District (BAAQMD). Currently, regional, state, and federal agencies generally estimate methane emissions using bottom-up inventory methods that rely on a combination of activity data, emission factors, biogeochemical models and other information. Recent atmospheric top-down measurement estimates of methane emissions for the US as a whole (e.g., Miller et al., 2013) and in California (e.g., Jeong et al., 2013; Peischl et al., 2013) have shown inventories underestimate total methane emissions by ~ 50% in many areas of California, including the SF Bay Area (Fairley and Fischer, 2015). The goal of this research is to provide information to help improve methane emission estimates for the San Francisco Bay Area. The research effort builds upon our previous work that produced methane emission maps for each of the major source sectors as part of the California Greenhouse Gas Emissions Measurement (CALGEM) project (http://calgem.lbl.gov/prior_emission.html; Jeong et al., 2012; Jeong et al., 2013; Jeong et al., 2014). Working with BAAQMD, we evaluate the existing inventory in light of recently published literature and revise the CALGEM CH4 emission maps to provide better specificity for BAAQMD. We also suggest further research that will improve emission estimates. To accomplish the goals, we reviewed the current BAAQMD inventory, and compared its method with those from the state inventory from the California Air Resources Board (CARB), the CALGEM inventory, and recent published literature. We also updated activity data (e.g., livestock statistics) to reflect recent changes and to better represent spatial information. Then, we produced spatially explicit CH4 emission estimates on the 1-km modeling grid used by BAAQMD. We present the detailed activity data, methods and derived emission maps by sector. In total, we estimate the anthropogenic emissions for BAAQMD to be 116.4 Gg (1 Gg = 109 g) CH4/yr, with a likely uncertainty of ~ 50% or more (e.g., NRC, 2010; US-EPA, 2015). Including the emissions from wetland (Jeong et al., 2013), the total CH4 emission estimate for BAAQMD is 120.1 Gg CH4/yr. Table 1 summarizes the estimated CH4 emissions for 2011 by sector. The sectors were categorized following those that are used in recent regional emission quantification studies (e.g., Jeong et al., 2013; Peischl et al., 2013; Wecht et al., 2014). However, we note that this result is marginally lower than the top-down estimate of 240 ± 60 Gg CH4/yr (at 95% confidence) reported by Fairley and Fischer (2015), suggesting some combination of systematic error in the top-down estimate, underestimation of emissions from known sources, or as yet unidentified sources may be present. With respect to the relative contributions from different source sectors, the CH4 emissions from the region are dominated by urban activities. Landfill emissions represent 53% of the District’s total emission followed by livestock (16%) and natural gas (15%). These three dominant sectors account for 84% of the total anthropogenic emission in BAAQMD. This suggests that mitigation efforts need to focus on these three sources. Figure 1 shows the gridded anthropogenic CH4 emissions on the BAAQMD’s 1-km grid. In general, the spatial pattern of emissions follows the density of population while strong point sources are also distributed in the rural areas of the District. Detailed methods and emissions for each sector and county are described in the following sections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Brady's Geothermal Field Nodal Seismometer Active Source Data Sample

This data is in sac format and includes recordings of two active source events from 238 three-component nodal seismometers deployed at Bradys Hot Springs geothermal field as part of the PoroTomo project. The source was a viberoseis truck operating in P-wave vibrational mode and generating a swept-frequency signal. The files are 33 seconds long starting 4 seconds before each sweep was initiated. There is some overlap in the file times.

15 GEOTHERMAL ENERGY↗
NASA NTRS1976

Formulation of detailed consumables management models for the development (preoperational) period of advanced space transportation system. Volume 2: Consumables data base workbook

The consumables characteristic data associated with the performance of the mission activities required by the mission planning processor are defined to calculate the consumables requirements. The activity data is defined in terms of discrete time periods having a distinct rate for each consumable required to support the performance of a given operation. The data is structured in a series of consumable data worksheets for each activity that includes a profile of its operations and the rate of each consumable required to support the given activity. The data worksheets provide for the uniform specification of consumables data, allows for the ready identification of the consumables affected by a given activity, and facilitates the updating process. An activity and the data that must be included in the data worksheets are defined and an example of its use and application the consumables data requirements for the performance of the EVA are presented.

Zamora, M. A.↗
NASA NTRS1983

Data base management systems activities

The Data Management System-1100 is designed to operate in conjunction with the UNIVAC 1100 Series Operating System on any 1100 Series computer. DMS-1100 is divided into the following four major software components: (1) Data Definition Languages (DDL); (2) Data Management Routine (DMR); (3) Data Manipulation Languages (DML); and (4) Data Base Utilities (DBU). These software components are described in detail.

Source record↗
DOE OSTI2018

Partnership For Edge Physics Simulation

In this effort, we will extend our prior work as part of CPES (i.e., DART and DataSpaces) to support in-situ tight coupling between application codes that exploits data locality and core-level parallelism to maximize on-chip data exchange and reuse. This will be accomplished by mapping coupled simulations so that the data exchanges are more localized within the nodes. Coupled simulation workflows can more effectively utilize the resources available on emerging HEC platforms if they can be mapped and executed to exploit data locality as well as the communication patterns between application components. Scheduling and running such workflows requires an extended framework that should provide a unified hybrid abstraction to enable coordination and data sharing across computation tasks that run on the heterogeneous multi-core-based systems, and develop a data-locality based dynamic tasks scheduling approach to increase on-chip or intra-node data exchanges and in-situ execution. This effort will extend our prior work as part of CPES (i.e., DART and DataSpaces), which provided a simple virtual shared-space abstraction hosted at the staging nodes, to support application coordination, data sharing and active data processing services. Moreover, it will transparently manage the low-level operations associated with the inter-application data exchange, such as data redistributions, and will enable running coupled simulation workflow on multi-cores computing platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

A flight test facility design for examining digital information transfer

Information is given in viewgraph form on a flight test facility design for examining digital information transfer. Information is given on aircraft/ground exchange, data link research activities, data link display format, a data link flight test, and the flight test setup.

Knox, Charles E.↗
DOE OSTI2024

Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the above-mentioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

54 ENVIRONMENTAL SCIENCES↗