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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 127 records · Page 7

Expanding the Domain of Applicability of Machine Learning Models with Limited Data for Drug Property Prediction

Accurate machine learning models for predicting small molecule interactions with biological targets are essential for therapeutic discovery, biothreat response, and computational drug design, but their performance is often limited for understudied targets with sparse experimental data. To address this challenge, we developed and evaluated methods to improve molecular property prediction under low-data conditions, using the NimA-related kinase (NEK) family as a proof-of-concept. This work focused on two complementary goals within the ATOM Modeling PipeLine (AMPL) and the Generative Molecular Design (GMD) loop: expanding model applicability through transfer learning, representation learning, feature scaling, sampling strategies, and active-learning-inspired compound selection; and enabling efficient virtual screening to prioritize compounds that balance predicted activity, design objectives, and synthetic accessibility.

organic↗

Novel Preprocessing Techniques for Enhancing Flowability of Miscanthus

Purpose-grown energy crops possess significant potential as promising feedstocks for biofuel and biochemical production. However, similar to other biomass feedstocks, their utilization has been hindered by handling and feeding challenges such as clogging and segregation, which prevent biorefineries from operating at full capacity. These challenges arise primarily due to particle attributes including irregular shape, high flexibility, and high compressibility, leading to interlocking, high compaction, and significant friction under stress consolidation. To enhance operational reliability, it is crucial to focus on preprocessing techniques to address these issues, alongside accurately characterizing the mechanical and physical properties and flow performance of these feedstocks. This study investigates novel preprocessing techniques, including pelletization and torrefaction, to fundamentally alter these particle attributes and improve flowability. Miscanthus, an herbaceous energy crop, was the primary focus of this study. Samples were processed using a Forest Concepts Crumbler rotary shear system and an oscillating multi-stack screen bed to achieve two nominal (baseline) particle sizes: 6mm and 2mm. The study evaluated the efficiency and energy consumption of size reduction, revealing that while 2mm particles required more energy, they exhibited better flowability and higher yield strength compared to 6mm particles. Shear and compression tests assessed the material's shear strength, internal friction, and elastic modulus, while wedge-shaped hopper tests measured the critical arching distance and mass flow rate. The results provide valuable insights into the mechanical properties and processing efficiency of Miscanthus, contributing to the development of a preprocessing framework that enhances energy efficiency and material flowability in bioenergy production. However, further preprocessing and development are required to optimize this framework fully.

09 - BIOMASS FUELS↗

Computational materials assessment of the D/Li-stripping neutron source as a prototypical facility for fusion materials testing

As the US fusion materials community awaits the selection and design of a fusion prototypical neutron source (FPNS), a risk reduction exercise has been conducted to (i) provide an updated materials performance evaluation using state-of-the-art computational materials modeling, (ii) expand on legacy analysis based on pure Fe to other relevant fusion structural materials types, and (iii) ensure that materials response under FPNS operational conditions is consistent with referential fusion reactor conditions. The current paper describes the efforts undertaken to assemble a comprehensive computational methodology that includes neutronics, primary damage calculations, atomistic simulations of displacement cascades, chemical inventory evolution calculations, and a computational thermodynamic analysis of emerging phases during irradiation. Our work extends existing studies in pure Fe to reduced-activation ferritic/martensitic steels, tungsten, silicon carbide, and vanadium alloys. We focus on the single-beam deuteron/lithium-stripping neutron source behind the IFMIF-DONES concept, which we assess against ITER, two DEMO designs, and an ideal pure 14-MeV flux. Our analysis indicates that, within standard uncertainties inherent to the models employed, the DONES concept adequately captures fusion conditions in the four materials analyzed. Our work is intended as a comprehensive irradiation damage analysis of fusion-representative neutron sources, to be used for further neutron source evaluation and fusion facility operation.

Marian, Jaime [Univ. of California, Los Angeles, C↗

Highly accelerated life testing (HALT): A review from a statistical perspective

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated-stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). Here, this review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high-stress test-analyze-fix-test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.

97 MATHEMATICS AND COMPUTING↗

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗

Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework

Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗

A Versatile Simulated Data Transport Layer for in Situ Workflows Performance Evaluation

In situ processing does not only allow scientific applications to face the explosion in data volume and velocity but also to address the time constraints of many simulation-analysis workflows by providing scientists with early insights about their applications at runtime. Multiple frameworks implement the concept of a data transport layer (DTL) to enable such in situ workflows. These tools are very versatile, directly or indirectly access the data generated on the same node, another node of the same compute cluster, or a completely distinct node, and allow data publishers and subscribers to run on the same computing resources or not. This versatility puts on researchers the onus of taking key decisions related to resource allocation and how to transport data to ensure the most efficient execution of their in situ workflows. However, domain scientists and workflow practitioners lack the appropriate tools to assess the respective performance of particular design and deployment options. In this paper we introduce a versatile simulated DTL designed to provide researchers with insights on the respective performance of different execution scenarios of in situ workflows. This open-source, standalone library builds on the SimGrid toolkit and can be linked to any SimGrid-based simulator. It facilitates the evaluation of the performance behavior, at scale, of different data transport configurations and the study of the effects of resource allocation strategies. We demonstrate the scalability, versatility, and accuracy of this simulated DTL by reproducing the execution of two synthetic benchmarks and of a real-world in situ workflow composed of an MPI application and a parallel data analysis. Results of simulations run on a single core show that the proposed library can simulate the interactions of tens of thousands of simulated processes deployed on two interconnected commodity clusters in a few seconds, and the execution by a thousand simulated processes of an in situ workflow in less than three minutes.

Suter, Fred [ORNL] (ORCID:0000000319021955)↗

GaN Core-shell Nanofin Vertical Transistor (CoNVerT): A New Direction for Power Electronics (Final Scientific/Technical Report)

A novel power transistor architecture, the GaN c ore-shell n anofin ver tical transistor (CoNVerT) to address fundamental challenges in realizing the ultimate limit of GaN power transistor performance was explored experimentally. This technology promises ultra-high-efficiency high voltage/high power applications (e.g. DC/DC converters, motor control, fast charging, actuation), as well as to operate in harsh environments. The device exploits a vertical superjunction structure based on an experimentally-validated core-shell nanofin growth process in which lateral p-n heterojunctions are formed in a single growth step, while still maintaining vertical current flow for compact die size and low cost. The concept leverages the best properties of GaN for mid-range voltage applications: high mobility, high breakdown voltage, and native heterojunction enhancement-mode operation. Due to the crystallographic nature of the nanofin growth by molecular beam epitaxy, the sidewall heterojunctions occur on non-polar planes, resulting in ultra-smooth interfaces for high mobility, no sidewall etch damage and related surface/interface states, and elimination of piezoelectric effects that can limit reliability in conventional structures. This also facilitates superjunction formation for maximum device performance, and the selective-area growth of the nanofin results in dislocation-free growth, even on low-cost Si (111) substrate. In this program, core-shell nanofins were grown by molecular beam epitaxy, test structures to evaluate the doping, resistivity, and other electrical properties were fabricated, and the material and test structures were characterized in detail. The work identified clear potential (e.g., the doping was well controlled as required for superjunction concepts), but also additional areas that require additional effort to resolve (some unexpected crystal defects were encountered that require additional engineering to overcome). Simulation studies of the proposed concept validate that the fundamental approach is very promising, but additional effort in experimental realization is needed.

42 ENGINEERING↗

THz Radiation Generation to Enable Internal Magnetic Field Measurement of Burning Plasmas (Final Scientific Report)

A one-year experimental program was performed using the Multi-TeraWatt (MTW) laser at the Laboratory for Laser Energetics (LLE) to investigate the efficiency and physical process of laser-driven—wire THz generation. This process was evaluated as a potential high-repetition-rate source of powerful THz pulses for use in THz pulsed polarimetry of a moderate-density magnetic-confinement fusion concept developed by TAE. The goal was to develop a source for short pulses in the THz regime (150 μm wavelength) containing 10’s of mJ. The campaign tested the impact of Cu wire diameter (25, 75, 160 μm), length (250 – 750 μm), and laser irradiation orientation on THz production efficiency in comparison to 20-μm thick Cu foils. Of these targets, the 160 µm diameter, 750 µm long wires with sharpened tips and irradiated at the base were found to produce the highest energy and shortest wavelength THz pulses, exceeding 2.5 Joule/sr and meeting the requirements for the polarimetry diagnostic. The brightest THz signal was radiated in the direction of the sharpened wire tip. A combination of two models – a traveling wave antenna combined with coherent transition radiation – describes the emission pattern, pulse energy, and spectrum observed in the experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rotary Inertia Friction Welding of Dissimilar High-Strength 422 Martensitic Stainless Steel and 4140 Low Alloy Steel for Heavy-Duty Engine Piston Fabrication

AISI 422 martensitic stainless steel with superior high temperature performance (oxidation resistance and strength) is under evaluation for replacing current heavy-duty piston crown materials, AISI 4140 martensitic steel and micro alloyed steel (MAS) 38MnSiVS5, to fabricate a multimaterial piston. This multimaterial piston concept further improved power density and fuel economy by allowing heavyduty diesel engines to operate at higher temperatures and pressures. Joining AISI 422 steel piston crowns with AISI 4140 steel piston skirts is a key manufacturing step for this multimaterial piston. However, the significant differences in strength, elevated temperature flow stress, alloy chemistry, and temper resistance between these two martensitic steels cause some weldability issues (cracking) and metallurgical challenges (alloying element migration/segregation) when using conventional fusion-based welding processes. Rotary inertia friction welding (RIFW), a solid-state welding process, has been the preferred method to join 4140 crowns to 4140 skirts (and MAS crowns to MAS skirts) in high-volume production of current heavy-duty diesel engine pistons. It has been used to join these two materials with relatively comparable alloy chemistry to fabricate pistons with MAS skirts and 4140 crowns. Meanwhile, RIFW has also been a preferred method of dissimilar metal welding. However, RIFW of dissimilar high-strength martensitic steels has yet to be widely pursued. The interfacial microstructure complexities created by the thermomechanical process and highly nonequilibrium phase transformations during RIFW are a significant challenge for understanding and predicting their joining behavior and have not been reported in detail. Here, in this work, defect-free AISI 422 steel-AISI 4140 multimaterial pistons were successfully fabricated using the RIFW process. The interfacial microstructure and mechanical properties of dissimilar 422/4140 steel RIFW in the as-welded condition were experimentally studied in detail. The results provide critical baseline information for understanding RIFW mechanisms and guiding subsequent postweld heat treatment (PWHT) practice.

36 MATERIALS SCIENCE↗

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

Control of wakefield in sub-THz dielectric-lined waveguides using multiple-bunch excitation

Beam-driven wakefield accelerators offer the potential to achieve accelerating fields approaching the sub-GV/m range, paving the way for compact and cost-effective next-generation high-energy colliders. This method typically employs a two-bunch system: a drive bunch that excites an electromagnetic wakefield in a solid-state or plasma medium, and a witness bunch that extracts energy from the wake for acceleration. Our research focuses on two key challenges in wakefield acceleration using structures. First, we investigate strategies to suppress transverse instabilities by employing non-cylindrical geometries that damp dipole modes. Second, we explore methods to precisely terminate the wakefield after the interaction region, thereby improving the efficiency of energy transfer. This paper presents detailed simulation results and the corresponding experimental design developed to validate these concepts. Furthermore, the proposed experiment will be carried out at the Argonne Wakefield Accelerator (AWA) facility, focusing on controlling wakefield duration through tailored drive and witness bunch configurations and evaluating dielectric-lined structures with non-cylindrical cross sections.

43 PARTICLE ACCELERATORS↗

Human Factors Considerations in Artificial Intelligence Applications for Nuclear Power Plants

In recent years, there has been a wave of artificial intelligence (AI) technologies that offer to solve problems from shopping habits to mortgage approvals to critical systems operations. The rapidity of the development of these systems has led to both excitement and apprehension about the roles these systems should play in our modern societies. Furthermore, this paper focuses on the critical infrastructure industry, in general, and nuclear power generation, in particular, and seeks to scrutinize how we can leverage these novel technologies in human-centered ways to maintain or enhance the established high levels of reliability and resilience in these industries. First, we discuss the broader aspects of cognitive systems and activities that are critical to understanding the human-AI space. Then we explore different approaches to explainability in AI and the notions of trust. We then move on to discuss several human factors concepts and methods and how they can support the design of human-AI teams. We then explore recent research related to nuclear power that has been undertaken and evaluate the current industry and regulatory landscapes. Finally, we discuss identified research gaps and recommendations for solving these for the critical infrastructure space.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Technical Information Needs and Regulatory Considerations for Front-End Transportation Activities of HALEU Fuel Feed Material

This report fulfills task order number 31310022F0033 Task 1 Assessment of technical information needs and considerations for front-end transportation activities for HALEU fuel feed material. This assessment primarily focuses on the transportation outlook and packaging requirements for transporting high-assay low-enriched uranium (HALEU) fuel feed material. The regulatory framework is described in section 3.0. In section 4.0 the specific issues associated with reviewing HALEU feed material packages are discussed. The rest of the report discusses the need for new packages and Department of Energy progress on HALEU production. Through this evaluation it is shown that the 5% enrichment barrier between low-enriched uranium and HALEU is a significant challenge to transportation packaging. However, there are licensed designs and concepts that can be used to transport HALEU feedstock. No significant issues were identified through the HALEU range up to 20% enriched.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Feasibility Assessment of Using Electrical Impedance Tomography for Damage Localization in Graphite Microreactor Components

Microreactors have great potential to decrease capital costs and construction timelines, reducing the barriers to implementing advanced nuclear reactor technologies. However, the lower power output of these microreactors introduces economic challenges if the operation and maintenance costs cannot be reduced sufficiently. Many microreactor concepts use graphite materials for in-core moderator and structural purposes, which will require periodic inspection or, ideally, in situ structural health monitoring. This work describes an initial evaluation of the feasibility of leveraging graphite’s semiconducting properties to perform electrical impedance tomography (EIT) for defect localization. First, a study was performed to identify the best methods for bonding electrical contacts to minimize the effects of contact resistance that interfere with impedance measurements of the graphite. After determining the best bonding approach, electrodes were attached to multiple graphite components with varying geometries (e.g., simple block and more representative microreactor hexagonal block). In parallel, finite element analysis approaches were developed and implemented to analyze the impact of defects and contact resistances and to inform an iterative inverse model for reconstructing the conductivity distribution. The results of this study show that defect localization in graphite components is possible using EIT if a sufficient number of electrodes (to improve spatial resolution) can be bonded using a technique with very low contact resistance and those contact resistances remain stable during reactor operation. If the reactor core and vessel design do not allow electrodes to be bonded during reactor operation, then it may be possible to detach/reattach electrodes between reactor operation and outages if a suitable mechanical connection that offers repeatable contact resistance can be identified. Alternatively, future work could focus on identifying contacts that can survive the harsh reactor operating environment so that contacts do not need to be removed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multiphysics Analysis of Li Cooled Divertor Substrate During Loss of Coolant Accident (LOCA)

In the ongoing study of potential designs for liquid metal (LM) plasma-facing components (PFCs), so-called “slow” and “fast” Li flow divertor concepts are under investigation. In the previous studies on design and analysis of the slow Li flow divertor and comparison with the fast Li flow divertor, the magnetohydrodynamics (MHD)/heat transfer effects of the Li flowing inside the substrate as a second coolant were comprehensively investigated under the normal steady-state operation conditions. Here, in the present study, the multiphysics analysis is extended to the unsteady abnormal divertor scenario where the Li layer on top of the substrate does not provide full coverage or even totally disappears for a certain period of time, so that the substrate becomes directly exposed to the incident high plasma heat flux. Such an unwanted event may happen regardless of the concept of the divertor and is worth detailed investigations, typically referred to as a loss of coolant accident (LOCA). To address this situation, a simplified scoping analysis is conducted first in 2-D, and then an integrated 3-D modeling is performed using a time-dependent multiphysics model in COMSOL Multiphysics that integrates LM MHD, heat transfer, and solid mechanics. The main goal is to evaluate conditions under which the major material limits, such as the maximum allowable temperature, stress, and displacement of the substrate, can still be met. It was shown that the maximum time over which the substrate of RAFM steel can retain structural integrity during the LOCA is around 0.2 ∼ 0.3 s. Any divertor concept that utilizes RAFM steel as a substrate material and liquid Li as a second coolant should take such a permitted time into consideration.

divertor↗

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗