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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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160 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Experimental comparison of pyranometer, reflectometer, and spectrophotometer methods for the measurement of roofing product albedo

Albedo (solar reflectance) can be measured outdoors with a pyranometer or indoors with a hemispherical reflectometer or a spectrophotometer. The current study evaluates these methods and their applicability to roofing materials by measuring and comparing the ASTM E1918 (pyranometer), non-ASTM E1918A (alternative pyranometer), ASTM C1549 (reflectometer), and E903 (spectrophotometer) albedos of 10 roofing products, including three single-ply membranes, one asphalt shingle, three roofing aggregates, and three high-profile tiles. It uses full-size (4 m × 4 m) assemblies in the E1918 and E1918A trials; corrects the E1918 albedos to remove shadow and background errors; and evaluates C1549 and E903 albedos with two different irradiance spectra, one global horizontal and the other beam normal. E1918A albedos matched E1918 corrected (E1918_cor) albedos to within 0.036. Furthermore, agreement between C1549 air mass 1 global horizontal (C1549_G1) albedo and E1918_cor albedo was within 0.015 for membrane and shingle coupons, and within 0.031 for aggregates, though the uncertainty in the latter agreement was up to 0.043. After minor corrections, C1549_G1 albedos of flat or slightly convex tile chips were 0.032–0.052 higher than the E1918_cor albedos of their corresponding high-profile tile assemblies because high-profile surfaces have concavities. Switching to the beam-normal albedo C1549_1.5E increased the C1549 albedos of the 10 tested products by 0.004–0.054, with the largest increases (C1549_1.5E – C1549_G1) accruing to spectrally selective cool colors. Using C1549_1.5E albedo to characterize a chip of a cool-colored tile compounded the error induced by representing a high-profile surface by a flat or slightly convex specimen.

14 SOLAR ENERGY↗
DOE OSTI2022

Leading-color two-loop amplitudes for four partons and a $\textit{W}$ boson in QCD

We present the leading-color two-loop QCD corrections for the scattering of four partons and a W boson, including its leptonic decay. The amplitudes are assembled from the planar two-loop helicity amplitudes for four partons and a vector boson decaying to a lepton pair, which are also used to determine the planar two-loop amplitudes for four partons and a $Z/γ^\ast$ boson with a leptonic decay. The analytic expressions are obtained by setting up a dedicated Ansatz and constraining the free parameters from numerical samples obtained within the framework of numerical unitarity. The large linear systems that must be solved to determine the analytic expressions are constructed to be in Vandermonde form. Such systems can be very efficiently solved, bypassing the bottleneck of Gaussian elimination. Our results are expressed in a basis of one-mass pentagon functions, which opens the possibility of their efficient numerical evaluation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity)

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity) project aims to demonstrate a novel, scalable method for removing carbon dioxide (CO 2 ) directly from ambient air and delivering it to cyanobacterial cultures to produce commodity biofuel, mid-value protein for supplements, and high value phycocyanin (PC), a natural blue colorant (Figure A). This approach uses low-cost, reusable anion exchange polymers embedded in modular mesh packets, which capture CO 2 during drying cycles when exposed to ambient air, and release concentrated CO 2 into aqueous cultivation systems. The project addresses a critical challenge in energy research needed for developing sustainable, economically viable methods of Direct Air Capture (DAC) that can be integrated with bio-based systems for fuel and chemical production. AUDACity contributes to scientific understanding by integrating materials chemistry, cyanobacterial biology, and system engineering to create a distributed CO 2 delivery platform. Key insights have emerged around the design of biocompatible sorbents, optimization of CO 2 capture-release cycles, and durability of packet-based delivery systems under outdoor conditions. Notably, the team has synthesized and tested a range of polymer sorbents, identified mechanisms of material degradation and fouling, and advanced both lab- and pilot-scale cultivation systems to evaluate performance. From a technical and economic standpoint, AUDACity shows promise for achieving cost-effective CO 2 capture and delivery into aqueous media and biofuel production. Preliminary techno-economic analysis (TEA) indicates that the DAC system based on current performance can reach $\$$680/tonne CO 2 delivered into aqueous solution; with reasonable improvements to sorbent lifetime, sorbent capacity, reducing water uptake the approach could reach $\$$66/tonne by avoiding the need for energy-intensive sorbent regeneration and CO 2 compression, making it more feasible for decentralized deployment. With these costs for CO 2 and by extracting and selling high-value PC ($\$$50/kg) and mid-value protein supplement ($\$$6/kg), the remaining biomass can be hydrothermally treated into biofuel for $\$$2.50/gallon, and would support a small first-of-a-kind biorefinery capable of producing 500 barrels per day of biofuel. The project offers meaningful public benefits by advancing carbon removal technologies that are low-energy, modular, and adaptable to non-arable land and brackish water use. It aligns with national goals to develop advanced biotechnology and supports future pathways for bio-based fuels and products. By enabling direct coupling of CO 2 transfer into aqueous medium and biological carbon utilization, AUDACity lays the groundwork for effective algae cultivation without wasteful CO 2 delivery and is a promising and innovative solution for low-carbon fuel and bioproduct generation contributing to a vigorous bioeconomy.

09 BIOMASS FUELS↗
DOE OSTI2020

Stellar Mass and Stellar Mass-to-light Ratio–Color Relations for Low Surface Brightness Galaxies

We estimate the stellar mass for a sample of low surface brightness galaxies (LSBGs) by fitting their multiband spectral energy distributions (SEDs) to the stellar population synthesis model. The derived stellar masses (log M {sub *}/M {sub ⊙}) span from 7.1 to 11.1, with a mean of log M {sub *}/M {sub ⊙} = 8.5, which is lower than that for normal galaxies. The stellar mass-to-light ratio (γ*) in each band varies little with the absolute magnitude but increases with higher M {sub *}. This trend of γ* with M {sub *} is even stronger in bluer bands. In addition, the γ* for our LSBGs slightly declines from the r band to the longer-wavelength bands. The log γ{sub ∗}{sup j} (j = g, r, i, and z) have relatively tight relations with optical colors of g − r and g − i. Compared with several representative γ*–color relations (MLCRs) from the literature, our MLCRs based on LSBG data are consistently among those literature MLCRs previously defined on diverse galaxy samples, and the existing minor differences between the MLCRs are caused by the differences in the SED model ingredients (including initial mass function, star formation history, and stellar population model), line fitting techniques, galaxy samples, and photometric zero-point, rather than the galaxy surface brightness itself, which distinguishes LSBGs from high surface brightness galaxies. Our LSBGs would be very likely to follow those representative MLCRs previously defined in diverse galaxy populations, if those main ingredients were taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

EI_MS_ML

The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation. Substructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit. Determining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.

Mitchell, Joshua↗
DOE OSTI2022

The Use of Thermal Cameras for Pedestrian Detection

Visible-range camera sensors have been widely used for pedestrian detection. However, most of the methods, which employ visible-range color cameras, do not perform well under low-light and no-light conditions, e.g. during night time. Since the working principle of thermal camera sensors is mainly based on temperature and not light, they have been employed for person detection to overcome the drawbacks of visible-range sensors under these conditions. Every object gives off thermal energy, which is captured by a thermal camera sensor. When an object becomes hotter, it emits more thermal energy, and is therefore captured as much brighter or vice versa. Yet, compared to visible-range cameras, there are many additional challenges that need to be addressed when detecting pedestrians from thermal camera images. These challenges include bright hot objects close to humans, similar pixel values in an image due to weather conditions, or objects that block thermal cameras such as concrete or glass. Glass acts like a mirror for infrared radiation and reflects whatever is in front of the camera. Thus, novel methods are still required to accomplish pedestrian detection task from thermal camera images. To contribute to these efforts, we propose a new method and a modified object detection network incorporating saliency maps of thermal camera images. The features obtained from thermal images and their corresponding saliency maps are combined to obtain richer representations of pedestrian regions, and better detection performance. We perform extensive evaluations on five different datasets to compare the performance of the proposed approach with two baselines. Moreover, we evaluate and compare the transferability of these approaches by doing leave-one-out cross validation across different datasets. Furthermore, the results show that the proposed approach outperforms the baselines, and has better transferability properties across different thermal image datasets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Using Host Galaxy Photometric Redshifts to Improve Cosmological Constraints with Type Ia Supernovae in the LSST Era

We perform a rigorous cosmology analysis on simulated Type Ia supernovae (SNe Ia) and evaluate the improvement from including photometric host galaxy redshifts compared to using only the "z spec " subset with spectroscopic redshifts from the host or SN. We use the Deep Drilling Fields (~50 deg 2 ) from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC) in combination with a low-z sample based on Data Challenge2. The analysis includes light-curve fitting to standardize the SN brightness, a high-statistics simulation to obtain a bias-corrected Hubble diagram, a statistical+systematics covariance matrix including calibration and photo-z uncertainties, and cosmology fitting with a prior from the cosmic microwave background. Compared to using the z spec subset, including events with SN+host photo-z results in (i) more precise distances for z > 0.5, (ii) a Hubble diagram that extends 0.3 further in redshift, and (iii) a 50% increase in the Dark Energy Task Force figure of merit (FoM) based on the w 0 w a CDM model. Analyzing 25 simulated data samples, the average bias on w 0 and w a is consistent with zero. The host photo-z systematic of 0.01 reduces FoM by only 2% because (i) most z < 0.5 events are in the z spec subset, (ii) the combined SN+host photo-z has ×2 smaller bias, and (iii) the anticorrelation between fitted redshift and color self-corrects distance errors. To prepare for analyzing real data, the next SN Ia cosmology analysis with photo-zs should include non–SN Ia contamination and host galaxy misassociations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Investigation of Superluminescent Diodes for Smart Lighting Systems. Final Report

The solid-state lighting ecosystem has evolved very rapidly over the last few years, with significant improvements in the technical performance of light-emitting diodes (LEDs) and the commoditization of LED-based lighting fixtures. As the performance of conventional lighting products begins to saturate, there is growing market interest in “Lighting as a Service” applications that will leverage advanced systems to impart new functionalities to lighting and improve energy efficiency, human health, and productivity. These “Smart Lighting” systems will include high-performance light sources, specialized sensors, and dynamic controls to deliver high quality, energy efficient, color tunable lighting with customized spatial light delivery and integrated visible light communication capability. To achieve these capabilities, smart lighting systems will place greater demands on the performance of light sources. Highly efficient sources with additional functionalities compared to conventional LEDs, such as small form factor, large modulation bandwidth, and spatially coherent output beams, will be required. While laser diodes have been proposed as potential sources for smart lighting systems, they also exhibit several properties that pose challenges, such as temporal coherence, extremely high spatial coherence, and ultra-narrow linewidths. To address these issues, we propose an investigation of an alternative device architecture known as a superluminescent diode (SLD). SLDs are similar in form to ridge laser diodes and share many of the same characteristics, such as stimulated emission operation, spatially coherent output, small form factor, and the potential for large modulation bandwidth. However, the operating principle for SLDs is distinct from laser diodes in that SLDs lack a strong cavity feedback mechanism, resulting in spatially coherent but temporally incoherent light output. Thus, SLDs may address the issues with laser diodes for lighting, while simultaneously maintaining some of the desirable characteristics of both laser diodes and LEDs. The objectives of this proposal are to design, grow, and fabricate blue (450 nm) SLDs on polar c-plane and nonpolar m-plane free-standing GaN substrates, and to evaluate their potential as sources in smart lighting systems through basic device characterization and detailed investigations of their efficiency droop and modulation bandwidth. The primary scientific aims of this work are to understand the fundamental role of optical gain in the superluminescent (non-lasing) regime on efficiency droop and modulation bandwidth in III-nitride emitters and to understand the effects of higher optical gain on SLD performance by comparing polar c-plane and nonpolar m-plane SLDs. The University of New Mexico (UNM) will collaborate with Sandia National Laboratories (SNL) and the Center for Integrated Nanotechnologies to design, fabricate, grow, and characterize the SLDs. UNM will perform the design and epitaxial growth, while SNL will focus on the fabrication and device characterization. The novelty of the proposed work includes the first comprehensive theoretical and experimental investigations of efficiency droop and the first investigation of modulation bandwidth in GaN-based emitters operating in the superluminescent regime. Moreover, the comparison of c-plane and m-plane SLDs will enable the first analysis of the effects of higher optical gain on the device performance. The development of high-performance GaN-based SLDs may enable efficiency gains and improved functionality in next-generation smart lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Analysis of Solids Obtained from 201O, 201P, 202A, and 202B Contactors in the Salt Waste Processing Facility

In December 2022, Savannah River Mission Completion personnel recovered solids samples from four contractors (EXT-001, EXT-007, EXT-031, and EXT-040) employed at the Salt Waste Processing Facility (SWPF). These solids were submitted to Savannah River National Laboratory for analysis and characterization. This Technical Report outlines the analytical findings and observations associated with these samples and explores the potential source of solid generation within the SWPF. The following conclusions are offered as a result of this work: the light color solids recovered from EXT-007 are consistent with crystallized, soluble salt components (such as sodium nitrate, sodium hydroxide, and sodium carbonate), all of which can be easily re-dissolved in process water and do not represent a threat to SWPF CSSX processing. While the light solids from the top of EXT-040 were not analyzed, it is believed that they share similar characteristics to those recovered from EXT-007; The dark color solids recovered from EXT-001, EXT-031, and the inside of EXT-040 appear to be complex, consisting of several different types of solids: High concentrations of mercury (Hg, 40-75% by mass) partially present as elemental Hg are consistent with the precipitation of Hg 0 /Hg 2+ from disproportionation of Hg + species in pH swing conditions; Moderate concentrations of titanium (Ti) (2-7%, by mass) are also present, often co-located with Hg. This is consistent with co-precipitation, entrainment, and/or amalgamation of Ti and Hg; Moderate concentrations of iron (Fe) (1-3%, by mass) are observed in SWPF solids and are likely attributable to erosion of stainless-steel components within the CSSX process; Small concentrations of tungsten (W) and cobalt (Co) (<1%, by mass) are observed in SWPF solids. The presence of these solids is consistent with the erosion of components coated with W and Co (e.g., Stellite); Small concentrations of aluminum (Al) (<1%, by mass) are observed in the form of gibbsite and potentially sodium aluminosilicate. The presence of these compounds is likely attributable to the pH swing observed between the scrub and extraction cycles within the CSSX process. The following recommendations are made as a result of this work: Testing should be performed to determine the chemical drivers, process, and mechanism of Hg precipitation in CSSX processing. Special care should be taken to include titanium in tests to evaluate the potential for co-precipitation, entrainment, and amalgamation; Hg-mitigation options that would minimize or eliminate risks of Hg precipitation and solids accumulation (e.g., Hg-absorption techniques, ion exchange/adsorbents, flowsheet changes, etc.) should be assessed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Clarifying the trophic state concept to advance macroscale freshwater science and management

For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use‐specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based on autotrophic production, whereas phosphorus, dissolved organic carbon, and true color are used to classify TS based on both autotrophic and heterotrophic production. Both classification approaches aim to characterize an ecosystem's function broadly, but with varying degrees of autotrophic and heterotrophic processes considered in those characterizations. Moreover, differing classification schemes can create inconsistent interpretations of ecosystem integrity. For example, the US Clean Water Act focuses exclusively on algal threats to water quality, framed in terms of eutrophication in response to nutrient loading. This usage lacks information about non‐algal threats to water quality, such as dystrophication in response to dissolved organic carbon loading. Consequently, the TS classification schemes used to identify eutrophication and dystrophication may refer to ecosystems similarly (e.g., oligotrophic and eutrophic), yet these categories are derived from different proxies. These inconsistencies in TS classification schemes may be compounded when interdisciplinary projects employ varied TS frameworks. Even with these shortcomings, TS can still be used to distill information on complex aquatic ecosystem function into a set of generalizable expectations. The usefulness of distilling complex information into a TS index is substantial such that usage inconsistencies should be explicitly addressed and resolved. To emphasize the consequences of diverging TS classification schemes, we present three case studies for which an improved understanding of the TS concept advances freshwater research, management efforts, and interdisciplinary collaboration. To increase clarity in TS, the aquatic sciences could benefit from including information about the proxy variables, ecosystem type, as well as the spatiotemporal domains used to classify TS. As the field of aquatic sciences expands and climatic irregularity increases, we highlight the importance of re‐evaluating fundamental concepts, such as TS, to ensure their compatibility with evolving science.

classification↗
DOE OSTI2020

Spitzer Variability Properties of Low-gravity L Dwarfs

We present Spitzer Space Telescope variability monitoring observations of three low-gravity L dwarfs with previous detections of variability in the near-IR: 2MASS J0045+16, 2MASS J0501–00, and 2MASS J1425–36. We detect significant periodic variability in two of our targets, 2MASS J0045+16 and 2MASS J0501–00. We do not detect variability in 2MASS J1425–36. Combining our new rotation periods with rotational velocities, we calculate inclination angles of 22° ± 1°, 60{sub -8}{sup +13°}, and 52{sub -13}{sup +19°} for 2MASS J0045+16, 2MASS J0501–00, and 2MASS J1425–36, respectively. Our three new objects are consistent with the tentative relations between inclination, amplitude, and color anomaly previously reported. Objects with the highest variability amplitudes are inclined equator on, while the maximum observed amplitude decreases as the inclination angle decreases. We also find a correlation between the inclination angle and (J–K){sub 2MASS} color anomaly for the sample of objects with measured inclinations. Compiling the entire sample of brown dwarfs with Spitzer variability detections, we find no enhancement in amplitude for young, early-L dwarfs compared to the field dwarf population. We find a possible enhancement in amplitude of low-gravity late-L dwarfs at 4.5 μm. We do not find a correlation between amplitude ratio and spectral type for field dwarfs or for the young population. Finally, we compile the rotation periods of a large sample of brown dwarfs with ages 1 Myr–1 Gyr and compare the rotation rates predicted by evolutionary models assuming angular momentum conservation. We find that the rotation rates of the current sample of brown dwarfs fall within the expected range set by evolutionary models and breakup limits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Qualitative Risk Assessment of Legacy Wells within the Estimated Prairie State Generating Company Area of Review

This report details the digitization of a legacy wellbore database, including data processing assumptions, parameter estimation, and risk assessment methodology. The database, comprising 6,454 documents, was provided by ISGS. It includes valuable data from the Prairie State Generating Company (PSGC) and One Earth Energy (OEE) sites of the CarbonSAFE Phase III – Illinois Storage Corridor project. The report focuses on wells within a 15-mile radius from the Lively Grove #1 (LG#1) well at PSGC site, evaluating subsurface conditions and potential risks. A total of 4,386 wellbores within 15 miles of the LG#1 well were filtered based on depth and formation codes. LG#1 is the stratigraphic well at the PSGC site drilled in 2021. Ninety-four (94) wells penetrating the Maquoketa Shale Group (the primary confining unit) within the estimated area-of-review (AoR) for the PSGC site were evaluated using a qualitative risk assessment (QRA) methodology. The QRA developed by Arbad et al. 2022 focuses on legacy wells within the AoR and categorizes them based on well construction details. The QRA identifies wells that need immediate attention by categorizing them based on penetration depth and protection. Wells within the AoR were categorized into nine groups based on penetrations and protections. These categories range from Type 1 wells, with no documentation, to Type 9 wells, which do not penetrate the primary confining unit or storage reservoir (unit). Well accessibility within the AoR varies based on well status, including Dry & Abandoned (DA), Plugged & Abandoned (PA), Injection (INJ), Oil/Gas Producing (PROD), and Observation (Obs) wells. Accessibility levels were determined by well construction, with DA wells being the least accessible and Observation wells the most accessible, impacting gas leakage detection possibilities. Remedial action priority of wells decreases from Type 1 to Type 9 wells. Type 1 to Type 6 wells with status DA and PA require immediate attention, while Type 7 and Type 8 wells are low priority. A risk matrix used to prioritize corrective actions for legacy wells is proposed to categorize wells within an AoR based on penetrations, protections, and accessibility. The methodology involves data acquisition, well categorization into nine types, and determining CO 2 leakage pathways using well schematics and geospatial mapping. This approach is particularly useful for managing the integrity of legacy wells throughout the lifecycle of a Carbon Capture and Storage (CCS) project. A qualitative risk assessment of 94 wells within the AoR of the PSGC site identified 54 wells with high priority for corrective action due to penetration of the primary containment seal. The assessment utilizes color-coded maps to categorize well types and prioritize corrective actions, providing a comprehensive analysis. Schematics of wells penetrating the primary confining unit were drawn, and leakage pathways were identified. Details of all wells penetrating the confining zone are provided in the appendix, including information on well types, plugging, and casing status.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗
DOE OSTI2025

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Remote sensing images, DEM, and point clouds associated with “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds”

This data package is associated with the publication “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds” published in Frontiers in Environmental Science, Environmental Informatics and Remote Sensing (Bao et al., 2026; doi: 10.3389/fenvs.2026.1725258). This data package includes the drone photos for a section of Umtanum Creek in Washington, Unted States. The photos were used to reconstruct the 3-dimensional (3D) digital elevation model (DEM) of the riverbed for the investigated stream section. The reconstruction results from four approaches are provided: (1) unoccupied aerial vehicle (UAV, colloquially known as drone) imagery-based Structure-from-Motion (SfM), (2) a machine learning-based 3D reconstruction model, Visual Geometry Grounded Deep Structure from Motion (VGGSfM), (3) Visual Geometry Grounded Transformer for long sequence of images (VGGT-Long), and (4) handheld smartphone LiDAR scanning. The ground truth measurements by tripod-mounted optical level kit and ground control points GPS locations for evaluating the accuracy of the four reconstruction approaches are also provided in this data package. A preliminary version of this data package was published in October 2025 at the time of manuscript submission. It was updated in March 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) 8 folders; (2) the detailed flight configuration html files; (3) field metadata; (4) a readme; (5) a data dictionary; and (6) file-level metadata. The folders “2024_10_18_d01” and “2024_10_18_d02” contain the original drone photos for the two drone flights (d01 and d02) on October 18, 2024. The reconstruction results from each of the approaches are in the folders called “ODM_SfM”, “VGGSfM”, “VGGTLong”, and “LiDAR”. The ground truth measurements are in the folder called “optical_level_kit”. Lastly, results comparing the different approaches are in the folder called “comparisons”. All files are .csv, .html, .jpg, .obj, .txt, and .npy. For information on using the .obj and .npy files, see the readme files within the same folder as the files.

54 ENVIRONMENTAL SCIENCES↗