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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 181 records · Page 10

Recent High Burnup LOCA Testing at Oak Ridge National Laboratory

To improve fuel cycle economics, increasing the fuel burnup limit in light-water reactors requires a solid technical foundation. Observations from experiments at Halden and Studsvik highlighted severe fuel fragmentation during loss-of-coolant-accident (LOCA) conditions, indicating a need for further technical considerations. These experiments suggest that the fragmentation threshold for high-burnup fuel might be influenced by pre-transient power levels. Consequently, additional LOCA test data are essential to complement existing findings and to deepen our understanding. Oak Ridge National Laboratory’s Severe Accident Test Station has been instrumental in advancing knowledge about high-burnup fuel fragmentation, relocation, and dispersal. This milestone report details two high-burnup LOCA tests designed to evaluate the effects of terminal temperature and grid spacers (or cladding restraints) on fuel fragmentation and relocation susceptibility. In addition, BISON fuel performance modeling and out-of-cell benchmark testing were conducted to better interpret the in-cell test results. These tests were developed in collaboration with fuel vendors to ensure that the results provide valuable data for topical reports and support the Nuclear Regulatory Commission’s review.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Progress Towards the Validation of a new RELAP5-3D model of the High Temperature Test Facility

Validation is a key step in the development of any type of systems model. As the next generation of reactors approaches, the need for codes that have been validated for these new types of systems continues to grow. An example of a prominent option is the Reactor Excursion Leak Analysis Program (RELAP5-3D), developed by Idaho National Laboratory. This code was developed for the purpose of systems level thermal-hydraulic modeling of light water reactors (LWRS) and postulated transients that can occur in LWRS.RELAP5-3D has been substantially validated against LWR data. Due to its long history as a reactor safety analysis tool, there has been an effort to adapt RELAP5-3D for the purposes of advanced reactor concepts such as prismatic high-temperature gas-cooled reactors (HTGRs). However, RELAP5-3D has not nearly been validated and verified for HTGRs to the degree of LWRs, warranting verification and validation opportunities with computational benchmarks and existing experimental facilities. Examples of such facilities include the modular high-temperature gas-cooled reactor (MHTGR) 350 and the high temperature engineering test reactor (HTTR) from Japan. The MHTGR 350 is a benchmark design concept for code-to-code verification purposes; therefore, it does not provide any experimental data for validation opportunities The HTTR provides useful multiphysics validation data but does not have the in-core instruments to generate thermal-hydraulic experimental data to help with RELAP5-3D validation. Consequently, a facility that could provide key in-core temperatures for thermal-hydraulic validation was still needed. The High Temperature Test Facility (HTTF) is an integral effects facility for HTGR thermal hydraulics developed and operated by Oregon State University. HTTF represents ¼ length scale of the General Atomics MHTGR and is rated for a total power of 2.2 MW. Axially, the core consists of an upper and lower reflector and 10 blocks, numbered from bottom to top (Block 1 is right above lower reflector). The core is heated via graphite resistive heater rods, with respective channels distributed throughout the core. The primary coolant is helium and heat can radiate out of the core to the reactor cavity cooling system (RCCS), which is cooled by water. The primary purpose of the facility is to investigate pressurized conduction cooldown (PCC) and depressurized conduction cooldown (DCC) transients, which are also referred to as the pressurized and depressurized loss of forced cooling respectively. Two experiments were chosen to perform the validation study with a RELAP5-3D model of HTTF. These experiments are PG-27 (PCC) and PG-29 (DCC). These were chosen based off of the quality of available experimental data before and during the experiment which led to their inclusion in the HTGR Thermal Hydraulics Benchmark.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

5G Communications in Nuclear: Potential Use Cases and Security Considerations

As fifth-generation (5G) communications continues to revolutionize the future of wireless technology, there is growing demand to utilize its benefits for critical infrastructures such as nuclear power plants (NPPs). In regard to achieving full automation and control in the operation of existing and future nuclear reactors, the unique capabilities of 5G can bring several potential advantages over other wireless technologies. However, a deep investigation is needed for the availability and security of 5G communications under various NPP operational scenarios. This article examines how 5G security capabilities can be architecturally deployed in nuclear applications so as to replace existing communication infrastructures. We discuss the current use of all wireless technologies in NPPs with their key features. Consequently, we investigated several NPP use cases in which 5G offers potential advantages but entails specific security considerations. The present article covers the characteristics of 5G communications, general challenges to its application in nuclear, and the security gaps that need to be addressed. We also highlight certain 5G security-by-design features that can help addressing current stringent NPP requirements. In addition, we discuss some future research direction that can facilitate the implementation of 5G in a nuclear facility. The findings presented herein can help foster 5G deployment in NPPs, thus enabling secured data transmission, cost savings, and increased operational efficiency with enhanced reliability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CNN-Based Phase Fault Classification in Real and Simulated Power Systems Data

This study proposes a convolutional neural network (CNN)–based two-step phase fault detection and identification method to classify anomalies in the power grid signal. Specifically, the first step checks the fault’s existence and determines the need for the second step. Subsequently, in the case of anomalies in the power grid signal, the second step identifies the type of fault, including line-to-line, single-line-to-ground, double-line-to-ground, and triple-line. Accordingly, the CNN architecture is both designed for the classification layers and trained with simulated data. To provide maximum prediction accuracy with minimum processing time, this study investigates the combinations of various feature extraction (FE) techniques, such as fast Fourier transform (FFT), amplitude and phase (AP), auto-correlation function, power spectral density, and wavelet transform (WT). Consequently, simulated and real-world results demonstrate that the proposed two-step method outperforms conventional one-step techniques, with the best performance obtained by using the combination of AP-AP, AP-WT, FFT-AP, and FFT-WT–based FE methods.

Alaca, Ozgur↗

ARCADE Technical Pathway and Industry Impact

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) simplifies the evaluation and assessment of robustness factor and cyber resilience that support secure-by-design for advanced reactor nuclear power plants. In this manner, ARCADE supports risk-informed performance based (RIPB) evaluations of cybersecurity through its integration of plant physics with high-fidelity emulations of control systems. This cross domain approach enables comprehensive analysis of control system sensitivities, cyber-attack scenarios, and their consequences. ARCADE has been custom developed to meet the demands identified in Tier 1 of the Tiered Cyber Analysis (TCA) as outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors.

97 MATHEMATICS AND COMPUTING↗

From IMT Device Measurements to Network-Level Consequences: When Learning Suppresses Beyond-LIF Neuron Dynamics

Emerging neuromorphic devices such as insulator--metal transition (IMT) devices exhibit complex temporal dynamics, including slow internal state memory, hysteresis, and burst-like firing, which are poorly captured by conventional leaky integrate-and-fire (LIF) neurons. However, it remains unclear when such dynamics influence learning and inference at the network level, particularly under commonly used unsupervised plasticity rules. We present a controlled, full-stack co-design study spanning experimental characterization of individual IMT devices, compact neuron model development, and large-scale spiking network simulations with identical architectures and learning rules. Rather than optimizing benchmark accuracy, our goal is to diagnose when neuron-level dynamics survive learning and competition, and when they are suppressed, to inform the co-design of devices, networks, and learning rules that can exploit beyond-LIF complexity.

42 ENGINEERING↗

Instrumentation for the Investigation of Pitch Bearing Design and Reliability

Recently, there has been an increasing level of industry interest in pitch system and pitch bearing reliability. Pitch bearings are used in wind turbines to connect the blade root to the hub. Some populations of pitch bearings have demonstrated a 12% failure rate in 20 years. As rotor diameters continue to increase for tall land-based and offshore wind turbines, pitch bearings are becoming even larger in diameter, which can make them vulnerable to deflections and consequent stress concentrations. There is an increased need to more accurately study pitch bearing deformations, misalignment, load distributions, and contact stresses. A significant body of work has investigated fatigue lives and wear characteristics of pitch bearings on ground-based test rigs. NREL has also recently begun a research program related to pitch bearing reliability, recognizing its growing importance for wind turbines. The purpose of this paper is to describe a set of instrumentation that was recently installed on a 1.5 MW wind turbine at the NREL Flatirons Campus and provide an example data set. To the authors' knowledge, this will be the first publicly available pitch bearing data collection campaign on an operational wind turbine.

17 WIND ENERGY↗

Adapting Traditional Hazards Analysis Methods to Address Cyber Risks

Traditional hazards analysis (HA) methods, originally developed to address physical and operational risks, often fall short when it comes to identifying and mitigating cyber threats. These cyber threats pose unique and evolving risks to critical infrastructure and industrial control systems (ICS). This report explores the integration of Cyber-Informed Engineering (CIE) principles into existing HA methods to enhance their ability to address cyber-induced risks. CIE provides organizations with a practical, cost-effective approach to closing the gap between traditional HA methods and the need for cyber risk mitigation. By leveraging existing safety processes and controls, CIE allows users to examine and mitigate cyber vulnerabilities without overhauling existing HA methods. This report identifies areas where HA and CIE naturally align and where their approaches diverge. It emphasizes how CIE principles can be used to adapt HA methods, broadening their scope to include cyber risks and enabling the mitigation of cyber- induced impacts alongside traditional hazards and failure scenarios. This report examines how CIE can be applied across various HA methods—such as Hazard and Operability Studies (HAZOP), Probabilistic Risk Assessment (PRA), Failure Modes and Effects Analysis (FMEA), Systems-Theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), and Layers of Protection Analysis (LOPA). It provides strategies for integrating CIE to strengthen the identification, assessment, and mitigation of cyber-induced risks. The findings offer a structured entry point for organizations to embed CIE concepts into hazards and safety analyses, as well as broader engineering processes, ultimately supporting the design and operation of a more resilient infrastructure.

42 ENGINEERING↗

Adapting Traditional Hazards Analysis Methods to Address Cyber Risks

Traditional hazards analysis (HA) methods, originally developed to address physical and operational risks, often fall short when it comes to identifying and mitigating cyber threats. These cyber threats pose unique and evolving risks to critical infrastructure and industrial control systems (ICS). This report explores the integration of Cyber-Informed Engineering (CIE) principles into existing HA methods to enhance their ability to address cyber-induced risks. CIE provides organizations with a practical, cost-effective approach to closing the gap between traditional HA methods and the need for cyber risk mitigation. By leveraging existing safety processes and controls, CIE allows users to examine and mitigate cyber vulnerabilities without overhauling existing HA methods. This report identifies areas where HA and CIE naturally align and where their approaches diverge. It emphasizes how CIE principles can be used to adapt HA methods, broadening their scope to include cyber risks and enabling the mitigation of cyber- induced impacts alongside traditional hazards and failure scenarios. This report examines how CIE can be applied across various HA methods—such as Hazard and Operability Studies (HAZOP), Probabilistic Risk Assessment (PRA), Failure Modes and Effects Analysis (FMEA), Systems-Theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), and Layers of Protection Analysis (LOPA). It provides strategies for integrating CIE to strengthen the identification, assessment, and mitigation of cyber-induced risks. The findings offer a structured entry point for organizations to embed CIE concepts into hazards and safety analyses, as well as broader engineering processes, ultimately supporting the design and operation of a more resilient infrastructure.

42 - ENGINEERING↗

Field Demonstration and Adoption Impacts of an Affordable Thermoelectric Heat Pump

This study presents the design, field validation, and utility impacts of an air source heat pump that uses thermoelectric (TE) technology to provide supplemental heating at outside air temperatures below 17°F. Conventional heat pumps experience reduced heating capacity and COP at low outdoor temperatures due to the temperature difference between the source and demand sides of the vapor compression cycle. Consequently, during colder months, supplemental heating such as electric resistance or natural gas furnace is often needed to provide additional warmth, which increases the overall equipment and energy costs. To address this challenge, a TE subcooler (an array of solid-state, thermoelectric modules that provides heat pumping using non-vapor compression technique) is fabricated and integrated with the vapor compression cycle of a conventional air-source heat pump. In colder ambient conditions, TE subcooler exchanges heat with the refrigerant to provide additional subcooling, thereby enhancing the capacity of the heat pump. The operation of thermoelectric-integrated heat pump was demonstrated in an occupied single-family home in Nashville, TN. The TE subcooler increased the system’s heating capacity at 15°F outdoor temperature by 25–30% and reduced electricity demand by 10%. It also met the heating load in the house without supplemental electric resistance down to 5°F outdoors, delivering the additional heat at nearly 80% greater efficiency compared to electric resistance heating. With a modest first cost increment of 10–15% over conventional single-speed heat pumps, this approach offers a promising, energy-efficient solution to accelerate residential heat pump adoption in the U.S.

KRISHNAMOORTHY, Sreenidhi [Electric Power Research↗

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities (Revision 1)

This project will demonstrate a multi-hazard time-dependent probabilistic risk assessment (PRA) approach for nuclear facilities considering aging-related deterioration of structures. A generic pressurized water reactor (PWR) reactor subjected to seismic mainshock-aftershock sequences considering the aging of the containment structure will be used as a case study to demonstrate the multi-hazard PRA approach. Using advanced modeling and simulation, seismic mainshock-aftershock fragility functions will be simulated for the containment structure considering aging effects. A multi-hazard PRA model for a generic PWR reactor will be built to quantify the multi-hazard core damage frequency (CDF) and large early release frequency (LERF) with explicit time-dependent modeling of event sequences. To date, the cascading impacts of multi-hazards are not adequately accounted for in the PRA models for nuclear facilities. In addition, for both initial and periodic evaluation of facilities to withstand natural phenomena hazards (NPH), deterioration of the SSCs due to aging and other effects is not adequately considered. By advancing multi-hazard considerations accounting for aging effects, this project will contribute to improved understanding of the safety of aging nuclear facilities. Project outcomes such as the multi-hazard CDF and LERF will also allow facility owners to optimize upgrade and retrofit protocols. This project is divided into two components: (1) advanced modeling and simulations; and (2) multi-hazard PRA. For the first component, Idaho National Laboratory’s (INL) Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) and BlackBear codes will be used to simulate the seismic response and damage of a containment structure under cascading mainshock-aftershock sequences with aging effects. Uncertainties related to the seismic inputs, material parameters, and environmental factors such as temperature and humidity will be identified and propagated to the fragility functions. These fragility functions, which consider aging effects, will be time dependent. The second component will take the fragility information from the first component to build a multi-hazard time-dependent PRA model starting from a generic PWR model to evaluate the multi-hazard CDF and LERF and characterize the associated consequences. For this component, OpenPRA Web Application and SAPHIRE code will be used. Events such as the Fukushima Daiichi accident have highlighted the importance of considering the cascading impacts of multi-hazards for PRA. Moreover, many of the reactors in the current nuclear fleet in the United States (US) are already operating well beyond their initially planned design life, and applications for further extensions to operating licenses are being considered. Therefore, considering multi-hazard effects and aging deterioration in the NPH risk assessment process will contribute to the safety of both existing and future nuclear facilities. Outcomes of this project will thus directly benefit the standards DOE-STD-1020-16 and DOE-HDBK-1224-18.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tuning Strong Metal–Support Interactions via Synergistic Alloying

The encapsulation phenomenon associated with strong metal-support interaction (SMSI) has been largely restricted to catalyst systems consisting of group VIII metals with high surface energy and reducible transition metal oxide supports with low surface energy. Here, we demonstrate an encapsulation phenomenon that, while sharing morphological similarities with conventional SMSI, follows a distinctive pathway. This is shown by the encapsulation of CuAu nanoparticles (NPs) supported on highly ordered pyrolytic graphite (HOPG). Through dynamic monitoring of Cu, Au, and Cu 50 Au 50 NPs in an oxidizing atmosphere using ambient-pressure X-ray photoelectron spectroscopy, we show that this spontaneous encapsulation is achieved through the synergistic effect of the alloying elements. Specifically, the surface segregation of Cu promotes dissociative O 2 adsorption, leading to the formation of atomic O species, while the subsurface enrichment of Au hinders O incorporation into the bulk of CuAu NPs. Consequently, O spillover onto the graphite support occurs, resulting in the oxidation of the HOPG surface into graphitic oxide species. The higher affinity of the graphitic oxide species toward the Cu-segregated surface prompts their migration from the HOPG support to encapsulate the CuAu NPs. Finally, these results transcend the conventional SMSI and bear practical implications for the design and development of heterogeneous catalysts, particularly in carbon-supported alloy systems.

36 MATERIALS SCIENCE↗

Achieving Higher Activity of Acidic Oxygen Evolution Reaction Using an Atomically Thin Layer of IrO x over Co 3 O 4

The development of electrocatalysts with reduced iridium (Ir) loading for the oxygen evolution reaction (OER) is essential to produce low-cost green hydrogen from water electrolysis under acidic conditions. Herein, an atomically thin layer of iridium oxide (IrO x ) has been uniformly dispersed onto cobalt oxide (Co 3 O 4 ) nanocrystals to improve the efficient use of Ir for acidic OER. In situ characterization and theoretical calculations reveal that compared to the conventional IrOx cluster, the atomically thin layer of IrO x shows stronger interaction with the Co 3 O 4 and consequently higher OER activity due to the Ir-O-Co bond formation at the interface. Equally important, the facile synthetic method and the promising activity in the proton exchange membrane water electrolyzer, reaching 1 A cm -2 at 1.7 V with remarkable durability, enable potential scale-up applications. In conclusion, these findings provide a mechanistic understanding for designing active, stable and lower-cost electrocatalysts with well-defined structures for acidic OER.

58 GEOSCIENCES↗

DEMographic MicrOSimulation (DEMOS) v2.0

DEMOS is an agent-based simulation framework used to evolve population demographic characteristics or lifecycle events such as education, marital status etc. DEMOS modules are designed to capture the interdependencies of short-term and long-term lifecycle events often influential in downstream transportation and land use modeling. An important facet of DEMOS is that it is dynamic, meaning it captures the impact of an agent's demographic characteristics in year 't' on their demographic status in year 't+1'. This has important consequences on medium- and long-term downstream modeling in different domains, such as transportation where decisions such as household vehicle transactions (i.e., buying, selling, or replacing a vehicle) depend current or past household vehicle holdings as well as household transitions. Other downstream modeling that can be enabled by DEMOS include building technology adoption or retrofit decisions, and more. DEMOS modules include: individual age progression year by year, individual mortality events, household restructuring events including marriage match-making; household birth events; individual education participation; individual labor force participation; child leaving household; household in-migration and out-migration for the region; household residence location choice and household mandatory destination choice (work and school). This version of DEMOS is tailored to be integrated with the land use simulation software UrbanSim.

Caicedo, Juan [UrbanSim, Inc.]↗

NuclPred v1

This tool takes a genome assembly as input and predicts per-site nucleosome occupancy as output. Trained on physical maps of nucleosome binding preferences across the fungal kingdom, NuclPred can be applied broadly across fungi (and other eukaryotes). This breadth, combined with its accuracy, means it could have both basic and applied biological implications, for example in understanding eukaryotic gene regulation and genetic engineering. Almost universally across eukaryotes, nucleosomes - each wrapping ~150 base pairs of DNA - serve to package DNA inside the nucleus, with major consequences on DNA access, gene activity and DNA integration. NuclPred was generated using a supervised deep learning approach combining convolutional and recurrent neural networks to take DNA features (nucleotides, GC content and structural information) as input, then use that information to predict the physical attractiveness DNA sequences might have for forming nucleosomes. With this information at hand, researchers can design more efficient CRISPR constructs, explore the interplay between DNA signatures and other regulators impact nucleosome locations, predict expression patterns, etc. This tool will be published as part of a manuscript currently under revision at iScience (draft attached).

Mondo, Stephen↗

Multilaminate Energy Storage Films from Entropy‐Driven Self‐Assembled Supramolecular Nanocomposites

Abstract Composite materials comprising polymers and inorganic nanoparticles (NPs) are promising for energy storage applications, though challenges in controlling NP dispersion often result in performance bottlenecks. Realizing nanocomposites with controlled NP locations and distributions within polymer microdomains is highly desirable for improving energy storage capabilities but is a persistent challenge, impeding the in‐depth understanding of the structure–performance relationship. In this study, a facile entropy‐driven self‐assembly approach is employed to fabricate block copolymer‐based supramolecular nanocomposite films with highly ordered lamellar structures, which are then used in electrostatic film capacitors. The oriented interfacial barriers and well‐distributed inorganic NPs within the self‐assembled multilaminate nanocomposites effectively suppress leakage current and mitigate the risk of breakdown, showing superior dielectric strength compared to their disordered counterparts. Consequently, the lamellar nanocomposite films with optimized composition exhibit high energy efficiency (>90% at 650 MV m −1 ), along with remarkable energy density and power density. Moreover, finite element simulations and statistical modeling have provided theoretical insights into the impact of the lamellar structure on electrical conduction, electric field distribution, and electrical tree propagation. This work marks a significant advancement in the design of organic–inorganic hybrids for energy storage, establishing a well‐defined correlation between microstructure and performance.

Li, He↗

Coalescence-Induced Spontaneous Shedding of Microdroplets on Superhydrophobic Surfaces Featuring Enclosed Micropillars with Hierarchical Roughness

This study investigated water vapor condensation on superhydrophobic surfaces (SHSs) featuring micropillars enclosed by wall lattices and having three-tier hierarchical roughness. A total of five samples were created with three (NW-J, W200-J and W400-J samples) having large micropillar depth (~6 μm) and two (NW-S and W200-S samples) having small micropillar depth (~1 μm). Two distinct condensate removal modes were observed during condensation: coalescence-induced jumping on samples with large micropillar depth and coalescence-induced shedding on samples with small micropillar depth. The results showed that the diameter of the shedding droplet on the W200-S sample having small micropillar depth could be as small as 107 μm, as compared to the theoretical critical diameter of 267 μm for gravitational shedding on the same sample. The enhanced functionality of the three-tier nanotextures on the W200-S sample could effectively suppress localized pinning of the three-phase contact line and Wenzel neck formation during the growth of condensate droplets. Consequently, during multidroplet coalescence, the released surface energy easily overcomes the solid–liquid adhesion, leading to spontaneous shedding of merged droplets. The inclusion of the wall lattice aids condensate growth by the droplet self-alignment along the walls and promoting coalescence. As a result, the W200-S sample exhibited the highest condensate collection as well. In conclusion, the proposed surface design has great potential for scaling up and implementation in heating, ventilation, and air-conditioning equipment due to the simplicity of the surface morphology and the facile spray-coating method used to achieve hierarchical roughness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency responses, meteorology, radionuclide release and transport, land contamination, and health impacts. We identify three key factors that exacerbated the consequences of the accident: (1) the failure of Unit 2 containment venting, (2) the insufficient integration of radiation measurements and meteorology data in the evacuation strategy, and (3) the limited risk assessment and emergency preparedness. We conclude with new research and development directions to improve the resilience of nuclear energy systems and communities, including (1) meteorology-informed proactive venting, (2) machine learning-enabled adaptive evacuation zones, and (3) comprehensive risk-informed emergency planning while leveraging the experience from responses to other disasters.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗