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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 OSTI2019

Operator spreading in quantum maps

Operators in ergodic spin chains are found to grow according to hydrodynamical equations of motion. The study of such operator spreading has aided our understanding of many-body quantum chaos in spin chains. Here we initiate the study of “operator spreading” in quantum maps on a torus, systems which do not have a tensor-product Hilbert space or a notion of spatial locality. Using the perturbed Arnold cat map as an example, we analytically compare and contrast the evolutions of functions on classical phase space and quantum operator evolutions, and identify distinct timescales that characterize the dynamics of operators in quantum chaotic maps. Until an Ehrenfest time, the quantum system exhibits classical chaos, i.e., it mimics the behavior of the corresponding classical system. After an operator scrambling time, the operator looks “random” in the initial basis, a characteristic feature of quantum chaos. These timescales can be related to the quasienergy spectrum of the unitary via the spectral form factor. Furthermore, we show examples of “emergent classicality” in quantum problems far away from the classical limit. Lastly, we study operator evolution in nonchaotic and mixed quantum maps using the Chirikov standard map as an example.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2005

Mapping Weathering and Alteration Minerals in the Comstock and Geiger Grade Areas using Visible to Thermal Infrared Airborne Remote Sensing Data

To support research into both precious metal exploration and environmental site characterization a combination of high spatial/spectral resolution airborne visible, near infrared, short wave infrared (VNIR/SWIR) and thermal infrared (TIR) image data were acquired to remotely map hydrothermal alteration minerals around the Geiger Grade and Comstock alteration regions, and map the mineral by-products of weathered mine dumps in Virginia City. Remote sensing data from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), SpecTIR Corporation's airborne hyperspectral imager (HyperSpecTIR), the MODIS-ASTER airborne simulator (MASTER), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) were acquired and processed into mineral maps based on the unique spectral signatures of image pixels. VNIR/SWIR and TIR field spectrometer data were collected for both calibration and validation of the remote data sets, and field sampling, laboratory spectral analyses and XRD analyses were made to corroborate the surface mineralogy identified by spectroscopy. The resulting mineral maps show the spatial distribution of several important alteration minerals around each study area including alunite, quartz, pyrophyllite, kaolinite, montmorillonite/muscovite, and chlorite. In the Comstock region the mineral maps show acid-sulfate alteration, widespread propylitic alteration and extensive faulting that offsets the acid-sulfate areas, in contrast to the larger, dominantly acid-sulfate alteration exposed along Geiger Grade. Also, different mineral zones within the intense acid-sulfate areas were mapped. In the Virginia City historic mining district the important weathering minerals mapped include hematite, goethite, jarosite and hydrous sulfate minerals (hexahydrite, alunogen and gypsum) located on mine dumps. Sulfate minerals indicate acidic water forming in the mine dump environment. While there is not an immediate threat to the community, there are clearly sources of acidic drainage that were identified remotely.

imaging spectroscopy↗
NASA NTRS2000

High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used by government officials, urban planners, and other decision-makers, to make more informed decisions on how to mitigate the UHI and its subsequent impacts.

Quattrochi, Dale A.↗
DOE OSTI2021

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Finally, our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

42 ENGINEERING↗
DOE OSTI2017

Mapping high pH levels in hydrated calcium silicates

Data on the variability of pH levels in cement-based materials is essential for a better understanding of the early aging of materials and the long-term performance of concrete structures. Current approaches for measuring pH levels in concrete are inadequate with respect to radiometric range and resolution and spatial granularity. We report on a methodology for mapping pH levels in concrete utilizing a halochromic porphyrin sensor molecule that allows a simple measurement of surface values of pH level using a commercial digital camera setup. As proof of concept, cement paste, mortar, and concrete samples were subject to accelerated carbonation and then evaluated for pH profiles at different ages of degradation. Comparative tests on the same specimens were also conducted using phenolphthalein as the pH indicator. Spatial distribution of pH level from pH 11.0 to 13.5 was mapped at various levels of carbonation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
NASA NTRS1998

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Quattrochi, Dale A.↗
DOE OSTI2017

Evaluation of Story Maps to Enhance Public Engagement and Communication at Legacy Management Sites - 17334

The US Department of Energy's Office of Legacy Management's (LM) mission is to fulfill the department's post-closure responsibilities and to ensure protection of human health and the environment. Accomplishing that mission currently requires managing 91 legacy sites across the country by performing efficient long-term surveillance and maintenance activities, preserving and making accessible historic site records, and identifying opportunities for beneficial reuse. Integral to the success of these activities is connecting and effectively communicating with the public, governments, and other interested parties. Relationships with such entities are so important that the Office of Legacy Management has elevated such engagement to one of its strategic goals for the next 10 years. Several public engagement efforts are currently supported, including stakeholder meetings, interpretive visitor centers, hard-copy documents, and Internet-based information sources. The tools available to communicate with the public via the Internet are continually improving, and LM proactively evaluates these tools to enhance public engagement. The use of ESRI Story Maps to effectively and more succinctly communicate LM's long-term surveillance and maintenance practices is one tool currently being evaluated. Story Maps can utilize multiple types of content to engage users through site narratives, illustrations of change over time, photos, videos, and embedded links to external sources of information. The ability to illustrate site complexities via graphics and geo-spatial data is particularly useful for staff as well as communicating to stakeholders. Staff with a variety of expertise and functions in the organization can be empowered to respond to stakeholder questions using this tool. In addition, Story Maps can be easily initiated and managed in real time by LM site managers, an efficiency that would be invaluable to them as immediate site communication needs arise. A series of test Story Maps for several sites were developed to explore the capabilities of the tool. The test Story Maps included pages that described site description and overview, historical conditions and use, cleanup conditions, current monitoring data if applicable, and institutional controls. Links to existing communications tools were also incorporated in Story Maps, such as existing web sites that currently store environmental reports and the Geo-spatial Environmental Mapping System (GEMS), where stakeholders can download monitoring data. As with any tool, many things must be taken into consideration, such as: 1) Can the current IT infrastructure support the tool? 2) What data quality protocols need to be established? 2) What resources will be needed to maintain this tool? 3) What type of information should be shared? 4) Who will be responsible for information updates? This paper explores potential approaches for developing and deploying this tool for the public. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Unsupervised Segmentation and Clustering Workflow for Efficient Processing of 4D-STEM and 5D-STEM Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure–strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.

4D-STEM↗
NASA NTRS1994

The rotation of photospheric magnetic fields: A random walk transport model

In an earlier study of solar differential rotation, we showed that the transport of magnetic flux across latitudes acts to establish quasi-stationary patterns, therby accounting for the observed rigid rotation of the large-scale photospheric field. In that paper, the effect of supergranular convection was represented by a continuum diffusion, limiting the applicability of the calculations to large spatial scales. Here we extend the model to scales comparable to that of the supergranulation itself by replacing the diffusive transport with a discrete random walk process. Rotation curves are derived by cross-correlating the simulated photospheric field maps for a variety of time lags and spatial resolutions. When the lag between maps is relatively short less than or approximately = 15 days), the midlatitude correlation functions show two distinct components: a broad feature associated with the large-scale unipolar patterns and a narrow feature originating from small magnetic structures encompossing from one to several supergranular cells. By fitting the broad component we obtain the rigid rotation profile of the patterns, whereas by fitting the narrow component, we recover the differential rate of the photospheric plasma itself. For time lags of 1 month or greater, only the broad feature associated with the long-lived patterns remains clearly identifiable in the simulations.

Wang, Y. -M.↗
NASA NTRS1973

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. The vegetation map in preparation at the time of the last report was refined and labeled. This map is presented as an indication of the spatial and classificatory detail possible from interpretations of enlarged ERTS-1 color photographs. Using this map, areas covered by the several vegetation types characterized by white spruce were determined by planimetry. A 1:63,360 scale land use map of the Juneau area was drawn. This map incorporates the land use classification system now under development by the U.S. Geological Survey. The ERTS-1 images used in making the Juneau map were used to determine changes in surface area of the terminal zones of advancing and receding glaciers, the Taku, Norris, and Mendenhall. A new 1:63,360 scale land use map of the Bonanza Creek Experimental Forest and vicinity was drawn. Several excellent new sciences of test areas were received from NASA in color-infrared transparency format. These are being used for making photographic prints for analysis and mapping according to procedures outlined in this report.

Anderson, J. H.↗
NASA NTRS2010

Multiple Spectral-Spatial Classification Approach for Hyperspectral Data

A .new multiple classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region, with the corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker selection procedure, each of them combining the results of a pixel-wise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification -driven marker and forms a region in the spectral -spatial classification: map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies, when compared to previously proposed classification techniques.

Tarabalka, Yuliya↗
NASA NTRS1991

Polarimetric mapping of Orion using Millipol - Magnetic activity in BN/KL

The spatial distribution of the polarized component of the thermal dust emission from the core of the Orion molecular cloud has been mapped over 15 positions at a wavelength of 1300 microns using the Millipol instrument on the NRAO 12 m telescope. The polarization directions deduced for the map positions are quite similar, implying that the embedded magnetic field is strong (of the order of 1 mG) and uniform in direction over the core of the cloud. The mean polarization percentage, 4.6 percent, is quite high, and two positions show polarization percentages of nearly 8 percent, the highest yet detected for polarized thermal dust emission. Finally, the polarization of the BN/KL position was found to be significantly lower than the polarizations toward positions 30 arcmin outside BN/KL.

Leach, Robert W.↗
NASA NTRS2005

IRAS 16293-2422: Evidence for Infall onto a Counter-Rotating Protostellar Accretion Disk

We report high spatial resolution VLA observations of the low-mass star-forming region IRAS 16293-2422 using four molecular probes: ethyl cyanide (CH3CH2CN)) methyl formate (CH3OCHO), formic acid (HCOOH), and the ground vibrational state of silicon monoxide (SiO). Ethyl cyanide emission has a spatial scale of approx. 20" and encompasses binary cores A and B as determined by continuum emission peaks. Surrounded by formic acid emission, methyl formate emission has a spatial scale of approx. 6" and is confined to core B. SiO emission shows two velocity components with spatial scales less than 2" that map approx. 2" northeast of the A and B symmetry axis. The redshifted SiO is approx. 2" northwest of blueshifted SiO along a position angle of approx. 135deg which is approximately parallel to the A and B symmetry axis. We interpret the spatial position offset in red and blueshifted SiO emission as due to rotation of a protostellar accretion disk and we derive approx. 1.4 Solar Mass, interior to the SiO emission. In the same vicinity, Mundy et al. (1986) also concluded rotation of a nearly edge-on disk from OVRO observations of much stronger and ubiquitous CO-13 emission but the direction of rotation is opposite to the SiO emission findings. Taken together, SiO and CO-13 data suggest evidence for a counter-rotating disk. Moreover, archival BIMA array CO-12C data show an inverse P Cygni profile with the strongest absorption in close proximity to the SiO emission, indicating unambiguous material infall toward the counter-rotating protostellar disk at a new source location within the IRAS 16293-2422 complex. The details of these observations and our interpretations are discussed.

Remijan, Anthony J.↗
NASA NTRS2021

The Large Footprint of Small-scale Artisanal Gold Mining in Ghana

Gold mining has played a significant role in Ghana's economy for centuries. Regulation of this industry has varied over time and while industrial mining is prevalent in the country, the expansion of artisanal mining, or Galamsey has escalated in recent years. Many of these artisanal mines are not only harmful to human health due to the use of Mercury (Hg) in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal goldmines in Ghana from 2005 to 2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007 to 2017. A combination of machine learning and change detection algorithms were used to calculate different land cover conversions and the timing of conversion annually. Within the study area of southwestern Ghana, our results indicate that approximately 47,000 ha (⨦2218 ha) of vegetation were converted to mining at an average rate of ~2600 ha yr−1. The results indicate that a high percentage(~50%) of this mining occurred between 2014 and 2017. Around 700 ha of this mining occurred within protected areas as mapped by the World Database of Protected Areas. In addition to deforestation, increased artisanal mining activity in recent years has the potential to affect human health, access to drinking water resources and food security. This work expands upon limited research into the spatial footprint of Galamseyin Ghana, complements mapping efforts by local geographers, and will support efforts by the government of Ghana to monitor deforestation caused by artisanal mining.

Abigail Barenblitt↗
DOE OSTI2024

Quasifragmentation functions in the massive Schwinger model

We introduce the concept of the quark quasifragmentation function (qFF) using an equal-time and spatially boosted form of the Collins-Soper fragmentation function where the out-meson fragment is replaced by the current asymptotic condition. We derive the qFF for a fermion in two-dimensional quantum electrodynamics (QED2) using the Kogut-Susskind Hamiltonian after a mapping onto spin qubits in a spatial lattice with open boundary conditions. This form is suitable for quantum computations. We compute the qFF by exact diagonalization of the spin Hamiltonian. The results are compared to the qFF following from the Drell-Levy-Yan result for QED2, both at strong and weak coupling, and to two-dimensional quantum chromodynamics in the lowest Fock approximation.

Fragmentation functions↗
NASA NTRS2013

Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

Atmospheric errors due to the troposphere are a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging. This software generates tropospheric delay maps that can be used to correct atmospheric artifacts in InSAR data. The software automatically acquires all needed GPS (Global Positioning System), weather, and Digital Elevation Map data, and generates a tropospheric correction map using a novel algorithm for combining GPS and weather information while accounting for terrain. Existing JPL software was prototypical in nature, required a MATLAB license, required additional steps to acquire and ingest needed GPS and weather data, and did not account for topography in interpolation. Previous software did not achieve a level of automation suitable for integration in a Web portal. This software overcomes these issues. GPS estimates of tropospheric delay are a source of corrections that can be used to form correction maps to be applied to InSAR data, but the spacing of GPS stations is insufficient to remove short-wavelength tropospheric artifacts. This software combines interpolated GPS delay with weather model precipitable water vapor (PWV) and a digital elevation model to account for terrain, increasing the spatial resolution of the tropospheric correction maps and thus removing short wavelength tropospheric artifacts to a greater extent. It will be integrated into a Web portal request system, allowing use in a future L-band SAR Earth radar mission data system. This will be a significant contribution to its technology readiness, building on existing investments in in situ space geodetic networks, and improving timeliness, quality, and science value of the collected data

Moore, Angelyn W.↗
DOE OSTI2026

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗