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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Generating Ground Reference Data for a Global Impervious Surface Survey

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Tilton, James C.↗
DOE OSTI2021

A VR-based volumetric medical image segmentation and visualization system with natural human interaction

Volume rendering produces informative two-dimensional (2D) images from a 3-dimensional (3D) volume. It highlights the region of interest and facilitates a good comprehension of the entire data set. However, volume rendering faces a few challenges. First, a high-dimensional transfer function is usually required to differentiate the target from its neighboring objects with subtle variance. Unfortunately, designing such a transfer function is a strenuously trial-and-error process. Second, manipulating/visualizing a 3D volume with a traditional 2D input/output device suffers dimensional limitations. To address all the challenges, we design NUI-VR 2 , a natural user interface-enabled volume rendering system in the virtual reality space. NUI-VR 2 marries volume rendering and interactive image segmentation. It transforms the original volume into a probability map with image segmentation. A simple linear transfer function will highlight the target well in the probability map. More importantly, we set the entire image segmentation and volume rendering pipeline in an immersive virtual reality environment with a natural user interface. NUI-VR 2 eliminates the dimensional limitations in manipulating and perceiving 3D volumes and dramatically improves the user experience.

42 ENGINEERING↗
DOE OSTI2025

Structure-guided utilization of lignocellulose for catalysis, energy, and biomaterials

As a complex composite of cellulose, hemicellulose, and lignin, plant lignocellulose has long served as a major resource for biomass conversion, materials engineering, and bio-based product development. High-resolution structural insights enabled by solid-state nuclear magnetic resonance (ssNMR) now allow the mapping of polymer interfaces, identification of functional group accessibility, and tracking of molecular organization during processing, all of which are critical factors for optimizing catalytic strategies. These insights could drive transformative progress in lignocellulose-based applications, including selective depolymerization, improved pretreatment design, and efficient upcycling of lignin into resins, plastics, and biomedical materials. In industry-relevant contexts, such as biofuel generation and renewable material manufacturing, understanding the hydration dynamics, cross-linking patterns, and structural heterogeneity is also essential. The ability to visualize these features in native biomass presents a unique opportunity to develop new strategies for sustainability and performance. As the structural toolbox continues to expand, it is becoming a central enabler for innovations in renewable energy, green chemistry, and advanced bioproducts.

bioproduct↗
DOE OSTI2021

Magnetohydrodynamic Control of Interfacial Degradation in Lithium-Ion Batteries for Fast Charging Applications

Interfacial anodic degradation in graphitic materials under fast charging conditions causes severe performance loss and safety hazard in lithium ion batteries. We present a novel method for minimizing the growth of these aging mechanism by application of an external magnetic field. Under magnetic field, paramagnetic lithium ions experience a magnetohydrodynamic force, which rotates the perpendicularly diffusing species and homogenizes the ionic transport. This phenomenon minimizes the overpotential hotspots at the anode/separator interface, consequently reducing SEI growth, lithium plating, and interfacial fracture. In situ electrochemical measurements indicate an improvement in capacity for lithium cobalt oxide/graphite pouch cell (20 mAh) charged from 1–5 C under an applied field of 1.8 kG, with a maximum capacity gain of 22% at 5C. Post-mortem FE-SEM and EDS mapping shows that samples charged with magnetic field have a reduced lithium deposition at 3C and a complete suppression of interfacial fracture at 5C. At 5C, a 24% reduction in the lithium content is observed by performing XPS on the anodic interfacial film. Finally, fast charging performance under variable magnetic field strengths indicate a saturation behavior in capacity at high fields (>2 kG), thereby limiting the field and consequent energy requirements to obtain maximum capacity gain under extreme conditions.

electromagnetism↗
DOE OSTI2026

A path to intelligent watersheds: coordinating the data to decision pipeline

Operations of multi-reservoir systems are challenged in-part by the interplay of complex physical processes functioning within the watershed. The employment of intelligent systems can be of aid by linking environmental sensing, information technology, data analytics, simulation and decision support to achieve a data-to-decision flow of information. A further challenge is that watershed resources are managed for multiple purposes requiring some level of coordination among numerous resource managers, asset operators and users. System intelligence in this context relies on shared community platforms (data portals, community models), and coordinated communication between decision makers. Opportunities to enrich watershed intelligence has been the subject of a roadmapping exercise for the Department of Energy’s Water Power Technologies Office which has relied on broad stakeholder engagement. Initial phases of engagement involved personal interviews and a series of virtual group meetings, which focused on identifying opportunities to improve the intelligence of the physical infrastructure within our watersheds—examples of feedback include improved sensing of snowpack and runoff, data standards for facilitated data sharing, and better forecasting tools. The latter phase of engagement involved the conduct of a case study in the Upper Colorado River basin where key stakeholders were interviewed to map how their decisions are informed by intelligence from other basin stakeholders. Our presentation will highlight the interdisciplinary flow of information in complex watershed systems and identify physical and institutional opportunities toward the strategic operation of water infrastructure.

Colorado River↗
DOE OSTI2022

Non-Gaussianity constraints with anisotropic μ distortion measurements from Planck

ABSTRACT Primordial non-Gaussianity can source μ-distortion anisotropies that are correlated with the large-scale temperature and polarization signals of the cosmic microwave background (CMB). A measurement of μT and μE correlations can therefore be used to constrain it on wavelengths of perturbations not directly probed by the standard CMB anisotropies. We carry out a first rigorous search for μ-distortion anisotropies with Planck data, applying the well-tested constrained ILC component-separation method combined with the needlet framework. We correlate the reconstructed μ map with the CMB anisotropies to derive constraints on the amplitude fNL of the local form bispectrum, specifically on the squeezed configurations with effective wavenumbers $k_s \simeq {740}\, \mathrm{Mpc^{-1}}$ and $k_L \simeq {0.05}\, \mathrm{Mpc^{-1}}$, improving previously estimated constraints by more than an order of magnitude. This enhancement is owing to the fact that we are able to use the full multipole information by carefully controlling biases and systematic effects in the analysis. We also for the first time incorporate constraints from measurements of μE correlations, which further tighten the limits. A combination of the derived Planck μT and μE power spectra yields |fNL| ≲ 6800 (95 per cent c.l.) on this highly squeezed bispectrum. This is only ≃3 times weaker than the anticipated constraint from Litebird. Furthermore we show that a combination of Litebird with Planck can improve the expected future constraint by ${\simeq}20{{\%}}$. These limits can be used to constrain multifield inflation models and primordial black hole formation scenarios, thus providing a promising novel avenue forward in CMB cosmology.

Rotti, Aditya (ORCID:0000000341245226)↗
DOE OSTI2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The spatial and temporal evolution of the Portland and Tualatin forearc basins, Oregon, USA

The Portland and Tualatin basins are part of the Salish-Puget-Willamette Lowland, a 900-km-long, forearc depression lying between the volcanic arc and the Coast Ranges of the Cascadia convergent margin. Such inland seaways are characteristic of warm, young slab subduction. We analyzed the basins to better understand their evolution and relation to Coast Range history and to provide an improved tectonic framework for the Portland metropolitan area. We model three key horizons in the basins: (1) the top of the Columbia River Basalt Group (CRBG), (2) the bottom of the CRBG, and (3) the top of Eocene basement. Isochore maps constrain basin depocenters during (1) Pleistocene to mid-Miocene time (0–15 Ma), (2) CRBG (15.5–16.5 Ma), and (3) early Miocene to late Eocene (ca. 17–35 Ma) time. Results show that the Portland and Tualatin basins have distinct mid-Miocene to Quaternary depocenters but were one continuous basin from the Eocene until mid-Miocene time. A NW-striking gravity low coincident with the NW-striking, fault-bounded Portland Hills anticline is interpreted as an older graben coincident with observed thickening of CRBG flows and underlying sedimentary rocks. Neogene transpression in the forearc structurally inverted the Sylvan-Oatfield and Portland Hills normal faults as high-angle dextral-reverse faults, separating the Portland and Tualatin basins. An eastward shift of the forearc basin depocenter and ten-fold decrease in accommodation space provide temporal constraints on the emergence of the Coast Range to the west. Clockwise rotation and northward transport of the forearc is deforming the basins and producing local earthquakes beneath the metropolitan area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Efficient sampling of constrained high-dimensional theoretical spaces with machine learning

Abstract Models of physics beyond the Standard Model often contain a large number of parameters. These form a high-dimensional space that is computationally intractable to fully explore. Experimental results project onto a subspace of parameters that are consistent with those observations, but mapping these constraints to the underlying parameters is also typically intractable. Instead, physicists often resort to scanning small subsets of the full parameter space and testing for experimental consistency. We propose an alternative approach that uses generative models to significantly improve the computational efficiency of sampling high-dimensional parameter spaces. To demonstrate this, we sample the constrained and phenomenological Minimal Supersymmetric Standard Models subject to the requirement that the sampled points are consistent with the measured Higgs boson mass. Our method achieves orders of magnitude improvements in sampling efficiency compared to a brute force search.

Hollingsworth, Jacob↗
DOE OSTI2022

Progress in Modeling the 2019 Extended Magnetically Insulated Transmission Line (MITL) and Courtyard Environment Trial at HERMES-III

This report documents the progress made in simulating the HERMES-III Magnetically Insulated Transmission Line (MITL) and courtyard with EMPIRE and ITS. This study focuses on the shots that were taken during the months of June and July of 2019 performed with the new MITL extension. There were a few shots where there was dose mapping of the courtyard, 11132, 11133, 11134, 11135, 11136, and 11146. This report focuses on these shots because there was full data return from the MITL electrical diagnostics and the radiation dose sensors in the courtyard. The comparison starts with improving the processing of the incoming voltage into the EMPIRE simulation from the experiment. The currents are then compared at several location along the MITL. The simulation results of the electrons impacting the anode are shown. The electron impact energy and angle is then handed off to ITS which calculates the dose on the faceplate and locations in the courtyard and they are compared to experimental measurements. ITS also calculates the photons and electrons that are injected into the courtyard, these quantities are then used by EMPIRE to calculated the photon and electron transport in the courtyard. The details for the algorithms used to perform the courtyard simulations are presented as well as qualitative comparisons of the electric field, magnetic field, and the conductivity in the courtyard. Because of the computational burden of these calculations the pressure was reduce in the courtyard to reduce the computational load. The computation performance is presented along with suggestion on how to improve both the computational performance as well as the algorithmic performance. Some of the algorithmic changed would reduce the accuracy of the models and detail comparison of these changes are left for a future study. As well as, list of code improvements there is also a list of suggested experimental improvements to improve the quality of the data return.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Progress Towards NQA-1 for Cardinal in FY25

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing,and maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program was initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as an analysis tool. These gaps were captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents the progress made towards NQA-1 for Cardinal in the Fiscal Year 2025 (FY25). All cases in the expanded Continuous Integration (CI) suite of NekRS are included in this report which test the solvers and modules available in NekRS exhaustively. The NekRS tests are integrated with the Cardinal CI suite and made available in publicly accessible Github documentation. Following the CI practice permits integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. Also in this report is a brief overview of the development of the Cardinal Software Quality Assurance Plan (SQAP) that was done in FY25, though it should be noted that the rest of the documentation for the SQA program needs to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1983

Stress studies in EFG

Experimental work in support of stress studies in high speed silicon sheet growth has been emphasized in this quarter. Creep experiments utilizing four-point bending have been made in the temperature range from 1000 C to 1360 C in CZ silicon as well as on EFG ribbon. A method to measure residual stress over large areas using laser interferometry to map strain distributions under load is under development. A fiber optics sensor to measure ribbon temperature profiles has been constructed and is being tested in a ribbon growth furnace environment. Stress and temperature field modeling work has been directed toward improving various aspects of the finite element computing schemes. Difficulties in computing stress distributions with a very high creep intensity and with non-zero interface stress have been encountered and additional development of the numerical schemes to cope with these problems is required. Temperature field modeling has been extended to include the study of heat transfer effects in the die and meniscus regions.

Source record↗
NASA NTRS1984

Passive microwave remote sensing for sea ice research

Techniques for gathering data by remote sensors on satellites utilized for sea ice research are summarized. Measurement of brightness temperatures by a passive microwave imager converted to maps of total sea ice concentration and to the areal fractions covered by first year and multiyear ice are described. Several ancillary observations, especially by means of automatic data buoys and submarines equipped with upward looking sonars, are needed to improve the validation and interpretation of satellite data. The design and performance characteristics of the Navy's Special Sensor Microwave Imager, expected to be in orbit in late 1985, are described. It is recommended that data from that instrument be processed to a form suitable for research applications and archived in a readily accessible form. The sea ice data products required for research purposes are described and recommendations for their archival and distribution to the scientific community are presented.

Source record↗
NASA NTRS1985

Characterization of LANDSAT-4 TM and MSS Image Quality for the Interpretation of California's Agricultural Resources

The quality of LANDSAT-4 MSS and TM data was determined by analyzing TM spectral and spatial performance in terms of spectral variability of natural targets and the TM-ground instantaneous field-of-view (IFOV) variability in level and mountainous terrain; and by assessing the suitability of TM and MSS image products for characterizing renewable resourse features. The TM data should be extremelly valuable for crop type and area proportion estimation; undating agricultural land use survey maps at 1:24,000 scale and smaller, field boundary definition; and determining the size and location of individual farmsteads. Ongoing research activities are focused on making spectral and spatial analyses of both MSS and TM analytical film products. The improved spectral, spatial, and radiometric quality of the TM data, should promote a renewed emphasis and interest in direct visual interpretation of these image products, both for updating and improving land stratification in support of resource inventory and for enhancing the image analyst's contribution to computer-assisted analysis procedures.

Degloria, S. D.↗
NASA NTRS1990

Mesoscale monitoring of the soil freeze/thaw boundary from orbital microwave radiometry

A technique was developed for mapping the spatial extent of frozen soils from the spectral characteristics of the 10.7 to 37 GHz radiobrightness. Through computational models for the spectral radiobrightness of diurnally heated freesing soils, a distinctive radiobrightness signature was identified for frozen soils, and the signature was cast as a discriminant for unsupervised classification. In addition to large area images, local area spatial averages of radiobrightness were calculated for each radiobrightness channel at 7 meteorologic sites within the test region. Local area averages at the meteorologic sites were used to define the preliminary boundaries in the Freeze Indicator discriminate. Freeze Indicator images based upon Nimbus 7, Scanning Multichannel Microwave Radiometer (SMMR) data effectively map temporal variations in the freeze/thaw pattern for the northern Great Plains at the time scale of days. Diurnal thermal gradients have a small but measurable effect upon the SMMR spectral gradient. Scale-space filtering can be used to improve the spatial resolution of a freeze/thaw classified image.

Dobson, Craig↗
NASA NTRS2015

Oyster Fisheries App

This project is creating a cloud‐enabled, HTML 5 web application to help oyster fishermen and state agencies apply Earth science to improve the management of this important natural and economic resource. The Oyster Fisheries app gathers and analyzes environmental and water quality information, and alerts fishermen and resources managers about problems in oyster fishing waters. An intuitive interface based on Google Maps displays the geospatial information and provides familiar interactive controls to the users. Alerts can be tailored to notify users when conditions in specific leases or public fishing areas require attention. The app is hosted on the Amazon Web Services cloud. It is being developed and tested using some of the latest web development tools such as web components and Polymer.

Perez Guerrero, Geraldo A.↗
NASA NTRS2019

Characterization of Subsurface Flow Dynamics for Forecasting of Solar Activity

Evolution of large-scale magnetic field structures in the solar photosphere and corona is controlled by motions beneath the visible surface of the Sun. Subsurface plasma flows play a critical role in formation and evolution of active regions and their activity. We analyze subsurface flow maps provided by the local helioseismology pipeline from the Helioseismic and Magnetic Imager (HMI) data on board the Solar Dynamics Observatory, and investigate links between flow characteristics and magnetic activity. The primary goal is to determine flow descriptors, which can improve solar activity forecasts. In particular, by employing machine learning classifiers, we test how the flow helicity and velocity shear descriptors can improve the prediction of initiation of flares and CME eruptions.

Kosovichev, Alexander↗