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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deep learning-driven super-resolution in Raman hyperspectral imaging: Efficient high-resolution reconstruction from low-resolution data

Deep learning (DL) has become an indispensable tool in hyperspectral data analysis, automatically extracting valuable features from complex, high-dimensional datasets. Super-resolution reconstruction, an essential aspect of hyperspectral data, involves enhancing spatial resolution, particularly relevant to low-resolution hyperspectral data. Yet, the pursuit of super-resolution in hyperspectral analysis is fraught with challenges, including acquiring ground truth high-resolution data for training, generalization, and scalability. The pressing issue of extended spectral acquisition times, notably for high-resolution scans, is a significant roadblock in hyperspectral imaging. Super-resolution methods offer a promising solution by providing higher spatial resolution data to expedite data collection and yield more efficient outcomes. This paper delves into a practical application of these concepts using Raman imaging, where spectral acquisition times can be prohibitively long. In this context, DL-based super-resolution models demonstrate their efficacy by predicting and reconstructing high-resolution Raman data from low-resolution input, eliminating the need for resource-intensive high-resolution scans. While previous work often relied on substantial high-resolution datasets, this study showcases the ability to achieve similar outcomes even with limited data, presenting a more practical and cost-effective approach. In conclusion, the results offer a glimpse into the transformative potential of this technology to streamline hyperspectral imaging applications by saving valuable time and resources through the successful generation of high-resolution data from low-resolution inputs.

42 ENGINEERING↗
DOE OSTI2024

Impacts of Spatial Resolution in a High-Fidelity Capacity Expansion Model: An ERCOT Case Study

Capacity expansion models are important tools in examining the evolution of the electric power sector. Embedded in these tools are many modeling choices with consequential impacts on computational burden and associated analysis. In this study, we adjust the spatial resolution of the Regional Energy Deployment System (ReEDS) to understand the implications of higher-fidelity modeling on energy system projections and model solve times. The native ReEDS regions capture the contiguous United States in 134 balancing areas whereas the regions in the higher-resolution version are defined by over 3,000 U.S. counties. Using both resolutions, we conduct a case study of the Texas Interconnection (The Electric Reliability Council of Texas [ERCOT]) to explore differences in model projections and to inform appropriate applications of high spatial resolution in a large-scale, applied capacity expansion model.

county↗
NASA NTRSDate not supplied

Determining True Sensor Spatial Resolution of Very High Resolution Optical Imagery

Some satellite data is delivered in images with gridded pixels. This gridded pixel size is often assumed to be the spatial resolution of the satellite sensor; however, this is not always the case. An image can be grided to any arbitrary pixel size, but the sensor resolution will remain constant. For example, an image with a pixel grid size much smaller than the sensor resolution will appear blurry along what should be sharp transitions. This discrepancy between an image’s pixel size and true sensor spatial resolution can be the source of much confusion and even misinformation among data users, which may lead them to waste time and resources on using images that do not suit their spatial resolution needs. This presentation will highlight our evaluation of the true spatial resolution of various government and commercial images in the pixel size range of 0.3 m to 60 m. Images evaluated include ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels). Our evaluation of true sensor spatial resolution, or ‘footprint size’ is based on the sensor’s line spread function (LSF). We calculate the width at half the height of the LSF to find the full width at half maximum (FWHM). The FWHM is how we report sensor spatial resolution. Different objects are examined for constructing the LSF depending on the sensor spatial resolution. Coarser resolution sensors in this evaluation such as Sentinel-2 and Landsat 8/9 are examined at bridges over a dark water background. The bright bridge acts as a line impulse, giving a sensor’s line spread function (LSF) in one direction. Additionally, we simulate the impacts of bridge width on the apparent LSF to obtain a true LSF without the effects of bridge width for these sensors. Finer resolution sensors will image the irregularities in bridges such as trusses, sidewalks, and in some cases painted lines, interfering with the LSF construction. Instead, these sensors are evaluated at large (60 m – 140 m) black and white checkerboards known as Cal/Val sites. At these locations, the image’s transition from black to white is extracted as an edge spread function (ESF). We calculate the derivative of this ESF to obtain the sensor’s LSF. From there, we find the FWHM as we do for the coarser resolution images. With the FWHM and pixel size, we determine how over- or under-sampled the images are. When the ratio of a sensor’s spatial resolution and the gridded image’s pixel size is less than 1, the image is considered under-sampled. In this case, each pixel’s information is unique but only a portion of that pixel’s ground area has been measured. On the other side, if the ratio is greater than 1, the image is considered over-sampled. That is, each pixel’s information is sourced from within the ground extent of the pixel and some extent outside additionally. We will show the true spatial resolution and the extent of over-/under-sampling in the imagery from ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels).

Alana Semple↗
NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗
DOE OSTI2026

Multi-resolution Arctic Shrub Cover Dataset Derived from UAS and Airborne SfM and LiDAR (2013-2025)

We synthesized 177 unoccupied aerial system flights and 77 airborne flights across the Arctic and created a multi-resolution benchmark data of low-to-tall shrub fractional cover leveraging Structure-from-Motion and Light Detection and Ranging. The resulting dataset covered a total of 1899 km2 across Alaska, Western Canada, Sweden, and Siberian Arctic, including key sites from the Oro Arctic to the High Arctic. The dataset is organized into 6 primary data collection directories (“Abisko,” “AWI,” “ERE,” “Fairbanks,” “NGEE,” “Toolik”), each containing site and flight subdirectories. Flight directories include shrub cover rasters (*.tifs) at 1 m, 5 m, and 30 m resolution, the canopy height model at 1 m resolution (*.tifs), and a bounding box *.kml file. For the AWI, Abisko, NGEE, and Fairbanks collections, we also include the GCC raster at 1 m resolution (*.tif). Files are organized by Collection > Site > Flight Name > Data Files. Flight rasters are in the local UTM zone and the .kml files are in the geographic coordinate system EPSG 4326. We also include a .csv file that details the source datasets for every flight. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

canopy height model↗
NASA NTRS2012

The Impact of Horizontal and Temporal Resolution on Convection and Precipitation with High-Resolution GEOS-5

Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

Putman, William P.↗
NASA NTRS2022

Evaluating the Impact of Chemical Complexity and Horizontal Resolution on Tropospheric Ozone Over the Conterminous US With a Global Variable Resolution Chemistry Model

A new configuration of the Community Earth System Model (CESM)/Community Atmosphere Model with full chemistry (CAM-chem) supporting the capability of horizontal mesh refinement through the use of the spectral element (SE) dynamical core is developed and called CESM/CAM-chem-SE. Horizontal mesh refinement in CESM/CAM-chem-SE is unique and novel in that pollutants such as ozone are accurately represented at human exposure relevant scales while also directly including global feedbacks. CESM/CAM-chem-SE with mesh refinement down to ∼14 km over the conterminous US (CONUS) is the beginning of the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0). Here MUSICAv0 is evaluated and used to better understand how horizontal resolution and chemical complexity impact ozone and ozone precursors over CONUS as compared to measurements from five aircraft campaigns, which occurred in 2013. This field campaign analysis demonstrates the importance of using finer horizontal resolution to accurately simulate ozone precursors such as nitrogen oxides and carbon monoxide. In general, the impact of using more complex chemistry on ozone and other oxidation products is more pronounced when using finer horizontal resolution where a larger number of chemical regimes are resolved. Large model biases for ozone near the surface remain in the Southeast US as compared to the aircraft observations even with updated chemistry and finer horizontal resolution. This suggests a need for adding the capability of replacing sections of global emission inventories with regional inventories, increasing the vertical resolution in the planetary boundary layer, and reducing model biases in meteorological variables such as temperature and clouds.

MUSICA↗
NASA NTRS1988

High-spatial resolution and high-spectral resolution detector for use in the measurement of solar flare hard X-rays

In the areas of high spatial resolution, the evaluation of a hard X-ray detector with 65 micron spatial resolution for operation in the energy range from 30 to 400 keV is proposed. The basic detector is a thick large-area scintillator faceplate, composed of a matrix of high-density scintillating glass fibers, attached to a proximity type image intensifier tube with a resistive-anode digital readout system. Such a detector, combined with a coded-aperture mask, would be ideal for use as a modest-sized hard X-ray imaging instrument up to X-ray energies as high as several hundred keV. As an integral part of this study it was also proposed that several techniques be critically evaluated for X-ray image coding which could be used with this detector. In the area of high spectral resolution, it is proposed to evaluate two different types of detectors for use as X-ray spectrometers for solar flares: planar silicon detectors and high-purity germanium detectors (HPGe). Instruments utilizing these high-spatial-resolution detectors for hard X-ray imaging measurements from 30 to 400 keV and high-spectral-resolution detectors for measurements over a similar energy range would be ideally suited for making crucial solar flare observations during the upcoming maximum in the solar cycle.

Desai, U. D.↗
DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1991

First results from the Goddard High-Resolution Spectrograph - A demonstration of spectral resolution and experiments with deconvolution

High-quality spectra of the sharp-lined star Chi Lupi were obtained with the Goddard High Resolution Spectrograph (GHRS). Spectra for the various resolving powers achievable with the echelle and G160M gratings are displayed. The effect of spherical aberration upon the spectral resolution is found to be negligible when using the small science aperture. The resolution of the large science aperture spectra is degraded by less than a factor of two. Efforts with spectral deconvolution using several techniques show that it is possible to regain much of the spectral resolution lost in the large science aperture if high signal-to-noise spectra are obtained.

Wahlgren, Glenn M.↗
DOE OSTI2026

Super-resolution model for overlapping peak detection and improved spatial resolution in high-energy diffraction microscopy

Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.

High-energy diffraction microscopy↗
NASA NTRS2006

Advanced Remote-Sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with MODIS Spatial Resolution

The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS Aqua Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and MODIS in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for MODIS.

remote sensing↗
DOE OSTI2024

Annotation of DOM metabolomes with an ultrahigh resolution mass spectrometry molecular formula library

Current approaches to analyzing metabolomic data often rely on matching MS/MS fragmentation data to sparse libraries or databases. This approach results in limited identification of features, often with less than 10% of the dataset being annotated. A complementary approach is to assign molecular formula to features based on accurate mass measurements, but the platforms commonly used for metabolomics do not have the needed accuracy or resolving power to do this robustly, particularly for larger molecules. Using our newly modified analysis tool, CoreMS, we generated a library of molecular formula from pooled samples analyzed with LC-21T FT-ICR MS. This library successfully annotated approximately 53.2% of features identified from the exometabolome of marine diatom Phaeodactylum tricornutum – a nearly ten-fold increase over the 5.9% annotation rate achieved using a conventional MS/MS library matching approach. Using this FT-ICR MS library approach, we were able to differentiate differences in the exometabolome of P. tricornutum in iron replete and iron limited conditions, with 668 metabolites being differentially expressed (p < 0.05, 2 x intensity difference) under these conditions. The traditional MS/MS fragmentation-based annotation approach only annotated 61 of these metabolites, while our novel pipeline annotated 450 metabolites and revealed 12 metabolites that were significantly more abundant under low iron conditions. Our results demonstrate the utility of ultrahigh resolution mass spectrometry for generating more comprehensive and confident molecular annotations.

21T-FTICR-MS, CoreMS↗
DOE OSTI2025

Commission < 5 µm spatial resolution x-ray imager for High Resolution Turbulence experiments

This report presents the successful development, commissioning, and deployment of the Scintillation-Based X-ray Imager (SBXI) for the High-Resolution Turbulence (HRT) campaign at the National Ignition Facility (NIF). The SBXI system was designed to overcome the spatial resolution and efficiency limitations of conventional x-ray imaging detectors. Through careful system engineering, rigorous laboratory characterization, and experimental validation at NIF, the SBXI has demonstrated spatial resolution at the object plane of 5 μm (±0.5 μm) and a detective quantum efficiency (DQE) of 34% at 7.2 keV, both of which surpass the requirements set by the campaign, and meeting the L2 milestone. The system’s deployment enables high-fidelity imaging of fine-scale hydrodynamic instabilities, directly supporting advanced turbulence model validation and future high energy density physics research.

42 ENGINEERING↗
NASA NTRS2003

Fine Resolution Topographic Mapping of the Jovian Moons: A Ka-Band High Resolution Topographic Mapping Interferometric Synthetic Aperture Radar

The topographic data set obtained by MOLA has provided an unprecedented level of information about Mars' geologic features. The proposed flight of JIMO provides an opportunity to accomplish a similar mapping of and comparable scientific discovery for the Jovian moons through use of an interferometric imaging radar analogous to the Shuttle radar that recently generated a new topographic map of Earth. A Ka-band single pass across-track synthetic aperture radar (SAR) interferometer can provide very high resolution surface elevation maps. The concept would use two antennas mounted at the ends of a deployable boom (similar to the Shuttle Radar Topographic Mapper) extended orthogonal to the direction of flight. Assuming an orbit altitude of approximately 100km and a ground velocity of approximately 1.5 km/sec, horizontal resolutions at the 10 meter level and vertical resolutions at the sub-meter level are possible.

Madsen, S. N.↗
NASA NTRS2003

Fine resolution topographic mapping of the Jovian moons: a Ka-band high resolution topographic mapping interferometric synthetic aperture radar

The topographic data set obtained by MOLA has provided an unprecedented level of information about Mars' geologic features. The proposed flight of JIMO provides an opportunity to accomplish a similar mapping of and comparable scientific discovery for the Jovian moons through us of an interferometric imaging radar analogous to the Shuttle radar that recently generated a new topographic map of Earth. A Ka-band single pass across-track synthetic aperture radar (SAR) interferometer can provide very high resolution surface elevation maps. The concept would use two antennas mounted at the ends of a deployable boom (similar to the Shuttle Radar Topographic Mapper) extended orthogonal to the direction of flight. Assuming an orbit altitude of approximately 100 km and a ground velocity of approximately 1.5 km/sec, horizontal resolutions at the 10 meter level and vertical resolutions at the sub-meter level are possible.

Jupiter Icy Moon Orbiter↗
NASA NTRSDate not supplied

Achieving Large-Scale, High-Resolution, Full Shell Replicated X-Ray Optics: Budgeting for Sources of Spatial Resolution Errors

Technology for a large-area, high-angular resolution mirror module for a future Great Observatory x-ray mission is progressing along different paths. To date, none of these are fully developed. Work at the Marshall Space Flight Center (MSFC) seeks to leverage the benefits of full shell optics while exploring the limits of using shell replication technology for optics production. Here, we provide an updated accounting of spatial-resolution-constraining error terms to give context to recent improvements in MSFC replicated optics, as well as guidance and justification for current and future directions of research. Content includes strawman error allocations for an optical system that is parametrically Lynx-like, where the replicated-optics technology stands relative to these allocations, and methodology for mapping development plans to efficiently identify the limiting factors and approaches to overcoming these.

error budget↗