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Technology Development for Dry Storage of Aluminum-Clad Spent Nuclear Fuel - 20490

A candidate disposition pathway for the > 13 MTHM of aluminum-clad spent nuclear fuel (ASNF), owned and managed by the U.S. Department of Energy, is the drying and placement of the SNF into sealed-canister dry storage, with the ASNF-in- canisters 'road-ready' for transportation to and final direct disposal in a repository waste package. Technical information gaps in fuel drying, and fuel dry storage behavior, have previously challenged the declaration of technology readiness for drying and placement of this fuel into the DOE Standard Canister design for > 50 years of safe dry storage. The principal technical information gaps included: i) characterization and thermal dehydration behavior of aluminum (oxy)hydroxide films attendant on the cladding due to film formation during reactor operation and during post-discharge up to long-term wet storage histories; and ii) G-value data to enable estimation of the radiolytic gas generation from the cladding with its (oxy)hydroxide films. Thus, the oxide films on the ASNF challenged the safety of a sealed storage canister with thermal and radiolytic decomposition of the waters on the films that can lead to corrosion, pressurization, and flammability issues. These gaps in the technical information base have largely been closed. This paper discusses the investigations at the Idaho National Laboratory (INL) and the Savannah River National laboratory (SRNL), and outlines the pending technology development work for input to an engineering design to enable a road-ready dry storage system for ASNF. The ASNF inventory considered for road-ready dry storage is stored at the Savannah River Site (SRS) and at the Idaho Nuclear Technology and Engineering Center (INTEC) at the INL. The ASNF inventory in the SRS L Basin is from foreign and domestic research reactors (FRR and DRR), and is diverse in terms of design, irradiation, and post-reactor-discharge storage conditions; these factors yield a range of characteristics of cladding oxide films on ASNF. Mixed aluminum (oxy)hydroxide (boehmite and bayerite/gibbsite) films, non-uniform in thicknesses up to a maximum local thickness bounded by 25 μm, were observed on ASNF materials removed from wet storage in the L Basin and in non-sealed dry storage at the SRS following reactor service and a long-term (up to 40+ years) interim storage history. The ASNF inventory at INTEC, in both wet and vented dry storage, is predominantly from the Advanced Test Reactor (ATR), but it also includes DRR and FRR fuel. To address a profound behavior of these films, radiolysis testing of aluminum specimens with mixed type boehmite/bayerite oxide films was performed to develop basic data on G-values for production of radiolytic hydrogen under dry storage conditions with nominal relative humidity, temperature, and cover gas. Modeling and simulation of canister internal environments with postulated inventories of oxide films provides estimation of the evolution of the conditions of the canister loaded with ASNF. Simultaneous Thermal Analysis (TGA/DSC) of hydrated oxide powders, and laboratory-scale aluminum specimens with a bayerite film (∼10 μm) using TGA methods, inform drying time/temperature conditions to be used for the ASNF. A demonstration project is recommended for Verification and Validation of the drying and storage of the ASNF. Remaining major tasks leading up to the hot demonstration include scale-up radiolysis testing and scale-up drying testing. Engineering design with the information from the technology program will establish the safety basis and enable long-term (> 50 years) dry storage compatibility with ASNF in the DOE Standard Canister pending its transportation to and disposal in a repository. This full capability would show the ASNF-in-canister storage system to be road-ready. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Composite Analysis for Low-Level Waste Disposal in the Hanford Site Central Plateau (FY 2020) (Rev. 2)

This document provides an updated Hanford Site composite analysis (CA). A Hanford Site CA was prepared and issued in 1998 (PNNL-11800) with an addendum provided in 2002 (PNNL-11800 Addendum 1). The CA was approved in 2002 (Frei, 2002) and has been maintained (DOE/RL-2000-29 and subsequent revisions) to support low-level waste disposal performance assessments (PAs) and disposal authorizations for facilities at the Hanford Site, including the following: Continued operation of the Environmental Restoration Disposal Facility (ERDF) and the 200 East and 200 West Low-Level Burial Grounds; Construction of the Integrated Disposal Facility (IDF); Forthcoming closure of tank residual waste systems such as Waste Management Area (WMA) C. The CA maintenance program resulted in a determination in 2015 (DOE/RL-2015-66) that the Hanford Site CA needed an update for the following reasons: While the initial Hanford Site CA has been maintained since 2001, the accumulation of basis changes reported in the annual summary reports over the succeeding 14 years merit evaluation in an updated analysis; The U.S. Department of Energy (DOE) Headquarters requested in a memorandum in 2015 (Gilbertson and Marcinowski, 2015) that “as soon as the relevant PAs are complete, the CA will be revised to account for all of the new information.” This updated Hanford Site CA accounts for the following new information: 1. Inclusion of a detailed Hanford Site baseline disposition that projects remedial activities through site closure. There have been significant changes through decision making in the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) process that were not available when the original CA was produced; 2. Inclusion of an updated inventory basis, new modeling capabilities, and new decisions reached in the associated record of decision (ROD) that was provided by issuance of DOE/EIS-0391 in fiscal year (FY) 2013. Development of a Hanford Site groundwater model from the baseline provided in a technical transfer of models for the Final Tank Closure and Waste Management Environmental Impact Statement (DOE/EIS-0391) commenced in FY 2014 and resulted in the plateau-to-river (P2R) groundwater flow model that is used in this updated Hanford Site CA; 3. Accounting for pump and treat systems, which were not evaluated in the initial CA. Pump and treat systems have had significant impact on groundwater flow system behavior, contaminant transport, and contaminant removal from Hanford Site groundwater. This process is accounted for in the use of the P2R model for this updated Hanford Site CA; 4. Inclusion of water-level data collected since the initial CA was completed. Data collected as the unconfined aquifer water levels continue to recede since the cessation of large liquid discharges in the late 1990s have led to marked improvement in understanding of the flow system for future conditions, particularly regarding northward flow potential in the critical Gable Gap area. The calibration in the latest version of the P2R model accounts for this information; 5. Inclusion of results from the revised ERDF PA completed in 2013 (WCH-5209) that account for updated inventory and expansion of the ERDF facility to about twice the size that was evaluated in the original CA; 6. Use of updated geoframeworks to provide the structural basis for numerical fate and transport models in the groundwater pathway of this updated CA. The geologic basis for groundwater models has continued to improve with additional data collection and interpretation with the creation and maintenance of the Hanford South Geoframework and the Central Plateau Vadose Zone Geoframework tools; 7. Incorporation of updated tank residual inventory estimates. Tank residual inventory estimates have improved with the incorporation of tank retrieval inventory data for those tanks that have completed retrieval. The CA inventory data package includes this updated information; 8. Incorporation of WMA C PA results. Two additional PAs for tank farm closure decisions are in preparation during the period required to prepare an updated Hanford Site CA: WMA C (FY 2016) and WMA A-AX (in preparation). The WMA C PA results are incorporated into the updated Hanford Site CA, and its grouted residuals model is used as the basis for a release model to account for the other tank farm systems modeling in this updated CA; 9. An update to the IDF PA was submitted in FY 2017 and has been reviewed and approved. The results of the IDF PA are incorporated into this updated CA; 10. Updated risk assessment scenarios. The risk assessment scenarios currently in use for Hanford Site CERCLA and Resource Conservation and Recovery Act of 1976 (RCRA) analyses differ from those evaluated in the initial Hanford Site CA. The representative person exposure scenario evaluated in this updated Hanford Site CA is consistent with recent PAs and CERCLA and RCRA analyses as the Hanford Site. This updated Hanford Site CA provides the following: A comparison of the updated Hanford Site CA all-pathway dose results with the performance measures during the compliance period, which is assumed to begin with site closure in calendar 2070 with the last scheduled disposal action and continue for 1,000 years postclosure (to calendar year 3069); A comparison of Hanford Site CA all-pathway dose results with the performance measures during the postcompliance period to address potential peaks beyond the compliance period. This is accomplished by evaluating dose in the period for 9,000 years following the compliance period (i.e., from calendar year 3070 to 12070).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Shared micromobility as a first- and last-mile transit solution? Spatiotemporal insights from a novel dataset

The first- and last-mile (FM/LM) problem is a major deterrent to public transit use. With the rise of shared micromobility options such as shared e-scooters in recent years, there is a growing interest in understanding their potential to serve as a last-mile transit solution. However, empirical data regarding the integrated use of shared micromobility and public transit have been limited so far. As a result, much is unknown regarding the spatiotemporal patterns and characteristics of shared micromobility trips serving as an FM/LM connection to transit. Here, this paper addresses these knowledge gaps by leveraging a novel dataset (i.e., the Spin post-ride survey dataset) that records thousands of transit-connecting shared e-scooter trips in Washington DC. Specifically, we used the dataset to reveal the spatiotemporal patterns of transit-connecting shared e-scooter trips in Washington DC, resulting in some major policy insights regarding the integral use of shared e-scooters and public transit. We further leveraged the dataset to validate if and to what extent a commonly applied buffer-zone approach can infer FM/LM micromobility trips accurately. Statistical tests showed that the actual FM/LM Spin e-scooter trips differ from inferred FM/LM Spin e-scooter trips in both spatial and temporal dimensions. This indicates that the common practice of inferring FM/LM micromobility trips with a buffer-zone approach can lead to inaccurate estimates of transit-connecting micromobility trips.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A High-Throughput Solver for Marginalized Graph Kernels on GPU

Here, we present the design and optimization of a solver for efficient and high-throughput computation of the marginalized graph kernel on General Purpose GPUs. The graph kernel is computed using the conjugate gradient method to solve a generalized Laplacian of the tensor product between a pair of graphs. To cope with the large gap between the instruction throughput and the memory bandwidth of the GPUs, our solver forms the graph tensor product on-the-fly without storing it in memory. This is achieved by using threads in a warp cooperatively to stream the adjacency and edge label matrices of individual graphs by small square matrix blocks called tiles, which are then staged in registers and the shared memory for later reuse. Warps across a thread block can further share tiles via the shared memory to increase data reuse. We exploit the sparsity of the graphs hierarchically by storing only non-empty tiles using a coordinate format and nonzero elements within each tile using bitmaps. We propose a new partition-based reordering algorithm for aggregating nonzero elements of the graphs into fewer but denser tiles to further exploit sparsity. We carry out extensive theoretical analyses on the graph tensor product primitives for tiles of various density and evaluate their performance on synthetic and real-world datasets. Our solver delivers three to four orders of magnitude speedup over existing CPU-based solvers such as GraKeL and GraphKernels. The capability of the solver enables kernel-based learning tasks at unprecedented scales.

97 MATHEMATICS AND COMPUTING↗

The Influence of Soil Properties on Sea-Breeze Circulations in the Southeast U.S.

Sea-breeze circulations (SBCs) are common weather phenomena at and near coastal regions. They form because of a thermal gradient between the land surface at the coast and the sea surface. In a mid-day regime, a “thermal low” generated at the warm coast will lead to rising air motion, creating a wind shift coming from the sea near the surface displacing the coastal air. A “return flow” moving back towards the sea is generated by upper-level divergence because of the rising motion from the thermal low. SBCs propagate and serve as a method of urban pollutant dispersion in the Los Angeles region of California and are constrained to the coast due to the topography of surrounding mountains serving as a boundary for further inland propagation. Within the northeast U.S. SBCs are seen in the warm season but tend to remain coastally bound due to Coriolis distortion over long distances. Within the southeast U.S. (SEUS), the paradigmatic example of SBCs occurs over the Florida peninsula, where thunderstorms form on a nearly daily occurrence due to the convergence of SBCs from the east and west sides of the peninsula. However, there are further examples of sea-breezes in the SEUS that warrant study. Within the region bordering the SEUS and the Mid-Atlantic, just east of the southern Appalachian Mountains, warm-season SBCs form at the coast of Georgia and the Carolinas. Relatively flat topography ~150-200km inland allows for mostly unimpeded inland SBC propagation. Through visual analysis, Viner et al. catalogued several SBCs that propagated as far inland as the Central Savannah River Area surrounding Augusta, Georgia. Wermter et al. found that while the land-sea thermal gradient at the coast can influence coastal SBC genesis, the inland-coastal thermal gradient over the land is the primary influencer on the speed and depth of inland propagation of SBCs in this region. Additionally, soil moisture itself is a known correlative factor to sea-breeze formation, as it influences the soil temperature and the thermal gradient needed for SBC genesis and inland penetration. Physick determined that higher latent heat fluxes associated with wetter soil dampen the land-sea thermal gradient and suppress the formation of a SBC. Physick determined that higher latent heat fluxes associated with wetter soil dampen the land-sea thermal gradient and suppress the formation of a SBC. Conversely, drier soil enhances the thermal gradient and promotes SBC formation. However, while there is an inverse relationship between soil moisture and SBCs, higher soil moisture can actually promote more convective rainfall following a SBC if it does not significantly impact the thermal gradient. While the relationship between soil moisture and SBC formation has been conceptually explored and modeled numerically, there is a research gap in observed connections. The Soil Moisture Active Passive (SMAP) satellite mission has been operational since 2015 and has been used to create high-resolution re-analytical Level 4 (L4) datasets of soil moisture and soil temperature at different soil depths: the surface (0-5cm) and rootzone (0-1m). The surface soil temperature effectively acts as the “skin temperature” of the surface at these levels, and a spatial map of the land-sea as well as the coastal-inland thermal gradients can be represented. SMAP data are also assimilated in some atmospheric models such at the High Resolution Rapid Refresh (HRRR) mesoscale model. We propose leveraging the use of SMAP products to fill in spatial gaps left by weather and mesonet stations within the SEUS region, as well as assessing the effectiveness of utilizing SMAP products towards SBC forecasting in both deterministic and machine learning (ML) models.

58 GEOSCIENCES↗

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗

Data From: "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater"

This repository contains the data and code associated with the paper titled "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater," published in Nature Geoscience, 2026. This study seeks to answer how various ages of groundwater interact with mountainous streamflow in mountainous headwaters such as the East River. It includes various model-data processing scripts, primarily for ParFlow-CLM analysis of simulated water years 2015-2021, and two numerical warming experiments (+2.5 and +4.0 degrees C), including run scripts, forcing scripts, and post-processing, as well as comparison to observation datasets, detailed below. This data requires the use of R (.r, .rmd), Python (.py), Jupyter Notebook or Jupyter Lab (.ipynb), ParFLOW-CLM, EcoSLIM. Further information on the use of all file formats mentioned below (e.g. .tff. .nc) are provided within the associated scripts and directory where the files are located. Contents & Usage ASO/: ​​Contains the bash and python scripts used to convert airborne snow observatory (ASO) data (ASO, 2023) in various data formats (georeferenced tiff file, NetCDF, UTM, and to latitude/longitude) then regrided to the ParFlow equivalent grid. Output data are in regrid_regll_data.zip and subsequently visualized and analyzed in plot_and_compare.py for Supplementary Figures A14 and A15. The wksht_ASO_comparison.xlsx spreadsheet is used to calculate the data for Supplementary Figure A16. EcoSLIM/: Contains the scripts and input files to run the EcoSLIM particle tracking simulations (/run_scripts) and the post-processing python script (/plot_scripts/eco_agedist_plots.ipynb). Jasechko et al./: Contains the jupyter notebook (Extract_Elevation.ipynb) to determine the outlet elevations of the 260 watersheds used in Jasechko et al. (2016), and the corresponding table, Table_S1_Watersheds_alt.csv. Used to create Supplementary Information Figure A2. PLM_Wells/: Contains the QA/QC-ed groundwater level time series of the PLM-1 and PLM-6 Monitoring Wells from Faybishenko et al. (2023), reformatted to water years used for Supplementary Figures A19 and and A20. ParFlow/: Contains the input files and run scripts to run ParFlow-CLM (/run_scripts), the python and tool command language (Tcl) scripts to create and distribute the ParFlow forcing simulation files (/forcing), and various scripts and intermediary files to analyze the model outputs (/post_process). SQUIRE/: Contains the processing scripts and intermediary files for the Surface QUantitatIve pRecipitation Estimation (SQUIRE) data (Grover, 2023) used to generate Supplementary Figure A18. USGS_Streamflow/: Contains the raw and gap-filled United States Geological Survey streamflow data (U.S. Geological Survey, 2026) used at the Almont station (site number 09112500). Gap-filling is performed in the R script with data from the Taylor station (site number 09110000). (/USGS_09112500_EAST_RIVER_AT_ALMONT_GAP_FILLED/code_almont_streamflow_gap_fill.Rmd). discharge/: Contains the gap-filled discharge data at the Watershed Function SFA East River pumphouse site (Newcomer et al., 2022) used to generate Supplementary Figure A13 and to compute hourly Nash-Sutcliffe model efficiency coefficients (NSE) in Table A4. snotel_and_flux_tower/: Contains the snow telemetry data (U.S. Department of Agriculture, 2024) from the Butte (site ID 380) and Schofield (site ID 737) stations, reformatted by water year, accessed with the snotelr R package. Used to create Supplementary Figure A17. Also contains the flux tower observational data (FluxTower_Pumphouse_ESS-DIVE.ET_only.h.txt) from Ryken et al. (2022) and sap flux transpiration data (MaxB_Transpiration_5Sites.daily_sums.h.txt) from Ryken (2021), used to create Supplementary Figures A22 and A23, respectively. Raw EcoSLIM model outputs are in excess of 24TB, and are stored on National Energy Research Scientific Computing Center (NERSC) and publicly available via the external link provided in the paper.

atmospheric warming↗

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗

Data for Clumping Index Estimation With 30°-tilted Cameras in Row Crops: Evaluation of Methods and Segment Size Effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

Modeling↗

Demystifying asynchronous I/O Interference in HPC applications

With increasing complexity of HPC workflows, data management services need to perform expensive I/O operations asynchronously in the background, aiming to overlap the I/O with the application runtime. However, this may cause interference due to competition for resources: CPU, memory/network bandwidth. The advent of multi-core architectures has exacerbated this problem, as many I/O operations are issued concurrently, thereby competing not only with the application but also among themselves. Furthermore, the interference patterns can dynamically change as a response to variations in application behavior and I/O subsystems (e.g. multiple users sharing a parallel file system). Without a thorough understanding, I/O operations may perform suboptimally, potentially even worse than in the blocking case. To fill this gap, here we investigate the causes and consequences of interference due to asynchronous I/O on HPC systems. Specifically, we focus on multi-core CPUs and memory bandwidth, isolating the interference due to each resource. Then, we perform an in-depth study to explain the interplay and contention in a variety of resource sharing scenarios such as varying priority and number of background I/O threads and different I/O strategies: sendfile, read/write, mmap/write underlining trade-offs. The insights from this study are important both to enable guided optimizations of existing background I/O, as well as to open new opportunities to design advanced asynchronous I/O strategies.

97 MATHEMATICS AND COMPUTING↗

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗

Climate-Related Trends of Within-Storm Intensities Using Dimensionless Temporal-Storm Distributions

Huff curves are probabilistic time distributions of rainfall expressed as dimensionless cumulative percentages of storm depth and duration. Previous studies have documented development factors, spatial robustness, and the utility of Huff curves in practical applications. However, the effects of trending rainfall on Huff curve intensity patterns have not yet been studied. As such, the goal of this paper is to fill this gap by studying Huff curve patterns in a watershed with demonstrated increasing trends of temperature and precipitation, with the intention that it can be generalized to other areas in the US and the world. To achieve this goal, the high temporal resolution precipitation data collected from a high spatial density, 72-year precipitation-gauge network on the 4.25-km 2 North Appalachian Experimental Watershed in east-central Ohio were used. Seasonal storm pattern trends from 1939 to 2010 were investigated using dimensionless depth (with the frequency of 50%, $d_{50}$) and the curve variability $(V = d_{80} - d_{20})$ at three dimensionless within-storms time periods (three verticals). The Spearman rank correlation procedure (correlation coefficient, ρ and significance probability, p) was used to statistically determine trends over time using 8 periods of 4-season sets of Huff curves over the 72 years. Two averages of ρ and p were computed: (1) by averaging the individual ρ and p obtained from 10 gauges (AvgI); and (2) by grouped averaging of all individual gauge values of $d_{50}$ and V and then computing ρ and p (AvgG). The test results of individual gauges showed that 4 cases for $d_{50}$ and 23 cases for V were significant for all seasons and verticals (total of 120 cases for each variable). The test results of AvgI for $d_{50}$ and V and AvgG for $d_{50}$ showed no significant trends in all seasons and verticals. Only the AvgG for V led to a significant trend for V in spring and fall at different times within storm patterns. The data do not provide sufficient evidence at the p=0.05 significance level to reject the null hypothesis of unchanging position of the dimensionless depth of the 50% Huff curves for individual or averages for all seasons and verticals. Also, there is insufficient evidence to reject the null hypothesis of unchanging variability, V, using the average ρ of individual gauges (AvgI for V) for all seasons and verticals. AvgG results showed a significant trend in V; however, this analysis may be affected by the nonindependence of storm data. The results suggest that it is likely that there is little if any effect of trending climate over approximately 70 years on Huff curve patterns. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Also, individual rain gauge data may not be representative of trends even over small areas, and seasonal differences were noticeable as found in other studies. Recommendations are provided.

54 ENVIRONMENTAL SCIENCES↗

Development of a BlueCRAB/MELCOR Framework for Supporting Realistic Mechanistic Source Term Calculations in Microreactors

Efforts are currently underway to deploy microreactor modeling and simulation tools to better support vendors and regulatory authorities in submitting and reviewing licensing applications. In particular, the Nuclear Regulatory Commission is expected to rely on the Comprehensive Reactor Analysis Bundle (BlueCRAB) multiphysics toolset in performing design- and beyond-design-basis accident analyses. In addition, the Nuclear Regulatory Commission has been using the MELCOR code to estimate mechanistic source terms during accidents. As MELCOR relies on isotopic inventory and reactor temperature/power evolution profiles during accident conditions—all of which can theoretically be obtained from BlueCRAB—the ultimate goal of this activity is to establish a common BlueCRAB-MELCOR framework. However, prior to the present research, BlueCRAB had never been used to calculate such quantities of interest at the full-core level. While there are many Monte Carlo (MC) codes capable of computing such quantities of interest, they are unable to readily account for multiphysics feedback. BlueCRAB allows for the coupling of different physics codes together to perform multiphysics-informed calculations. Therefore, the purpose of this fiscal year 2023 work is to investigate the feasibility and challenges of performing such calculations within BlueCRAB so as to generate the data that MELCOR relies on. To demonstrate the methodology, the proposed workflow was applied to a prototypical heat pipe-cooled microreactor model. To predict isotopic concentrations (taking into account the ac- cumulation of fission products during operation), the necessary microscopic cross sections were generated via OpenMC and tabulated with respect to temperature and burnup. Next, a recently developed capability in Griffin (the reactor physics application in BlueCRAB) was used to convert the OpenMC output format into the ISOXML format used by Griffin. A multiphysics microscopic depletion calculation that involved performing a coupled full-core, heterogeneous neutron trans- port and thermal calculation at each depletion step was conducted to deplete the core to end of life (EOL) conditions so as to provide both isotopics and the initial condition for the transient calculation. Following a brief null-transient to verify that the initial condition had been properly restarted and was indeed in thermal equilibrium, a heat pipe failure transient was simulated. Thus, the entire workflow of using BlueCRAB to generate MELCOR inputs, from cross-section generation to producing isotopic inventory and power/temperature evolution profiles during transients, is demonstrated. This report also details the identified gaps in the workflow and how they were (for the most part) addressed. Future work should focus on directly including MEL- COR into the workflow by performing a MELCOR calculation using the BlueCRAB-generated input data. In addition, the heat pipe reactor design should be improved so as to reflect more prototypical burnup characteristics at EOL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cost of Fish Exclusion and Passage Technologies for Hydropower

Hydropower represents a reliable source of renewable energy and accounts for approximately 7% of the total electrical generation in the United States. Future expansion of hydropower is likely to be in the form of either smaller new stream development projects or powering existing non-powered dams. For these new projects to be successful, careful analysis of risks, costs, and uncertainty to offset reduced power production as well as ensuring the protection and safe passage of migratory fish to gain public support, will be required. Exclusion and passage are two common approaches to protect fish from entrainment and impingement at hydropower facilities. The thresholds for entrainment risk and requirements for exclusion and passage often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders. While the costs associated with environmental mitigations represent a large proportion of the total costs required for the licensing of hydropower facilities, little quantitative information is present within the literature regarding the specific costs of fish exclusion and passage. Working with FOA awardee Natel Energy, scientists at Oak Ridge National Laboratory were tasked with assessing the capital construction costs for downstream fish exclusion and passage infrastructure. This report used keyword searches of an existing environmental mitigation cost data set and manual extraction of additional cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening and passage from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 PM&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens, 142 pertaining to passage studies, and 26 pertaining to passage-related studies. PM&E measures associated with positive barrier screens represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with new stream development (NSD) projects. Results from these data indicate highly variable costs associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1 to 2 in.). Furthermore, estimated capital costs of passage infrastructure were positively related to the scale of the project based on installed capacity for some, but not all, types of passage. These data provide an initial baseline for estimating exclusion and passage costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects. More data may still be available within the FERC eLibrary, but significant effort will be required to manually identify and extract the data for future analyses.

13 HYDRO ENERGY↗

An Energy Codes Gap Analysis Field Study in the Southwest (Final Technical Report)

The primary goal of the “An Energy Codes Gap Analysis Field Study in the Southwest” project was to improve housing through strengthened building energy code implementation in two states, Colorado and Nevada, leading to greater energy and utility bill savings for households. Colorado is a home rule state. Nevada adopts a statewide code, but cities and counties must also adopt the code, making the state function like a home rule state. To broaden the impact of the project, an additional goal was to share and amplify project experiences, findings, and lessons that can be applied in other states. To achieve these goals, the project’s key objectives were to examine how residential energy codes are implemented in partner states; to use these findings to strengthen codes implementation through enhanced education, training, and outreach; and to enhance energy code technical assistance capabilities in the two partner states. In both partner states, the project led to the creation of a quantitative baseline understanding of compliance with high-impact energy code requirements, such as foundation, wall, and ceiling R-value; window U-factor and SHGC; envelope air tightness; duct tightness; and high-efficiency lighting. It then applied this baseline information to directly inform training in geographic areas with high levels of building and construction activity. The project has placed Colorado and Nevada among 23 states across the country that have conducted a single-family residential field study based on the established U.S. Department of Energy (DOE) methodology since 2014. It has also helped each State Energy Office test models for partnership- and relationship-building among government agencies and key stakeholder groups, including the State Energy Office and relevant code administration and professional licensing agencies, building officials, designers, builders, trades and utilities. At the national level, the project helped educate and inform State and Territory Energy Offices on a replicable methodology to assess energy code construction practices, effective stakeholder engagement strategies, and tailored energy code education and training. These findings are particularly pertinent for home-rule states, such as Colorado and Nevada, which rely on local government awareness and action to advance and implement building energy codes. By raising awareness of code adoption and compliance, this project has helped to equip each partner state with data on code compliance, strategies, education, and partnership models to advance building energy codes. This in turn will have an important impact on new construction practices in Colorado and Nevada, leading to more energy efficient and affordable housing. Currently, more than 62 percent of Colorado’s population lives in one of the 55 jurisdictions that have adopted the 2021 IECC to date, while nearly 95 percent of the state's population lives in one of the 208 jurisdictions that have adopted a code at 2015 IECC levels or higher. In Nevada, the 2018 IECC was adopted by the Governor’s Office of Energy in July 2018. By July 2020, 47 percent of the adopted energy code in the state was 2018 IECC which covers 96.5 percent of Nevada’s population. The training materials funded by this project focus on the 2021 IECC and will continue to be relevant in the two states as additional jurisdictions update their building energy codes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quantifying UAS Observation Error Variance Used in Data Assimilation Systems and Its Impact on Predictive Skill

Observation error determines the weights of the observations and background state used in data assimilation to generate analyses. Quantifying observation error is critical for the optimal assimilation of observational data sets. Uncrewed Aircraft System (UAS) observations have shown potential benefits in filling observational gaps in the lower atmosphere; however, characterization of their error characteristics has been limited. To optimize the use of UAS observations in numerical weather prediction, UAS observation error is estimated based on the 3‐cornered hat diagnostic approach which uses three independent estimates of the atmospheric state. This approach is applied to data from the 2018 Lower Atmospheric Profiling Studies at Elevation‐a Remotely‐piloted Aircraft Team Experiment field campaign using collocated UAS and rawinsonde observations along with output from a set of convection‐permitting model simulations. The estimated observation error values for UAS temperature, wind, and relative humidity measurements were found to be only weakly dependent on height AGL with mean values equal to 0.5°C, 0.8 m s −1 , and 3%, respectively. Only the newly estimated observation error for temperature differed from that previously used to assimilate commercial aircraft observations into global models (1.0°C). However, using this reduced temperature observation error produced more accurate mesoscale analyses and forecasts of both terrain‐driven flows and convection initiation generated by colliding outflow boundaries within the San Luis Valley of Colorado.

54 ENVIRONMENTAL SCIENCES↗

Origin of Ferromagnetic Exchange Coupling in Donor–Acceptor Biradical Analogues of Charge-Separated Excited States

A new donor–acceptor biradical complex, Tp Cum,Me Zn(SQ-VD) (Tp Cum,Me Zn + = zinc(II) hydro-tris(3-cumenyl-5-methylpyrazolyl)borate complex cation; SQ = orthosemiquinone; VD = oxoverdazyl), which is a ground-state analogue of a charge-separated excited state, has been synthesized and structurally characterized. Here, the magnetic exchange interaction between the S = 1/2 SQ and the S = 1/2 VD within the SQ-VD biradical ligand is observed to be ferromagnetic, with $J_{SQ-VD}$ = +77 cm –1 (H = -2$J_{SQ-VD}\bar{S}_{SQ}·\bar{S}_{VD}$) determined from an analysis of the variable-temperature magnetic susceptibility data. The pairwise biradical exchange interaction in Tp Cum,Me Zn(SQ-VD) can be compared with that of the related donor–acceptor biradical complex Tp Cum,Me Zn(SQ-NN) (NN = nitronyl nitroxide, S = 1/2), where $J_{SQ-NN}$ ≅ +550 cm –1 . This represents a dramatic reduction in the biradical exchange by a factor of ~7, despite the isolobal nature of the VD and NN acceptor radical SOMOs. Computations assessing the magnitude of the exchange were performed using a broken-symmetry density functional theory (DFT) approach. These computations are in good agreement with those computed at the CASSCF NEVPT2 level, which also reveals an S = 1 triplet ground state as observed in the magnetic susceptibility measurements. A combination of electronic absorption spectroscopy and CASSCF computations has been used to elucidate the electronic origin of the large difference in the magnitude of the biradical exchange coupling between Tp Cum,Me Zn(SQ-VD) and Tp Cum,Me Zn(SQ-NN). A Valence Bond Configuration Interaction (VBCI) model was previously employed to highlight the importance of mixing an SQ SOMO → NNLUMO charge transfer configuration into the electronic ground state to facilitate the stabilization of the high-spin triplet (S = 1) ground state in Tp Cum,Me Zn(SQ-NN). Here, CASSCF computations confirm the importance of mixing the pendant radical (e.g., VD, NN) LUMO (VD LUMO and NN LUMO ) with the SOMO of the SQ radical (SQ SOMO ) for stabilizing the triplet, in addition to spin polarization and charge transfer contributions to the exchange. An important electronic structure difference between Tp Cum,Me Zn(SQ-VD) and Tp Cum,Me Zn(SQ-NN), which leads to their different exchange couplings, is the reduced admixture of excited states that promote ferromagnetic exchange into the Tp Cum,Me Zn(SQ-VD) ground state, and the intrinsically weaker mixing between the VD LUMO and the SQ SOMO compared to that observed for Tp Cum,Me Zn(SQ-NN), where this orbital mixing is significant. The results of this comparative study contribute to a greater understanding of biradical exchange interactions, which are important to our understanding of excited-state singlet–triplet energy gaps, electron delocalization, and the generation of electron spin polarization in both the ground and excited states of (bpy)Pt(CAT-radical) complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗