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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗
DOE OSTI2026

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗
DOE OSTI2024

Monsoonal MCS Initiation, Rainfall, and Diurnal Gravity Waves over the Bay of Bengal: Observation and a Linear Model

Abstract Previous observational studies have indicated that mesoscale convective systems (MCSs) contribute the majority of precipitation over the Bay of Bengal (BoB) during the summer monsoon season, yet their initiation and propagation remain incompletely understood. To fill this knowledge gap, we conducted a comprehensive study using a combination of 20-yr satellite observations, MCS tracking, reanalysis data, and a theoretical linear model. Satellite observations reveal clear diurnal propagation signals of MCS initiation frequency and rainfall from the west coast of the BoB toward the central BoB, with the MCS rainfall propagating slightly slower than the MCS initiation frequency. Global reanalysis data indicate a strong association between the offshore-propagating MCS initiation frequency/rainfall and diurnal low-level wind perturbations, implying the potential role of gravity waves. To verify the hypothesis, we developed a 2D linear model that can be driven by realistic meteorological fields from reanalysis. The linear model realistically reproduces the characteristics of offshore-propagating diurnal wind perturbations. The wind perturbations, as well as the offshore propagation signals of MCS initiation frequency and rainfall, are associated with diurnal gravity waves emitted from the coastal regions, which in turn are caused by the diurnal land–sea thermal contrast. The ambient wind speed and vertical wind shear play crucial roles in modulating the timing, propagation, and amplitude of diurnal gravity waves. Using the linear model and satellite observations, we further show that the stronger monsoonal flows lead to faster offshore propagation of diurnal gravity waves, which subsequently control the offshore propagation signals of MCS initiation and rainfall. Significance Statement Rainfall over the Bay of Bengal (BoB) is primarily contributed by large and organized rainfall systems in the summer monsoon season. During this season, these systems are commonly observed over the east coast of India around midnight, the western BoB in the morning, and the central BoB in the afternoon. This eastward rainfall propagation is confirmed by observations, reanalysis data, and a theoretical model to have a strong association with atmospheric diurnal gravity waves. These waves are caused by land–sea thermal contrast and can trigger rainfall systems over the offshore regions. We also found that the diurnal gravity waves, as well as their triggered rainfall systems, can be greatly modulated by the large-scale monsoonal flows. All the above findings improve our understanding of diurnal rainfall cycle over the BoB and may contribute to the future improvement of rainfall forecast over the region.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Advancing the utility of Data flow accelerators: Kokkos backend for Next Silicon

Next Silicon provides a novel reconfigurable accelerator, which is inherently a high-risk, early exploration effort. Higher readiness level for running NNSA mini-apps and initial mission applications on a data-flow accelerator Enable and demonstrate a new Kokkos back-end that directly drives an underlying dataflow accelerator

Garcia de Gonzalo, Simon Pedro [Sandia National La↗
DOE OSTI2025

A Parameter-masked Mock Data Challenge for Beyond-two-point Galaxy Clustering Statistics

The past few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge named “Beyond-2pt,” initiated during the Aspen 2022 Summer Program “Large-Scale Structure Cosmology beyond 2-Point Statistics,” whose first round of results we present here. The challenge data set consists of high-precision mock galaxy catalogs for clustering in real space, in redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown (“masked”) cosmological parameters of the underlying ΛCDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available, and we welcome future submissions from methods that are not yet represented.

Krause, Elisabeth [Univ. of Arizona, Tucson, AZ (U↗
DOE OSTI2025

dCache: The Storage System of Choice for Data-Intensive Applications

The ever-increasing volumes of data produced by modern scientific facilities like EuXFEL and LHC put significant stress on data management infrastructure operated by laboratories and research centers. The challenges to be addressed span the entire data life cycle, from ingest and efficient data analysis to long-term preservation, typically involving large tape libraries. dCache, a storage system developed in collaboration between the Deutsches Elektronen-Synchrotron (DESY), Fermi National Accelerator Laboratory, and Nordic e-Infrastructure Collaboration (NeIC), is designed to manage a large number of disk servers and to facilitate transparent data migration to and from archival storage. Its multifaceted approach offers a unified method to support a variety of scientific use cases with the same storage infrastructure, including high-throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters, and long-term data preservation on tertiary storage. Initially developed for high energy physics (HEP) experiments, dCache is now used by various scientific communities, including astrophysics, biomedical research, and life sciences, each having specific requirements. This paper presents architecture, deployment strategies, performance and scalability enhancements, and recent advancements in dCache addressing the needs of scientific communities. Finally, we touch on the development and release process, ensuring the software’s high quality.

DCache↗
DOE OSTI2026

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗
DOE OSTI2025

Enhancing Automotive Intrusion Detection Through Multi-Modal Fusion: A CAN FD-LiDAR Approach

As vehicles become smarter and more autonomous, they increasingly depend on advanced sensors and communication technologies to operate securely. However, such growing dependence on technology—whether it’s CAN (Controller Area Network) for internal communication or LiDAR (Light Detection and Ranging) for sensing the world around them—also expands the attack surface for the types of cyber attacks. Traditional intrusion detection systems (IDS) typically monitor these systems in isolation, limiting their ability to detect sophisticated, crosssystem attacks. To address this, we propose a multi-modal fusion approach that combines real-world CAN FD signals (from the HCRL dataset) with LiDAR features (from the nuScenes dataset) to enhance attack detection. Our method employs a twostage ensemble approach. Calibrated XGBoost and LightGBM models initially process CAN FD (Fuzzing Data) and LiDAR data independently, detecting timing anomalies and space abnormalities. They are subsequently logarithmically combined with a logistic regression meta-model along with 17 engineered features capturing cross-modal behavior, prediction conflicts, and nonlinear interactions. This approach achieves an AUC of 0.87 and an F1-score of 0.82, surpassing single-modality baselines and early fusion methods, at merely 2 ms inference latency. Compared with deep learning competitors, it is 3 times more efficient, providing a lightweight, interpretable, and real time solution to automotive cybersecurity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

In vitro selection and analysis of SARS-CoV-2 nirmatrelvir resistance mutations contributing to clinical virus resistance surveillance

To facilitate the detection and management of potential clinical antiviral resistance, in vitro selection of drug-resistant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) against the virus M pro inhibitor nirmatrelvir (Paxlovid active component) was conducted. Six M pro mutation patterns containing T304I alone or in combination with T21I, L50F, T135I, S144A, or A173V emerged, with A173V+T304I and T21I+S144A+T304I mutations showing >20-fold resistance each. Biochemical analyses indicated inhibition constant shifts aligned to antiviral results, with S144A and A173V each markedly reducing nirmatrelvir inhibition and M pro activity. SARS-CoV-2 surveillance revealed that in vitro resistance–associated mutations from our studies and those reported in the literature were rarely detected in the Global Initiative on Sharing All Influenza Data database. In the Paxlovid Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients trial, E166V was the only emergent resistance mutation, observed in three Paxlovid-treated patients, none of whom experienced COVID-19–related hospitalization or death.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

RxnRover/amlro

AMLRO (Active Machine Learning Reaction Optimizer) is an open-source framework designed to accelerate chemical reaction optimization using active learning with classical machine learning regression models. AMLRO integrates space-filling sampling strategies (e.g., Sobol and Latin Hypercube sampling) with iterative model training, prediction, and experiment selection to efficiently navigate complex reaction spaces. The platform supports multiple regression models, flexible multi-objective definitions, and user-defined parameter bounds, enabling data-efficient optimization from small initial datasets. AMLRO is designed for ease of use by experimentalists and can operate as a standalone decision-support tool or be integrated into closed-loop automated experimentation workflows.

Kulathunga, Dulitha Prasanna [Iowa State Universit↗
DOE OSTI2024

Influence of Antarctic and Greenland Continental Shelf Circulation on High‐Latitude Oceans in E3SM

The science objectives of this project are to simulate and understand the impacts of both deep-basin warm-water intrusions and land-ice melt on the continental shelf circulations and sea-ice distributions around the margins of Greenland and Antarctica. As well, the role of subsurface ocean heat from the Atlantic on declining sea-ice cover in the Arctic is explored. Mesoscale processes and fine bathymetry are implicated in cross-shelf property transports around both Greenland and Antarctica. Therefore, we configured and ran an atmospheric reanalysis-forced global ocean/sea-ice simulation on a grid that reduces from 8 km at the Equator to 2 km at the poles (UH8to2) with 60 vertical levels. It was produced using the Energy Exascale Earth System Model ‘‘HiLAT’’ code (E3SMv0-HiLAT) that uses the Parallel Ocean Program (POP) and CICE5 as its ocean and sea-ice components, respectively. Two main UH8to2 simulations were carried out: one for 1975-2009 and the other for July 2016-2020 after it was initialized from a 1/25° data-assimilative ocean/sea-ice prediction system ocean/sea-ice state. The UH8to2 is not coupled to an active land-ice model. Rather, land-ice melt is represented by observationally informed freshwater fluxes (FWFs). Short (multi-year) UH8to2 simulations were conducted to understand sensitivities when Greenland ice sheet (GrIS) melt is released only at the ocean surface or when it is distributed over the upper water column in accordance with fjord melt plume behavior; these cases were compared with a no GrIS melt case. West Greenland continental shelf currents were fastest in the vertical distribution case and an increase in baroclinic conversion at the shelf break associated with increased eddy kinetic energy was found relative to the surface release case. Further, salinity is lower and meltwater volume greater in the eastern Labrador Sea in the vertical distribution case. For the Arctic, the veracity of the UH8to2 was evaluated for 2017-2020 using available observations. Simulated seasonal sea-ice thickness and concentration are realistic, but the ice is unrealistically thin in the central and eastern Arctic in the fall. Comparisons of vertical sections of ocean temperature, salinity, and buoyancy collected from Ice-Tethered Profilers (ITPs) in the eastern Arctic in the fall and winter of 2019/2020 and co-located/concurrent UH8to2 fields show the stratification over the top 100 m of the water column is too low in the model, the simulated mixed layer too deep, and the simulated subsurface Atlantic Water (AW) too warm; these biases may contribute to the sea-ice biases. A model intercomparison study using the UH8to2 and a forced 1/25° regional Arctic ocean/sea-ice (uses the HYbrid Coordinate Ocean Model and CICE5) simulation further investigates the relationship between AW and sea-ice in the eastern Arctic. The models show a mesoscale-rich pulse of Atlantic Water extending into the eastern basin that reaches maximum intensity in late winter of 2018, after which it decreases in strength. Concurrent and co-located sea-ice melt or the inhibition of sea-ice growth is seen and is attributed to halocline mesoscale eddies doming into the mixed layer with convection bringing this heat into the vicinity of the sea-ice.

58 GEOSCIENCES↗
DOE OSTI2024

FY24 Report on Water NSTF Testing: Lower Tank Inlet Piping Configuration

The following report serves as a summary of the accomplishments and testing results by the Natural convection Shutdown heat removal Test Facility (NSTF) experimental program over the past 12-month period. A major activity included reconfiguration of the chimney piping geometry which altered the discharge position into the tank from the original 50% tank height to a new lower position at a 10.9% tank height. This modification increases the volume of available coolant thus extending long-term operating capacity, however also results in a decreased liquid driving head which has the potential to reduce the natural circulation efficiency and decrease overall performance. Examination of the tradeoffs for these two configurations is an area of interest for RCCS designers and drove planned test activities this year. Ten matrix tests were performed in FY24, totaling 195 hours of heated operations and 12.9 MWh of electrical heating throughout the year, with eight classified as Accepted per NQA-1 and two classified as Trending. Testing prior to the facility reconfiguration examined the facility response to throttling at the tank inlet, demonstrating increased sensitivity of flow instabilities to throttling within the two-phase region when compared to throttling at the lower sensitivity single-phase inlet region. Testing after the chimney reconfiguration began with a baseline test at conditions of 80% inventory fill and prototypic thermal power input of 2.1 MW t . In addition to establishing a reference for nominal system behavior and performance, repeat testing with multiple subsequent runs demonstrated strong repeatability between tests performed at the same conditions in this new configuration. These tests also examined if influences would occur to system behavior with installation of new higher-resolution instrumentation within the upper chimney. In this critical region where boiling and flashing phenomena dominate, the test results provided confidence that the new instrumentation does not uncharacteristically influence the observed behaviors. An inventory parametric series was then initiated to examine system behavior with the new chimney configuration at six varying initial inventory levels, ranging from high 80% to low 20% fill. Two-phase oscillations with similar peak and mean flow rates were observed when comparing to the previous mid tank configuration. Generally, similar system response trends with inventory were also observed, such as two phase oscillations suppressing as inventories were lowered. However, in one absolute inventory comparison at the highest fill of 80%, flow oscillations saw a gradual growth over the 4 hours of two-phase operation in the new lower tank inlet configuration, opposite of the gradual dampening observed in the mid tank inlet configuration. This can be attributed to, in part, a greater hydrostatic head pressure above the two-phase discharge region where the boiling front is developed. Furthermore, the change resulted in greater sensitivity to liquid degassing phenomena during single-phase heating, causing loop instabilities to form which trigged moderate flow degradation during the period approaching saturation and boiling conditions. This behavior had been observed previously under some conditions but was a common occurrence in recent testing with the newer lower tank inlet configuration. Initial observations from these first data sets suggest an overall larger window of stability for the mid tank inlet configuration compared to the lower tank inlet. Lastly, the lowest inventory fill test was repeated over an extended testing window to examine depletion behavior. Natural circulation flow and effective heat removal performance were observed during most of the testing period; only after the tank became fully drained (0% fill) did flow stagnate and violent geysering events occur. This early observation confirms one relative advantage over the mid tank inlet configuration, which stagnated under comparable conditions at ~20% inventory remaining in the tank.

42 ENGINEERING↗
DOE OSTI2025

Classification of Cloud Particle Imagery and Thermodynamics (COCPIT): A New Databasing Tool for the Characterization of Cloud Particle Images Captured During DOE Field Campaigns

The Department of Energy for decades has explored the earth system and atmosphere through research and deployment of in-situ and remote sensing platforms during field campaigns. Among these datasets exists a vast supply of cloud particle images that provide visual insight into the complex microphysics in the clouds that span our globe. The millions of images collected over decades of deployments provides a unique opportunity to further our understanding of our atmosphere down to the crystal size. This work over the past 5 years has sought to organize these images into digestible datasets that can then be used by scientists to further our understanding of microphysics. A machine learning model was developed that categorizes over 1.5 million images across 11 weather events with over 90% accuracy according to particle type. The database was then extended to include dimensional characteristics of the particle as well as co-location of environmental properties, such as temperature and water content. Then, to initialize the connection between these data and our understanding of how crystals form and grow, weather research and forecasting simulations were run to generate the growth histories of the classified crystals. This research culminates with 2 databases per event: (1) a database of all classified crystals and their dimensional and environmental properties and (2) simulated growth histories of each crystal. Finally, a user interface was created to allow researchers to explore data statistics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Identifying Opportunities at the Interface of Chemistry and Quantum Information Science (Final Technical Report)

This project convened a National Academies committee to identify opportunities and research priorities at the interface of chemistry and quantum information science (QIS). The work culminated in a consensus study report that (1) articulates three fundamental research areas to advance QIS (design and synthesis of molecular qubits; measurement and control of molecular quantum systems; and experimental and computational scaling of qubit design and function), and (2) underscores the importance of cross-disciplinary collaboration, access to facilities and instrumentation, FAIR-aligned data infrastructure, and workforce development initiatives to sustain U.S. leadership in QIS. The report and all other material associated with this project can be downloaded on the project webpage: https://www.nationalacademies.org/projects/DELS-BCST-21-01 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

U.S. Pacific Coast Workshop Report on Preconstruction Research Recommendations (U.S. Offshore Wind Synthesis of Environmental Effects Research (SEER) Project)

In May 2022, the U.S. Offshore Wind Synthesis of Environmental Effects Research (SEER) project team hosted a stakeholder workshop focused on preconstruction (baseline) research needs for potential floating offshore wind (OSW) energy development on the U.S. Pacific Coast, including California, Oregon, and Washington. Prior to the workshop, the SEER team developed a set of initial synthesized research recommendations that were identified based on a review of relevant, publicly available resources and with advisory group input. The workshop covered three marine life breakout groups on subsequent days to discuss research recommendations related to 1) marine mammals and sea turtles, 2) fish and invertebrates, and 3) birds and bats. As part of the workshop, over a hundred participants from the public and private sectors provided feedback on various aspects of the initial research recommendations, including associated data and knowledge gaps, benefits/limitations of available methods and technologies, and technological advancements or infrastructure needed to address the recommendation. Approximately 1,000 total comments were received on the workshop MURAL boards and were synthesized in this report. Based on workshop feedback, SEER developed a final database of over 500 specific research recommendations based on more than 40 resources. In Fall 2022, the full database and a tool with updated synthesized research recommendations were disseminated on Tethys (https://tethys.pnnl.gov) to assist with informing future funding opportunities and research programming. There is a continued need to improve awareness of the potential environmental effects, monitoring technologies, and management strategies for floating OSW energy development on the U.S. Pacific Coast. Coordination of these activities will require the sustained involvement of multiple stakeholders from across sectors. Beyond the baseline considerations discussed in this workshop, future state-of-the-science activities should be planned to consider research needs across wind energy life cycle phases for all relevant wildlife taxa and associated habitat and ecosystem processes.

17 WIND ENERGY↗
DOE OSTI2025

Intrinsic alignment demographics for next-generation lensing: Revealing galaxy property trends with DESI Y1 direct measurements

We present direct measurements of the intrinsic alignments (IA) of over 2 million spectroscopic galaxies using DESI Data Release 1 and imaging from four lensing surveys: DES, HSC, KiDS, and SDSS. In this uniquely data-rich regime, we take initial steps towards a more tailored IA modelling approach by building a library of IA measurements across colour, luminosity, stellar mass, and redshift. We map the dependence between galaxy type -- in terms of rest-frame colour, strength of the 4000 Angstrom break, and specific star formation rate -- and IA amplitude; the bluest galaxies have an alignment consistent with zero, across low ($0.05

Siegel, J. [Princeton U.]↗
DOE OSTI2024

Intern Poster - Characterizing Wildland Fire Conditions for Lab-Scale Testing of Advanced Conductors

As the demand for energy increases each year, electric utilities face the challenge of delivering more power than before. Current transmission/distribution networks have proved reliable in the past but are physically unable to meet higher energy demands. Traditional overhead conductor cables (such as Aluminum Conductor Steel Reinforced (ACSR)) are limited in their ability to hold more voltage due to increased temperatures and resulting sag. When the cable sags, it comes closer to the ground, violating clearance standards and presenting an environmental risk. Newly developed advanced conductors, aluminum conductors with carbon fiber composite cores (instead of steel) mitigate this risk. Advanced conductors are engineered to perform in higher operating temperatures without sagging, thus possessing higher capacity potential. Regardless, utilities are hesitant to adopt this new technology due to scarcity of use data. The largest looming risk for utilities is wildland fires. There is little to no data on how advanced conductors perform in the event of a wildland fire. To address these concerns, this project aims to test the mechanical performance of advanced conductors in these conditions, providing utilities use data for their reference. The initial steps of the project will be to design and construct a fire table apparatus to reproduce wildland fire conditions, calculate proper parameters for this testing, and analyze the impact mathematically. After completing these actions, the next steps will be to test the advanced conductors in the laboratory fire chamber.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Evaluation of Hanford 200 West Area Tank Farms (241-S/241-SX-/241-U tank farms) Physical Properties Data for Use in Development of West Area Tank Treatment (WATT) Processing

With the recent acceptance of West Area Tank Treatment disposition alternative for 200 West Area tanks at the Hanford Site by the State of Washington and the U.S. Department of Energy, a review was initiated to identify the physical properties data available in the literature for the Hanford 241-S, 241-SX, and 241-U tank farms. The literature reviewed indicated that there is a relatively small set of useful data on physical properties of 200 West Area tanks, and the data that do exist are biased around a narrow range of tank samples. Much of the testing between the 1990s and mid-2010s was intended to support either enhanced sludge washing or feed delivery to the Pretreatment Facility at the Hanford Waste Treatment and Immobilization Plant. As such, some physical properties of 200 West Area samples were measured under conditions that are no longer relevant. Because of the distinctly different nature of many past processes at the 200 West Area compared to the 200 East Area, insight from waste testing in the 200 East Area waste should be used with caution, as there may be significantly different qualities in the physical properties data between these two areas (both in situ and as measured in laboratory analyses). Based on this assessment, there is a need to collect additional physical property data to support planning for 200 West Area retrievals.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗