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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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DOE OSTI2017

Convolutional Neural Network Approach for Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion

Accurate and high-resolution maps of vegetation are critical for projects seeking to understand the terrestrial ecosystem processes and land-atmosphere interactions in Arctic ecosystems, such as U.S. Department of Energy's Next Generation Ecosystem Experiment (NGEE) Arctic. However, most existing Arctic vegetation maps are at a coarse resolution and with a varying degree of detail and accuracy. Remote sensing-based approaches for mapping vegetation, while promising, are challenging in high latitude environments due to frequent cloud cover, polar darkness, and limited availability of high-resolution remote sensing datasets (e.g., ~ 5 m). This study proposes a new remote sensing based multi-sensor data fusion approach for developing high-resolution maps of vegetation in the Seward Peninsula, Alaska. We focus detailed analysis and validation study around the Kougarok river, located in the central Seward Peninsula of Alaska. We seek to evaluate the integration of hyper-spectral, multi-spectral, radar, and terrain datasets using unsupervised and supervised classification techniques over a ~343.72 km 2 area for generating vegetation classifications at a variety of resolutions (5 m and 12.5 m). We fist applied a quantitative goodness-of-fit method, called Mapcurves, that shows the degree of spatial concordance between the public coarse resolution maps and k-means clustering values and relabels the k values based on the best overlap. We develop a convolutional neural network (CNN) approach for developing high resolution vegetation maps for our study region in Arctic. We compare two CNN approaches: (1) breaking up the images into small patches (e.g., 6 × 6) and predict the vegetation class for entire patch and (2) semantic segmentation and predict the vegetation class for every pixel. We also perform accuracy assessments of the developed data products and evaluate varying CNN architectures. The fusion of hyperspectral and optical datasets performed the best, with accuracy values increased from 0.64 to 0.96-0.97 when using a training map produced by unsupervised clustering and Mapcurves labeling for both CNN models.

Langford, Zach↗

NASA NTRS1981

Surface mapping of selected regions in the Orion Nebula

Low dispersion, large aperture, ultraviolet spectra of selected regions in the Orion Nebula were obtained with the International Ultraviolet Explorer (IUE) scientific instrument. Spectra obtained at 35 contiguous locations defining a mosaic within the nebula were used to generate monochromatic images of high spatial resolution at the wavelengths of the ultraviolet emission lines. Image processing techniques were utilized to generate and analyze these ultraviolet surface maps. The imagery at the three wavelengths studied shows definite differences in the spatial distribution of emission from the CII CIII and OII ions. Ways of using the imagery to determine ionization structure and C/O abundance ratios throughout the regions observed are developed, in addition to means of analyzing the extensive continuum measurements in terms of dust scattering characteristics.

Perry, P. M.↗

NASA NTRS1986

An overview of data acquisition, signal coding and data analysis techniques for MST radars

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.

Rastogi, P. K.↗

NASA NTRS2005

Vision Based Localization in Urban Environments

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by each camera. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations, For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of two primary components. The first is the vision system which uses binocular stereo ranging together with a set of heuristics to identify features likely to be part of building exteriors and to compute an estimate of the robot's motion since the previous step. The resulting visual features and the associated range measurements are software component, a particle-filter based localization system. This system uses the map and the then fed to the second primary most recent results from the vision system to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and will include the results of applying the system to the global localization of a robot over an approximately half-kilometer traverse across JPL'S Pasadena campus.

unmanned-ground vehicles↗

DOE OSTI2021

Block Scale Rooftop Solar Technical Potential for the City of Orlando

The html maps are provided as supplementary information for the publication titled Parcel Scale Assessment of Rooftop Solar Technical Potential (NREL/PR-7A40-80780). The maps contain information on rooftop solar technical potential at the block scale for the city of Orlando in Florida. The rooftop solar technical potential information is based on data from two different datasets. The first dataset is LiDAR data for the city of Orlando obtained from the Orlando Utilities Commission (OUC) (Koebrich et al. 2021). The second dataset is a national parcel dataset (HIFLD 2020) which contains descriptive data and geometries for parcels in the U.S. Parcel scale data from both these datasets have been processed and aggregated to block scale to produce these html maps. The first html map (block scale developable roof area for Orlando) contains the developable roof area for solar. The second html map (block scale rooftop solar technical potential for Orlando) contains the rooftop solar technical potential in units of kilowatts as well as additional information on the most common building use type and the most common building occupancy type for the block. These html maps are provided to demonstrate the proof-of-concept analysis conducted for Orlando.

14 SOLAR ENERGY↗

NASA NTRS2011

High Resolution Camera for Mapping Titan Surface

Titan, Saturn's largest moon, has a dense atmosphere and is the only object besides Earth to have stable liquids at its surface. The Cassini/Huygens mission has revealed the extraordinary breadth of geological processes shaping its surface. Further study requires high resolution imaging of the surface, which is restrained by light absorption by methane and scattering from aerosols. The Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft has demonstrated that Titan's surface can be observed within several windows in the near infrared, allowing us to process several regions in order to create a geological map and to determine the morphology. Specular reflections monitored on the lakes of the North Pole show little scattering at 5 microns, which, combined with the present study of Titan's northern pole area, refutes the paradigm that only radar can achieve high resolution mapping of the surface. The present data allowed us to monitor the evolution of lakes, to identify additional lakes at the Northern Pole, to examine Titan's hypothesis of non-synchronous rotation and to analyze the albedo of the North Pole surface. Future missions to Titan could carry a camera with 5 micron detectors and a carbon fiber radiator for weight reduction.

Cassini↗

DOE OSTI2025

Bias correcting regional scale Earth system model projections: novel approach using empirical mode decomposition

Bias correction is a crucial step in using Earth system model outputs for assessments, as it adjusts systematic errors by comparing the model to observations. However, standard methods – ranging from mean-based linear scaling to distribution-based quantile mapping typically treat bias correction as a single-scale process, overlooking the fact that biases can manifest differently across daily, seasonal, and annual timescales. In this study, we propose a novel, timescale-aware bias-correction approach built on Empirical Mode Decomposition. By decomposing the meteorological signal into multiple oscillatory components and aggregating them to represent distinct timescales, we apply targeted corrections to each component, thereby preserving both short- and long-term structure in the data. Experimental illustrations show that the timescale-aware EMDBC framework matches the performance of conventional quantile-delta mapping (QDM) at the native daily scale and achieves progressively larger bias reductions at bi-weekly, seasonal, and annual scales. As a result, the proposed approach offers a more robust path to accurate and reliable Earth system projections, strengthening their utility for resilience and adaptation planning.

Ganguli, Arkaprabha [Argonne National Laboratory (↗

NASA NTRS1988

Significance of elevated K/Rb ratios in lower crustal rocks

The granulite uncertainty principle, which states that it is difficult or impossible to determine with certainty the maximum geopressure and geotemperature that a granulite has experienced, is addressed. Also, geochemical fingerprinting cannot always be used reliably in the nebulous region that is transitional between metamorphic and igneous environments. Ion exchange thermometers are typically useful to approximately 800 C in slowly cooled plutonic rocks unless one uses a reintegration technique on unmixed minerals, or unless a metastable mineral assemblage can be observed. It is argued that in most granulites, fossil temperatures are typically obliterated by reequilibration and/or deformation during slow cooling. Granulite metamorphism may be further complicated by the common association with igneous activity. The previously-used geochemical indicators such as high K/Rb ratios and LIL depletion may not be strictly the result of granulite facies metamorphic depletion, but also may result from igneous processes, which depend on bulk and mineral compositions and on the mineralogy of the protolith. Detailed geologic mapping will be the ultimate arbitrator of whether a given geochemical signature is the result of igneous or metamorphic processes.

Frost, B. Ronald↗

DOE OSTI2025

Designing robust energy policy packages under deep uncertainty: A multi-metric decision support framework

The complexity of transitioning to sustainable energy systems requires policy frameworks capable of balancing multiple objectives while addressing deep uncertainty. However, existing approaches often lack systematic methods to identify combinations of policy levers that remain effective across a wide range of uncertain futures. This paper presents a novel decision support framework that guides the selection of robust policy packages based on their performance across multiple objectives under uncertainty. Our method leverages a large ensemble of scenarios and applies scenario discovery techniques to identify influential policy levers. Here, we introduce new indicators to assess the robustness of policies by evaluating their ability to mitigate adverse outcomes across metrics. These indicators support an iterative process to build a robust policy package. Finally, we map the technological and energy pathways associated with the robust policy package by leveraging an energy system optimization model. We illustrate the application of this framework to the Spanish energy system, providing insights into how specific combinations of policy levers shape decarbonization pathways under uncertainty.

Decision-support method↗

DOE OSTI2026

Innovative laser-based methods for monitoring fuel retention in ITER

This paper addresses the challenge of tritium inventory management in ITER and future fusion reactors, highlighting the importance of accurate tritium measurement and its spatial distribution within the vacuum vessel. Given ITER’s operational constraints, especially the limit on tritium retention, precise measurement is essential for both safety and regulatory compliance. To tackle these questions, the paper presents the T-monitor diagnostic system developed by Forschungszentrum Jülich, which uses Laser-Induced Desorption (LID) in combination with Diagnostic Residual Gas Analysis (DRGA) to measure hydrogen isotope concentrations on the surface of divertor tiles. The system integrates a high-power laser, advanced optical components, and a Fast Scanning Mirror Unit (FSMU) for accurate laser spot positioning with rapid response. Designed to measure in situ tritium retention, the diagnostic provides high-resolution spatial mapping, vital for evaluating detritiation strategies. The laser heating process increases the divertor surface temperature to 1600 K within the laser spot, promoting hydrogen isotope desorption. Accurate measurements require the precise control of laser parameters, including pulse duration and spot size, with a target relative accuracy of 20%. The optical design includes both in-vessel and ex-vessel components, such as durable high-reflectivity mirrors made of gold and copper, selected not only for their infrared performance but also for their transmission of visible wavelengths for observation purposes. To protect optical components from contamination, a pneumatic shutter is used.

Hydrogen isotopes↗

DOE OSTI2024

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models–Advances, Applications, and Challenges

Earth System Models (ESMs) simulate the exchange of mass and energy between the land surface and the atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is the second most important greenhouse gas after carbon dioxide. There are growing concerns over the rapidly increasing methane concentration in the atmosphere, underscoring the need for accurate global modeling of its emissions using ESMs. Of the multitude of sources of methane globally, wetlands are the largest natural emitters for methane, leading to significant efforts targeting their representation in ESMs with a special focus on their methane emissions. In this review, we first provide a historical overview of including wetland–methane components in ESMs and how methane modeling approaches have evolved over time. Second, we discuss recent modeling advancements that show promise for improvements in methane emissions predictions, namely the coupling of surface and atmospheric modules of ESMs, the representation of microtopography and transport mechanisms, the resolution of microbial processes at different spatial–temporal scales, and the improved mapping of wetland area extent across the different wetland types. Third, we shed light on the different challenges hindering accurate estimations of wetland–methane emissions, as shown by the consistent discrepancy between bottom–up and top–down models' predictions. Finally, we emphasize that more detailed representation of biogeochemistry and dynamic hydrology while resolving the within–wetland vegetation heterogeneity should improve model predictions, especially when coupled with expanding ground–based measurement networks and high–resolution remote sensing mapping of methane–relevant variables, such as water elevation, water table depth, and methane concentration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Discerning the Location and Nature of Coke Deposition from Surface to Bulk of Spent Zeolite Catalysts

The nanoscale compositional mapping of fresh HZSM-5 catalyst synthesized using hydrothermal process as well as after just steaming and after ethanol conversion reaction for 72 hours at realistic catalytic conditions was investigated using atom probe tomography. Atom probe tomography permitted direct atomic scale imaging of non-uniform distribution of Al within the HZSM-5 as well as for the first time image the hydrocarbon coking after ethanol reaction. Clear evidences for existence of multiple C-H molecular species which appear to aggregate as clusters within the pores of spent HZSM-5 catalyst materials is provided. Furthermore, these results provide evidence for the ability of atom probe tomography, a powerful 3D characterization tool in interrogating the atomic scale chemistry of zeolite catalyst materials at industrially relevant catalytic conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Multiple generations of grain aggregation in different environments preceded solar system body formation

The solar system formed from interstellar dust and gas in a molecular cloud. Astronomical observations show that typical interstellar dust consists of amorphous (a-) silicate and organic carbon. Bona fide physical samples for laboratory studies would yield unprecedented insight about solar system formation, but they were largely destroyed. The most likely repositories of surviving presolar dust are the least altered extraterrestrial materials, interplanetary dust particles (IDPs) with probable cometary origins. Cometary IDPs contain abundant submicron a-silicate grains called GEMS (glass with embedded metal and sulfides), believed to be carbon-free. Some have detectable isotopically anomalous a-silicate components from other stars, proving they are preserved dust inherited from the interstellar medium. However, it is debated whether the majority of GEMS predate the solar system or formed in the solar nebula by condensation of high-temperature (>1,300 K) gas. Here, we map IDP compositions with single nanometer-scale resolution and find that GEMS contain organic carbon. Mapping reveals two generations of grain aggregation, the key process in growth from dust grains to planetesimals, mediated by carbon. GEMS grains, some with a-silicate subgrains mantled by organic carbon, comprise the earliest generation of aggregates. These aggregates (and other grains) are encapsulated in lower-density organic carbon matrix, indicating a second generation of aggregation. Since this organic carbon thermally decomposes above ~450 K, GEMS cannot have accreted in the hot solar nebula, and formed, instead, in the cold presolar molecular cloud and/or outer protoplanetary disk. We suggest that GEMS are consistent with surviving interstellar dust, condensed in situ, and cycled through multiple molecular clouds.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Statistical inference of empirical constituents in partitioned analysis from integral-effect experiments: An application in thermo-mechanical coupling

Rapid advancements in parallel computing over the last two decades have enabled simulations of complex, coupled systems through partitioning. In partitioned analysis, independently developed constituent models communicate, representing dependencies between multiple physical phenomena that occur in the full system. Figure 1 schematically demonstrates a coupled system with two constituent models, each resolving different physical behavior. In this figure, the constituent model, denoted as the “consumer,” relies upon some input parameter that is being provided by the constituent model acting as a “feeder”. The role of the feeder model is to map operating conditions (i.e. those that are stimulating the process) to consumer inputs, thus providing functional inputs to the consumer model*. Problems arise if the feeder model cannot be built–a challenge that is prevalent for highly complex systems in extreme operational conditions that push the limits of our understanding of underlying physical behavior. Often, these are also the situations where separate-effect experiments isolating the physical phenomena are not available; meaning that experimentally determining the unknown constituent behavior is not possible (Bauer and Holland, 1995; Unal et al., 2013), and that integral-effect experiments that reflect the behavior of the complete system tend to be the only available observations. In this paper, the authors advocate for the usefulness of integral-effect experiments in furthering a model developer’s knowledge of the physics principles governing the system behavior of interest.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Code Release for “Unlocking Extreme Space Weather through Advanced Modeling of Legacy Vela Spacecraft” ER

The software being developed for this project has two mains aims. First, a Bayesian Model Calibration (BMC) procedure is being developed to calibrate a spallation model that simulates protons hitting a spacecraft orbiting earth to real data. The procedure will be developed for general data (there is no data release requested as part of this code release). Second, an inverse physics modeling task is being undertaken to map the number of resulting neutrons observed from this process to the expected number of protons that hit the model. This second task is of statistical interest; to publish on it, the code will need to be open source.

Murph, Alexander↗

DOE OSTI2026

Raman spectroscopic investigation of ianthinite [U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O, a rare mixed-valence uranium oxide hydrate

Ianthinite ([[U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O) is an exotic mineral that possesses U in both tetravalent and hexavalent oxidation states and is structurally related to the U 3 O 8 polymorphs, which are commonly encountered technogenic materials in the nuclear fuel cycle. Despite the similarities between U 3 O 8 and ianthinite, and the importance of ianthinite in U paragenesis, no Raman spectra have been reported for this mineral. Here, to gain a more complete understanding of how structural attributes of ianthinite give rise to observable spectroscopic features and how these may relate to important materials in the nuclear fuel cycle, we provide, for the first time, Raman spectra of ianthinite. Ianthinite readily oxidizes at ambient conditions, complicating analysis of phase-pure material. Several analytical methods are employed herein to decouple the Raman features of ianthinite from its alteration product(s). First, a simple difference spectrum is presented, then results of Raman spectroscopic mapping are employed, and finally, we use a novel processing and analysis method. Each analysis method provides different insight into structural features that are unique to ianthinite, in particular, features that are attributable to U(IV) in distorted octahedral coordination in both ianthinite and U 3 O 8 phases.

Spano, Tyler L. [Oak Ridge National Laboratory (OR↗

DOE OSTI2023

Basin-Scale Relicensing Opportunity Product User Guide

The Basin-Scale Relicensing Opportunity products provide a platform for identifying favorable areas for basin-wide collaboration using metrics derived from anticipated Federal Energy Regulatory Commission (FERC) relicensing dates. The hydropower relicensing process requires long-term resource allocation by agencies, hydropower owner/operators, non-governmental organizations, and tribal, state, and federal governments. Basin-scale hydropower relicensing has begun to receive attention as a potential solution for reducing licensing timelines, costs, and uncertainty which can provide benefits to a broad spectrum of participants in the licensing process. Two products were developed: (1) an interactive web map that allows users to browse facilities and rivers of interest and uncover locations for potential collaboration based on FERC relicensing metrics summarized along river reaches and (2) a spreadsheet that contains 1,261 facilities with associated FERC relicensing metrics and that allows users to join these data to others and develop and conduct their own analyses.

13 HYDRO ENERGY↗

DOE OSTI2022

A Simulation-based Method for Correcting Mode Coupling in CMB Angular Power Spectra

Modern cosmic microwave background (CMB) analysis pipelines regularly employ complex time-domain filters, beam models, masking, and other techniques during the production of sky maps and their corresponding angular power spectra. However, these processes can generate couplings between multipoles from the same spectrum and from different spectra, in addition to the typical power attenuation. Within the context of pseudo-C ℓ based, MASTER-style analyses, the net effect of the time-domain filtering is commonly approximated by a multiplicative transfer function, F ℓ , that can fail to capture mode mixing and is dependent on the spectrum of the signal. To address these shortcomings, we have developed a simulation-based spectral correction approach that constructs a two-dimensional transfer matrix, ${J}_{{\ell }{\ell }^{\prime} }$, which contains information about mode mixing in addition to mode attenuation. We demonstrate the application of this approach on data from the first flight of the Spider balloon-borne CMB experiment.

79 ASTRONOMY AND ASTROPHYSICS↗