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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Experimental Evidence on Latency in a Fleet of Controllable Water Heaters

Demand response is an important emerging part of smart grids with wide coverage in theoretical and modeling research. However, experimental evidence on the real-life behavior of controllable loads is still limited. We present observations regarding latency and communication aspects of the operation on a fleet of residential water heaters in a smart neighborhood in Atlanta, GA. Our analysis shows that latency in water heaters is not constant and does not follow a Gaussian distribution. We also find that there is a systematic relationship between latency and hour of the day. Latency was found to increase during morning and evening hours compared to the afternoon. These findings could help better plan deployment of control for demand response programs. Understanding delays associated with controlling smart devices is crucial for proper design and algorithm development for optimization, frequency of dispatch, and override detection.

communication delay↗
DOE OSTI2020

PdPt-TiO 2 nanowires: correlating composition, electronic effects and O-vacancies with activities towards water splitting and oxygen reduction

Here we report the optimization of both the support and the active phase of PdPt NPs supported on TiO 2 nanowires to obtain highly active electro/photocatalysts for the oxygen reduction and water splitting reactions. This system displayed strong metal-support interactions, high concentration of oxygen vacancies, and PdPt NP were ~2 nm in size. By optimizing the loading of PdPt, both the photo- and electrocatalytic activities were improved compared to commercial materials. Interestingly, a volcano plot was obtained from the activity and the PdPt composition, and the Pd 0.22 Pt 0.78 -TiO 2 /C sample afforded the optimal performance. For instance, the amount of hydrogen produced from water splitting was 11.6 mmol/g catalyst . For the ORR, the activity was similar to a commercial Pt catalyst, but a lower E onset (0.87 V RHE vs w 0.95 V RHE ) was detected. The variations in the activities with the composition correlated well with the variations in the electronic effects and the concentration of oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Identify and Assess Technical Challenges in Safeguards Measurements of Spent Advanced Reactor Fuels

Advanced reactor (AR) designs use various nuclear fuel types that can be significantly different than conventional light-water reactor (LWR) fuels, including differences in sizes, compositions, and chemical forms (e.g., oxide, carbide, metal). Nearly all the proposed AR fuels use high-assay low-enriched uranium (HALEU), which will have higher enrichments (5–20 wt% 235 U) than LWR fuels (currently limited to <5 wt% 235 U). In advance of the wide use of these new fuel types around the world, international safeguards organizations such as the International Atomic Energy Agency (IAEA]) are working with some of the AR vendors to formulate safeguards approaches for these AR fuel cycles. As part of the overall safeguards approach, it is important to identify the potential technical challenges in performing safeguards verification measurements of these AR fuels (both fresh and spent fuels) in advance of the widespread adoption of these new fuel types, because new safeguards technologies can take several years to develop, test, and approve for use. This report documents work performed in fiscal year 2024 based on modeling and simulation to assess the performance of the existing safeguards measurement technologies for irradiated or spent AR fuel elements or items. This work is a continuation of the work performed in fiscal year 2023 that focused on fresh AR fuels. Spent AR fuels have a distinct difference from their LWR counterparts: unlike the spent LWR fuels typically stored in a water-filled pool, some spent AR fuels—such as tristructural-isotropic (TRISO)-based fuels—will most likely be stored in air-filled hot cells. Because most safeguards measurements on spent fuel performed to date have been conducted under water, the air-filled hot cell environment could present unique challenges to safeguards measurements. Fork detector (FDET) and Cerenkov viewing device (CVD) systems have been the two primary instruments used by the IAEA for several decades to measure spent LWR fuel assemblies stored in pools for safeguards verification purposes. Because the lower refractive index of air causes Cerenkov light to be of lower intensity in air than in water, existing CVDs are likely unable to perform safeguards verification measurements for spent fuel stored in an air-filled hot cell, as is the case for the TRISO-based spent fuel elements (e.g., pebbles, graphite fuel blocks). Unlike FDET measurements, CVD measurements do not require fuel be moved, so they are a simpler and faster to take than FDET measurements. The inability to perform CVD measurements on the TRISO-based AR fuel types presents a major technical challenge in the effort to use existing technology to perform safeguards measurements on spent AR fuels. This study was mainly conducted through the modeling and simulation of an FDET or an FDET-like system on five spent AR fuel types, including one metallic fuel type and four TRISO-based fuel types in both pebble and graphite block forms in their respective storage configurations and environments. Because the various AR fuel types have significantly different dimensions, FDET systems must be adapted to accommodate them. Partial defect tests were also simulated in this study to assess the FDET’s ability to detect potential fuel diversions. The FDET measures the fuel’s total passive neutron and gamma emissions. The simulated FDET results from spent AR fuel items are compared against results from a typical spent pressurized water reactor (PWR) assembly. High-purity germanium (HPGe) gamma detector measurements were also simulated for the spent AR fuel types and the PWR assembly because the signature photopeaks have been used in LWR safeguards verifications, although HPGe is usually not used to detect diversions because of the fuel’s self-attenuation effects on those photopeaks. The results indicate that these detectors have significant challenges in performing safeguards measurements of the spent AR fuel items, including incompatibilities between AR fuel items and existing FDETs, lower neutron count rates, lower sensitivities to fuel diversions in certain AR fuel items, and significantly higher interference from a neighboring fuel item when the measurement is performed in air. These results suggest that an alternative technology or significant and timely technology development is needed to perform adequate safeguards measurements of some of these AR fuel items.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Soil organic matter diagenetic state informs boreal forest ecosystem feedbacks to climate change

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition of detrital inputs to soil over time – is useful for tracing the net response of SOC at the timescales relevant to climate change not usually discernible from fluxes and stocks alone. Here, we test two hypotheses using a mesic boreal forest climate transect: (1) the SOC diagenetic state is maintained across this climosequence, and (2) the maintenance of the SOC diagenetic state is a consequence of coupled soil C and N cycling, signifying the role of enhanced N cycling supporting SOC inputs that maintain SOC stocks within the warmer-climate forests. Shifts in nonvascular to vascular plant inputs with climate observed in these and other boreal forests highlighted the need to carefully separate biogeochemical indicators of SOC source from those signifying diagenetic alteration. We thus evaluated and applied lignin biomarkers to assess the diagenetic alteration of SOC in these boreal forest organic soils and directly compared the lignin diagenetic state with that of soil organic nitrogen (SON) assessed through amino acid composition. The lignin diagenetic state remained constant across the climate transect, indicating a balance between the input and removal of lignin in these mesic boreal forests. When combined with previous knowledge of these forest ecosystems, including the diagenetic state of SON and direct measures of C fluxes and stocks, the results indicate a coupled increase in C and N cycling with climate warming that supports forest productivity and maintains SOC stocks. This balance could markedly shift as other factors begin to limit forest productivity (e.g., trace nutrients, water) with further climate change or affect forest nutrient allocation (e.g., forest age or compositional change). Further application of the approach presented here could be used to detect the limits of this and other ecosystem–climate feedbacks, by providing a tractable and parameterizable index of the lignin state across large spatial scales, necessary for ecosystem-scale parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term cement hydration studies with isothermal calorimetry

The purpose of this study was to investigate for how long the thermal power of hydration can be measured with isothermal calorimetry, which is a general measurement technique with stable properties that, in many cases, can detect low rates of processes. Measurements were conducted for 365 days on cement paste with Portland cement, fly ash blended Portland cement and different water-to-binder ratios. The results showed that all the tested systems still produced a measureable signal after one year. The samples with Portland cement were also analyzed by XRD after 365 days, and phase composition calculations were made with GEMS. Together with the calorimetric results, these results were used to determine the degree of hydration by five methods, the results of which showed good agreement.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Pulse radiolysis and transient absorption spectra of aqueous solutions of sodium sulfamate

Chemical kinetics for the reactions of sulfamate ions (NH 2 SO 3 − ) with the primary products of water and nitric acid radiolysis were measured in aqueous solutions at ambient temperature. Using time-resolved electron pulse radiolysis techniques with a custom multichannel detection system, we examined the reactivity of NH 2 SO 3 − with the hydroxyl radical ( • OH), hydrogen atom (H • ), and nitrate radical (NO 3 • ). The sulfamate ion was found to react with • OH and H • with second-order rate coefficients of k • OH = (5.60 ± 0.04) × 10 6 M −1 s −1 and k H • = (7.96 ± 0.10) × 10 6 M −1 s −1 , respectively, and with NO 3 • with a rate coefficient of k NO 3 • = (1.67 ± 0.06) × 10 7 M −1 s −1 . The reactions of NH 2 SO 3 − with • OH and H • resulted in the formation of two transient radical species, one with maximum absorbance at 300 nm and a second with maxima at both 300 nm and 600 nm. These spectra are tentatively assigned to • NH 2 SO 3 and • NHSO 3 − , respectively. By measuring the absorbance of these radicals as a function of pH, the radical pK a was determined to be 9.5 ± 0.1. Overall, this work has implications for the longevity and performance of ferrous sulfamate, Fe(NH 2 SO 3 ) 2 , as a plutonium reductant in the reprocessing of used nuclear fuel.

Conrad, Jacy K. [Idaho National Laboratory (INL), ↗
DOE OSTI2021

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

A common strategy for the dimensionality reduction of nonlinear partial differential equations (PDEs) relies on the use of the proper orthogonal decomposition (POD) to identify a reduced subspace and the Galerkin projection for evolving dynamics in this reduced space. However, advection-dominated PDEs are represented poorly by this methodology since the process of truncation discards important interactions between higher-order modes during time evolution. In this study, we demonstrate that encoding using convolutional autoencoders (CAEs) followed by a reduced-space time evolution by recurrent neural networks overcomes this limitation effectively. We demonstrate that a truncated system of only two latent space dimensions can reproduce a sharp advecting shock profile for the viscous Burgers equation with very low viscosities, and a six-dimensional latent space can recreate the evolution of the inviscid shallow water equations. Additionally, the proposed framework is extended to a parametric reduced-order model by directly embedding parametric information into the latent space to detect trends in system evolution. Furthermore, our results show that these advection-dominated systems are more amenable to low-dimensional encoding and time evolution by a CAE and recurrent neural network combination than the POD-Galerkin technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The design, implementation, and performance of the LZ calibration systems

LUX-ZEPLIN (LZ) is a tonne-scale experiment searching for direct dark matter interactions and other rare events. It is located at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. The core of the LZ detector is a dual-phase xenon time projection chamber (TPC), designed with the primary goal of detecting Weakly Interacting Massive Particles (WIMPs) via their induced low energy nuclear recoils. Surrounding the TPC, two veto detectors immersed in an ultra-pure water tank enable reducing background events to enhance the discovery potential. Intricate calibration systems are purposely designed to precisely understand the responses of these three detector volumes to various types of particle interactions and to demonstrate LZ's ability to discriminate between signals and backgrounds. In this paper, we present a comprehensive discussion of the key features, requirements, and performance of the LZ calibration systems, which play a crucial role in enabling LZ's WIMP-search and its broad science program. The thorough description of these calibration systems, with an emphasis on their novel aspects, is valuable for future calibration efforts in direct dark matter and other rare-event search experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

From Pollutant Removal to Renewable Energy: MoS2-Enhanced P25-Graphene Photocatalysts for Malathion Degradation and H2 Evolution

The widespread presence of pesticides—especially malathion—in aquatic environments presents a major obstacle to conventional remediation strategies, while the ongoing global energy crisis underscores the urgency of developing renewable energy sources such as hydrogen. In this context, photocatalytic water splitting emerges as a promising approach, though its practical application remains limited by poor charge carrier dynamics and insufficient visible-light utilization. Herein, we report the design and evaluation of a series of TiO2-based ternary nanocomposites comprising commercial P25 TiO2, reduced graphene oxide (rGO), and molybdenum disulfide (MoS2), with MoS2 loadings ranging from 1% to 10% by weight. The photocatalysts were fabricated via a two-step method: hydrothermal integration of rGO into P25 followed by solution-phase self-assembly of exfoliated MoS2 nanosheets. The composites were systematically characterized using X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), UV-Vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) spectroscopy. Photocatalytic activity was assessed through two key applications: the degradation of malathion (20 mg/L) under simulated solar irradiation and hydrogen evolution from water in the presence of sacrificial agents. Quantification was performed using UV-Vis spectroscopy, gas chromatography–mass spectrometry (GC-MS), and thermal conductivity detection (GC-TCD). Results showed that the integration of rGO significantly enhanced surface area and charge mobility, while MoS2 served as an effective co-catalyst, promoting interfacial charge separation and acting as an active site for hydrogen evolution. Nearly complete malathion degradation (~100%) was achieved within two hours, and hydrogen production reached up to 6000 µmol g−1 h−1 under optimal MoS2 loading. Notably, photocatalytic performance declined with higher MoS2 content due to recombination effects. Overall, this work demonstrates the synergistic enhancement provided by rGO and MoS2 in a stable P25-based system and underscores the viability of such ternary nanocomposites for addressing both environmental remediation and sustainable energy conversion challenges.

Chemistry↗
DOE OSTI2020

Dielectric relaxation of neodymium chloride in water and in methanol

In this work, an open-ended coaxial probe was used to study the dielectric relaxation of neodymium chloride (NdCl 3 ) in water and in methanol at room temperature over the frequency range 0.2–40.0 GHz. An equivalent circuit model based on the antenna model was used to obtain the dielectric spectra with the effective removal of spurious effects. This extends the use of the open-ended coaxial probe technique for highly conductive substances. The structural and thermodynamic parameters obtained from the dielectric spectra of aqueous NdCl 3 solutions suggest that solvent-separated ion pairs and solvent-shared ion pairs dominate the low-frequency behavior at low concentrations. In methanol, solvent-shared ion pair relaxation modes were detected. No contact pair relaxation was observed in either solvent. Under all conditions, Nd 3+ was strongly solvated, as reflected by its high effective hydration number. The estimated association constant of NdCl 3 in water at infinite dilution was within the literature values and was lower than that observed in methanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Diversion Path Analysis: A Proposed Methodology to Develop an MC&A Approach for Liquid-Fueled Molten Salt Reactors

Nuclear material control and accounting (MC&A) is a critical element of both the US Nuclear Regulatory Commission (NRC) and US Department of Energy (DOE)’s domestic safeguards and security requirements. NRC licensees are required, under Title 10 of the Code of Federal Regulations (10 CFR) Part 74 to establish and maintain an MC&A program that captures and records the quantities and locations of special nuclear material (SNM) at the facility. Along with physical protection, MC&A is a key element of domestic nuclear material safeguards that enables the NRC to ensure that SNM is controlled and accounted for. SNM, per 10 CFR Part 74, refers to plutonium, 233 U, and uranium enriched in the isotope 233 U or 235 U, but does not include source material. Periodic physical inventories, coupled with material balance evaluations, are effective and demonstrated tools to account for and detect theft or diversion of SNM in facilities containing SNM in bulk material form (i.e., not in discrete, countable items). Historically in the United States, these types of facilities have included fuel fabrication, conversion, and enrichment facilities. In comparison, reactors have relied on item counting of assemblies and control of SNM while in containment (e.g., a sealed reactor pressure vessel) because, to date, reactor fuel has been in item form. In liquid-fueled molten salt reactors (MSRs), unlike traditional light water reactors (LWRs) or bulk facilities, bulk SNM quantities can change significantly during operation as a result of depletion and transmutation. This introduces challenges to the use of traditional periodic physical inventories and material balance evaluations to detect theft or diversion of SNM in reactors that use SNM in bulk material form. Liquid-fueled (i.e., salt-fueled) MSR facilities are MSRs that use SNM within a salt eutectic as the fuel. The SNM is in a bulk material form any time it is outside of fresh or spent fuel storage containers. Some examples of when SNM will be in bulk form in the facility are during addition of fuel to the reactor system, while fuel is circulating in operation, and while fuel is in a drain tank. Periodic physical inventories and material balance evaluations can likely be effectively applied to many portions of an MSR facility, including all areas where depletion and transmutation are not significantly changing the quantities of SNM within the control area. Within an MSR facility, this would include fresh fuel receipt and loading, waste streams that may contain SNM, irradiated fuel storage outside of the reactor core, and any irradiated fuel processing that may happen after SNM has been removed from the reactor. All of these process steps could rely on measurements of SNM quantities compared with documented inventories. Any discrepancies from predicted (i.e., book) inventories and measured inventories could be quantified as inventory differences, consistent with traditional MC&A guidance from the NRC (e.g., in NUREG-1065 Revision 2, NUREG-2159 Revision 1, and RG 5.29 Revision 2). Within the reactor system, additions and removals to the book inventory include depletion of the SNM (e.g., fission of 235 U), which complicates the use of physical inventories. SNM control, however, can also likely be effectively applied to detect theft of SNM throughout a liquid-fueled MSR facility. To complement these approaches, prior technical reports have identified that a diversion path analysis may be a useful, risk-informed, and performance-based tool to determine suitable elements of an MC&A approach for the reactor system within a liquid-fueled MSR facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

An Application of Faster R-CNNs in Object Detection Efforts Applied to the Critical Infrastructure Domain

Object detection and segmentation approaches have been successfully applied to multiple interdisciplinary domains ranging from medical imaging to autonomous vehicles. The following study details efforts to apply segmentation methods to the critical infrastructure domain. Specifically, the identification of critical sub-components of four facilities: airports, hospitals, hydroelectric dams, and water treatment plants. Data for this study was extracted from the U.S. Department of Agriculture’s National Agriculture Imagery Program data set. Each facility class was considered independently of the other facilities, producing four different segmentation models during the testing and training process. Ultimately, the study team concluded there are significant challenges associated with object detection modeling when applied to facility analysis within the critical infrastructure domain. The study team was able to identify possible sources of these challenges that could be potentially addressed in future work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

SpaceNet 8 - The Detection of Flooded Roads and Buildings

The frequency and intensity of natural disasters (i.e. wildfires, storms, floods) has increased over recent decades. Extreme weather can often be linked to climate change, and human population expansion and urbanization have led to a growing risk. In particular floods due to large amounts of rainfall are of rising severity and are causing loss of life, destruction of buildings and infrastructure, erosion of arable land, and environmental hazards around the world. Expanding urbanization along rivers and creeks often includes opening flood plains for building construction and river straightening and dredging speeding up the flow of water. In a flood event, rapid response is essential which requires knowledge which buildings are susceptible to flooding and which roads are still accessible. To this aim, SpaceNet 8 is the first remote sensing machine learning training dataset combining building footprint detection, road network extraction, and flood detection covering 850km 2, including 32k buildings and 1,300km roads of which 13% and 15% are flooded, respectively.

Arndt, Jacob↗
DOE OSTI2022

Insights on sources and formation mechanisms of liquid-bearing clouds over MOSAiC examined from a Lagrangian framework

Understanding Arctic stratiform liquid-bearing cloud life cycles and properly representing these life cycles in models is crucial for evaluations of cloud feedbacks as well as the faithfulness of climate projections for this rapidly warming region. Examination of cloud life cycles typically requires analyses of cloud evolution and origins on short time scales, on the order of hours to several days. Measurements from the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide a unique view of the current state of the central Arctic over an annual cycle. Here, we use the MOSAiC radiosonde measurements to detect liquid-bearing cloud layers over full atmospheric columns and to examine the cloud-generating air masses’ properties. We perform 5-day (120 h) back-trajectory calculations for every detected cloud and cluster them using a unique set of variables extracted from these trajectories informed by ERA5 reanalysis data. This clustering method enables us to separate between the air mass source regions such as ice-covered Arctic and midlatitude open water. We find that moisture intrusions into the central Arctic typically result in multilayer liquid-bearing cloud structures and that more than half of multilayer profiles include overlying liquid-bearing clouds originating in different types of air masses. Finally, we conclude that Arctic cloud formation via prolonged radiative cooling of elevated stable subsaturated air masses circulating over the Arctic can occur frequently (up to 20% of detected clouds in the sounding data set) and may lead to a significant impact of ensuing clouds on the surface energy budget, including net surface warming in some cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evidence for widespread thermal acclimation of canopy photosynthesis

Plants acclimate to temperature by adjusting their photosynthetic capacity over weeks to months. However, most evidence for photosynthetic acclimation derives from leaf-scale experiments. Here we address the scarcity of evidence for canopy-scale photosynthetic acclimation by examining the correlation between maximum photosynthetic rates (A max,2,000 ) and growth temperature $(\overline{T_{air}})$ across a range of concurrent temperatures and canopy foliage quantity, using data from >200 eddy covariance sites. We detect widespread thermal acclimation of canopy-scale photosynthesis, demonstrated by enhanced A max,2,000 under higher $\overline{T_{air}}$, across flux sites with adequate water availability. A 14-day period is identified as the most relevant timescale for acclimation across all sites, with a range of 12-25 days for different plant functional types. The mean apparent thermal acclimation rate across all ecosystems is 0.41 (-0.38-1.04 for 5th-95th percentile range) µmol m -2 s -1 °C -1 , with croplands showing the largest acclimation rates and grasslands the lowest. Incorporating an optimality-based prediction of leaf photosynthetic capacities into a biochemical photosynthesis model is shown to improve the representation of thermal acclimation. Our results underscore the critical need for enhanced understanding and modelling of canopy-scale photosynthetic capacity to accurately predict plant responses to warmer growing seasons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Equipartition and the Temperature of Maximum Density of TIP4P/2005 Water

Here, we simulate TIP4P/2005 water in the temperature range of 257 to 318 K with time-steps δ = 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density–temperature behavior obtained using 0.25 or 0.50 fs is in excellent agreement with each other but differs from those obtained using time steps that have been shown earlier to lead to a breakdown of equipartition. For δt = 0.25 or 0.50 fs, the temperature of maximum density (TMD) is 277.15 K and the density value is in close agreement with experiments. For δt = 1.00 fs, the TMD is 277.15 K, but the density value is shifted higher. For the other time steps considered here, the TMD is shifted to progressively lower values for longer time steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water–water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid–vapor phase envelope. We present a simple physically transparent explanation that highlights the separation of the time scales between translational and rotational motion. We also develop a metric, χ, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating χ is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time steps (≤0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct ensemble sampling is fundamental to ensure reproducibility across codes and simulation algorithms.

Asthagiri, Dilipkumar N. [Oak Ridge National Labor↗
DOE OSTI2024

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

High-Throughput Uniformity and Defect Monitoring in Low-Temperature Electrolysis Porous Transport Layers Using X-Ray Radiography

Effective quality control (QC) for manufacturing proton exchange membrane water electrolysis (PEMWE) components is critical to enabling widespread adoption of the technology for hydrogen generation. This study investigates X-ray radiography as a novel, high-throughput, potentially in-line QC technique for detecting defects and assessing material property distributions in titanium-based porous transport layers (PTLs) which constitute a crucial component of low temperature PEMWE stacks. We obtain radiographs of a set of fifteen PTLs and model their absorbance of the broadband radiation as a second-order polynomial to account for the non-monoenergetic radiation source used in this study. The resulting model serves as a basis for predicting the areal density and porosity distributions of the PTLs. We find radiography successful in detecting multiple instances of defects, including holes/depressions, cracks, and excess material on the surface or in the pores of the material, demonstrating its potential as a robust in-line QC tool for PTL manufacturing.

08 HYDROGEN↗