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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

PSInet: a new global water potential network

Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.

Forestry↗
DOE OSTI2024

Improving Grid Awareness by Empowering Utilities with Machine Learning and Artificial Intelligence

Gap filling time series data typically depends on linear interpolation. More recently gap filling advancements include machine learning techniques. However, none leverage advanced learning approach that uses cohort training or a neighborhood informed approach, which is described in this report. The report also describes a physics informed approach using Reduced Order Models (ROM). There are several methods to capture the nature of the detailed system in aggregated models, however there is a trade-off for these methods developed for multiple applications. These methods have specific requirements and applications that includes consideration of dynamics or covering a larger range of operating conditions, etc. The various methods of aggregation are: 1) Thevenin equivalents for downstream networks 2) Equivalent feeder representation to capture downstream network losses accurately 3) Structured reduced order models for dynamics 4) System identification-based ROM (abstract dynamical model) Methods described in items 1 and 2 above are ideal for steady-state models and useful for this application. Of these two methods, based on the data availability, the targeted application, the reduced order model that is proposed to be developed is the equivalent feeder model representation. This includes a structure of the reduced order model whose parameters can be determined by the system load and losses with the meter measurements.

14 SOLAR ENERGY↗
DOE OSTI2023

Automated Controller Hardware-In-The-Loop Testbed for EV Charger Resilience Analysis

This paper focuses on the development of a tool that includes an automated testbed with controls, protection, and communications integrated into a real-time system to provide a platform to generate data sets for failure modes and effects analysis. This tool establishes a value for automation of data generation for different scenarios and addresses the gap of nonexistent field data for different applications and use cases. The features of this tool can further be expanded to include multiple power electronics models, communication protocols, and scaled system architectures. This general framework was evaluated for a DC fast charger system use case to provide quantitative solution for resiliency.

Starke, Michael↗
DOE OSTI2020

Provenance infrastructure for multimodal x-ray experiments and reproducible analysis

Exploring relationships between material structures and desired properties for material discovery and synthesis requires mining machine-readable databases and linking experimental data with sufficiently rich annotations. There are vast gaps both in these data sources and in the connections between them. We present a provenance-based data management and analysis framework that enables capturing, persisting, and reanalyzing experimental data from the BNL National Synchrotron Light Source II (NSLS-II). Our system leverages NSLS-II Bluesky for experimental data acquisition, captures analysis parameters, and enriches the search space with results from the scientific literature. We describe in detail the challenges and benefits of data-driven approaches when comparing computational and experimental data, such as the multiple possible scenarios of interest in often ill-posed inverse problems and missing data. Our infrastructure utilizes the NSLS-II event model and includes discovery mechanisms across multiple beamlines. A text and data mining module using natural language processing classification techniques extracts relevant information from the literature that is added to data sources. We describe a provenance acquisition and analysis rerun workflow based on a directed acyclic graph that keeps track of process and data provenance and allows to replay analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ln 10 S 14 O (Ln = La, Pr, Nd, Sm) Oxysulfides: A Series of Direct n-Type Semiconductors

Lanthanoid oxysulfides are promising materials for technological applications owing to their magnetic, photoluminescent, catalytic, and optoelectronic properties. In this work, we report the solid-state synthesis and structural characterization of Ln 10 S 14 O (Ln = La, Ce, Pr, Nd, Sm) oxysulfides. Then, we present a thorough discussion on their electronic and photophysical properties. Through Tauc plot analysis and the derivation of the absorption spectrum fitting method (DASF), we determine that all oxysulfides have direct band gaps with energies of 2.84 eV (La), 2.02 eV (Ce), 2.56 eV (Pr), 2.64 eV (Nd), and 2.41 eV (Sm). Furthermore, surface photovoltage spectroscopy (SPS) shows photovoltage (ΔCPD) values of –0.4 to –1.1 V for La-, Pr-, Nd-, and Sm-containing compounds when illuminated near the optical band gap, indicating that these oxysulfides are n-type semiconductors, which is consistent with Mott–Schottky analysis. Photovoltages under sub-band gap illumination energy and photovoltage decay data suggest mid-band gap states possibly arising from the lanthanoid 4f orbitals and/or defects within the crystal structure or at the particle surfaces. These photophysical properties suggest possible applications of the oxysulfides in photoelectrochemical and photovoltaic energy conversion.

14 SOLAR ENERGY↗
DOE OSTI2026

Data Center Cybersecurity, Supply Chain Risk Management, and Emerging Regulation Cohort Summary: Takeaways and Action Plans

This report summarizes the outcomes of the Data Center Cohort under the Department of Energy’s Technical Assistance for Digital Assurance (TADA) initiative, aimed at enhancing grid resilience through cybersecurity, supply chain risk management (SCRM), and Cyber-Informed Engineering (CIE). The cohort engaged 17 organizations across utilities, data center operators, vendors, and technology providers in three sessions combining presentations, discussions, and exercises. Key topics included AI-driven load behavior, cybersecurity vulnerabilities in UPS/BESS and cooling systems, governance gaps at utility–data center boundaries, and supply chain integrity. Five cross-cutting themes emerged: interconnection architecture vulnerabilities, fragmented governance, AI-driven stability risks, lack of regulatory frameworks, and long-term supply chain concerns. Actionable recommendations were developed, including implementing DMZ segmentation, formalizing vendor access agreements, designing AI workload limits, and advancing standards through NERC and state-level programs. These strategies aim to strengthen resilience, clarify responsibilities, and ensure secure integration of data centers into the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Support of the Development of EPP Plus SMT Design Method (FY2020 Test Results)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) analysis and Simplified Model Test (SMT) design methodology continued in FY 2020. The previously developed single-bar SMT (SBSMT) technique was successfully extended to tubular shaped Alloy 617 specimens for evaluation of the effect of primary pressure load on SMT creep-fatigue (CF) properties at 950°C. A series of pressurized SMT tests were performed with various elastic follow-up factors and strain ranges. The results show that the primary pressure load reduces the SMT CF cycles. The reduction of SMT CF life due to primary load was found to be dependent on strain ranges, elastic follow up and test temperatures. These results are crucial for verification of the EPP strain range analysis in the EPP+SMT evaluation procedure. Additionally, hold time effect on the SMT CF life cycles is a determining factor for generating the EPP+SMT CF design curves. Lack of test data in the high cycle and low strain range region results in major uncertainty in developing the design curves. In FY2020, experiments were designed, and testing started on Alloy 617 at 950°C to fill the gap in experimental data. The on-going CF and additional SMT CF with elastic follow-up at low strain ranges will generate the information needed to verify the methods for extrapolation to long hold time and finalize the EPP+SMT design method.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Using Machine Learning to Track Objects Across Cameras

Video surveillance is one of the most important technologies used by the International Atomic Energy Agency in international safeguards. At large, complicated facilities, multiple surveillance cameras are deployed to monitor the transfer of safeguards-relevant objects across the site. During inspections, all surveillance videos are reviewed to ensure the objects are not manipulated or diverted during transfer, a laborious, time-consuming task. This work describes using deep machine learning algorithms to track objects automatically across multiple cameras, greatly improving the efficiency of the review process. The fundamental problem in this object tracking task across multiple cameras is how to associate the same object, which may show extreme intra-class variations, such as viewpoints, occlusions, and various scales, in different and even non-overlapped cameras. Object re-identification (Re-ID) in nuclear facility video surveillance is even more challenging than classic person or vehicle Re-ID problems because different instances in the same category may display an identical appearance. One observation from nuclear facility surveillance videos is that all objects must be carted (e.g., via forklift) to move. Therefore, the spatial context information of an object, which provides the feature from the carrier, is critical for the object Re-ID task. This work proposes a two-stream convolutional neural networks model that takes features of objects and their surrounding regions into account. Moreover, the custom videos usually are gleaned from different scenes from the training data, which may have extreme variations in illumination changes and/or cluttered backgrounds. Directly applying the trained model to custom videos will dramatically decrease the performance. To tackle this problem, an advanced domain adaptation technique is proposed to mitigate the gap between the data taken from different scenes. The proposed framework will track objects of interest across a nuclear complex. The resulting tracks can be used in further analyses, such as event/activity recognition, anomaly detection, etc.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

System Configuration Evaluation for Process Settling of Hanford Waste Solid Particles

Direct Feed High-Level Waste (DFHLW) is a potential flowsheet operations approach to initiating high-level waste (HLW) vitrification prior to completion of the Hanford Waste Treatment and Immobilization Plant (WTP) Pretreatment Facility. A settle/decant process has been proposed to concentrate solids prior to delivery to the WTP HLW Facility during DFHLW operations, wherein the solids in a settled layer would be remixed with the supernatant liquid remaining after decanting operations to provide the feed at required solids concentrations. Settling would be used in lieu of purpose-built filtration or other solids separation equipment. Pacific Northwest National Laboratory (PNNL) is providing baseline technical support to the Washington River Protection Solutions (WRPS) Flowsheet Integration group. To support planning for DFHLW, WRPS previously requested that PNNL evaluate the current data set available to predict the time needed for HLW solids to settle and the solids concentration and strength of that settled layer, to identify gaps in the understanding and predictive capability of HLW solids waste settling times, and to provide scoping estimates of the potential settling times. Eight technical gaps were identified for predicting settling times and characteristics of the formed sediment layers. In addition to the data gaps, an overarching observation was made that there is significant variation in behavior of settling rate and settled layer data. The settling time required to concentrate solids via a settle/decant process was determined from the limited data to have a difference of potentially more than a factor of 5,000 in the estimated settling times, varying from 0.2 to 1,060 days for example depending on process vessel depth and final sediment solids concentration. In contrast, successful processes of liquid-forward output streams resulting from in-tank settling and decanting forward liquid have been reported for operations conducted at the Hanford Site. The purpose of this current report is to further support DFHLW planning by evaluating double-shell tank (DST) and alternate vessel equipment and operational configurations to enable optimization of the settle/decant process to concentrate solids. Hanford waste processing behavior specific to liquid feed availability following a slurry transfer in a DST is summarized, including process stream characteristics and process equipment configurations. The performance of DST process equipment configurations is evaluated for possible improvements using computational fluid dynamics (CFD) and simple analytical models. Potential new vessel design(s) specific to enabling effective settle/decant processes, and cursory summary of other separate and inline solids separations processes, are also provided. The CFD results indicated that improvement in outflow solids concentration was promoted by a reduction in the slurry flow rate, angling the distributor nozzles downward, and lifting the transfer pump. The solid-liquid analysis evaluating particle trajectory confirmed that the potential for particle ingestion (in the transfer pump) was decreased with increased radial separation between the inlet and outlet (transfer pump inlet), decreased inlet flow, and decreased liquid density and viscosity for a neutrally buoyant inlet flow. An assessment was also made of the potential for inflow configuration changes to result in the discrete mounding or piling of solids within the tank. Based on the characterization of the settled waste to date, HLW sediments will be unlikely to sustain a substantial angle of repose to facilitate significant variations in the elevation of the settled solids.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Introduction to Evolve Central Appalachia

The Evolve-CAPP project is developing and implementing strategies to enable the Central Appalachian basin to realize its full economic potential for producing high-value, non-fuel, carbon-ore (CO) products, rare earth elements (REE), and critical minerals (CM). The Basinal Assessment of CORE-CM Resources is a state-of-the-art geological model and comprehensive database that will be used to identify, locate, and quantify in-situ resources in the basin. Restrictive aspects of resource recovery, such as ownership and legal restrictions, are being considered in estimating recoverable resources. A gap analysis of missing or unavailable data that could not be fully integrated in the initial assessment due to budget, access, or other constraints during the assessment effort is planned. A characterization and data acquisition plan to fully characterize the basin’s CORE-CM potential will address gaps in data. The plan will be developed with input from project team members and relevant stakeholders, including land and mineral holding companies and coal operators, who maintain sampling programs as part of their normal operations.

Bishop, Richard↗
DOE OSTI2021

Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Furthermore, our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Data call questions related to potential NEPA/Data gaps

Based on review of the related NEPA documents, and consideration of the potential gaps in NEPA coverage, a number of questions have been generated. These questions are generally higher level (less detailed) questions that should help to establish the applicability of analyses in existing NEPA documents and the ability of these documents to provide NEPA coverage for the Proposed Action. These questions do not request detailed information about SRS facilities/activities and the Proposed Action like typically would be requested when performing impacts analyses for an EIS. We do not believe detail information is needed; if it is needed, it may be an indication that an SA is not the appropriate level of NEPA documentation for the Proposed Action.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Creep-fatigue Behavior and Damage Accumulation of a Candidate Structural Material for Concentrating Solar Power Solar Thermal Receiver (Final Technical Report)

Creep-fatigue deformation is an important consideration for a thermal receiver in Concentrating Solar Power systems due to the constant static stress or pressure, diurnal cycling, and elevated service temperatures required for efficient operation. An accurate description of the creep-fatigue behavior, not available for five of the six candidate materials, is important for assessment of preliminary designs. This project has provided a detailed analysis of the creep-fatigue behavior and damage accumulation of Alloy 740H, a candidate structural material for a CSP solar thermal receiver to address a critical knowledge barrier for receiver designs identified in the CSP Gen3 Demonstration Roadmap. This project was divided in to three tasks, split between two general categories: Experimental and design methodology. Tasks 1 and 3, relating to the collection of data on Alloy 740H plate and sheet forms, respectively, were performed at the Idaho National Laboratory and used as input to Task 2, the development of design methodology performed at Argonne National Laboratory. Experimental work covered limited tensile and creep testing to fill gaps in available data that is currently available and to demonstrate how the plate of Alloy 740H tested in this work compared to historical data. A more substantial testing program for fatigue and creep-fatigue was performed, with particular emphasis on creep-fatigue as there is little available data and it is necessary to understand the creep-fatigue interaction and develop related design models. This effort includes the development of rules for the design of solar receiver components against high temperature creep-fatigue and ratcheting failure modes. The ASME Code rules for high temperature nuclear components was used to the basis of the method but adjustments will be made to reflect the generally shorter, diurnal operating cycles of thermal receivers and the relative consequences of failure, comparing nuclear to solar components. This work has provided guidance for the design of components for concentrating power facilities operating at high temperatures and undergoing high, secondary thermal stresses relative to the applied primary pressure stress. The design rules were developed for the design of Generation 3 CSP tubular receivers manufactured from Alloy 740H, but are generally applicable to a wide range of component types undergoing similar loads. Procedural design rules for components to be used in conjunction with the 2019 edition of the ASME Boiler & Pressure Vessel Code and the corresponding design data for Alloy 740H have been developed. A commentary describing the rationale behind the design rules and the data underlying the design material properties, as well as an extensive set of worked sample problems detailing the application of the rules to CSP components were developed as a part of this project, with a separate report covering these aspects in detail and included in the Appendix of this report.

14 SOLAR ENERGY↗
DOE OSTI2023

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗
DOE OSTI2020

(Oxy)hydroxides Formed on Aluminum Fuel Materials After Irradiation and Long-Term Wet Storage - 20354

The aluminum cladding of research-reactor fuel experiences general corrosion when in contact with water during in-reactor service and post-discharge wet storage, resulting in the formation of adherent aluminum (oxy)hydroxide films. These (oxy)hydroxides contain chemically-bound water that poses challenges for extended dry storage due to the risk of thermal or radiolytic decomposition releasing free water and/or hydrogen and oxygen gases. This study describes characterization of the (oxy)hydroxides present on several aluminum materials used in reactor operation and subsequently stored wet in the L-Basin storage facility at the Savannah River Site (SRS) for an extended period. Characterization data providing insight into the loading, composition, and morphology of (oxy)hydroxides to be expected on service-exposed aluminum cladding provides valuable benchmarks for designing adequate drying and dry-storage approaches. This work is part of a broader investigation to address knowledge gaps and technical data needs for dry storage of aluminum-clad spent nuclear fuel (ASNF), which included in-lab growth of (oxy)hydroxide films on aluminum alloy substrates to investigate formation behavior, investigation of drying methods to remove existing (oxy)hydroxides from ASNF cladding, and measurement of radiolytic yield of hydrogen from (oxy)hydroxide powders and films. In this study, (oxy)hydroxide films were characterized for three aluminum-alloy materials used in reactors and subsequently stored wet for up to approximately 40 years in L-Basin at SRS: one cropping from a Missouri University Research Reactor (MURR) fuel element (Al-6061 alloy), one cropping from a Universal Sleeve Housing (USH) (Al-6063 alloy), and one Mark-16B fuel assembly (either Al-6061 or Al- 6063). The USH and Mark-16B were used in SRS production reactors. Characterization of the as-received (oxy)hydroxides included scanning electron microscopy (SEM) in both plan-view and cross-section to characterize the (oxy)hydroxide layer's morphology, thickness, and structure. X-ray diffraction (XRD) was used to identify the chemical composition and distinguish between the various aluminum (oxy)hydroxides known to form under reactor and storage conditions. XRD analysis revealed both bayerite (Al(OH)3) and boehmite (AlOOH) on the surface of the MURR and USH samples, as well as bayerite, boehmite, and gibbsite (another Al(OH)3 polymorph) on the surface of the Mark-16B sample. The aluminum trihydroxides, bayerite and gibbsite, are typically associated with corrosion in low-temperature (<80 deg. C) water, while boehmite is expected to form at higher water temperature (>80 deg. C). The presence of bayerite on the USH, which is believed to have operated close to 90 deg. C, suggests that boehmite formed during in-reactor exposure was not protective against further hydroxide growth in low-temperature wet storage. Cross-section scanning electron microscopy (SEM) showed total (oxy)hydroxide layer thicknesses of ∼5- 10 μm for the MURR and ∼5-15 μm for the Mark-16B. The thickness of the USH's (oxy)hydroxide layer was indiscernible by the current mounting and imaging method, despite plan-view SEM and XRD confirming the presence of an (oxy)hydroxide layer. (authors)

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

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗