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At least 145 records · Page 8

Peening Techniques for Mitigating Chlorine-Induced Stress Corrosion Cracking of Dry Storage Canisters for Nuclear Applications

Fusion-welded austenitic stainless steel (ASS) was predominantly employed to manufacture dry storage canisters (DSCs) for the storage applications of spent nuclear fuel (SNF). However, the ASS weld joints are prone to chloride-induced stress corrosion cracking (CISCC), a critical safety issue in the nuclear industry. DSCs were exposed to a chloride-rich environment during storage, creating CISCC precursors. The CISCC failure leads to nuclear radiation leakage. Therefore, there is a critical need to enhance the CISCC resistance of DSC weld joints using promising repair techniques. This review article encapsulates the current state-of-the-art of peening techniques for mitigating the CISCC in DSCs. More specifically, conventional shot peening (CSP), ultrasonic impact peening (UIP), and laser shock peening (LSP) were elucidated with a focus on CISCC mitigation. The underlying mechanism of CISCC mitigation in each process was summarized. Finally, this review provides recent advances in surface modification techniques, repair techniques, and developments in welding techniques for CISCC mitigation in DSCs.

Chemistry↗

Cost Effectiveness of Laser Powder Bed Fusion for Heavy Duty Applications

ORNL (Contractor) and Cummins Inc. (Participant) collaborated to determine the cost effectiveness of laser powder bed fusion (LPBF) for heavy duty applications. The team demonstrated that coupons can be fabricated with two distinct process parameters i.e., different process parameters for the bulk and surface of the material. This is important for enabling the manufacturing of components in a production environment where the bulk of the material can be processed rapidly while high quality surface finish can minimize post-process machining as well as enable superior fatigue performance if the material were to be used in as-deposited condition.

36 MATERIALS SCIENCE↗

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↗

Application of Magnetized Target Fusion to High-Energy Space Propulsion

Most fusion propulsion concepts that have been investigated in the past employ some form of inertial or magnetic confinement. Although the prospective performance of these concepts is excellent, the fusion processes on which these concepts are based still require considerable development before they can be seriously considered for actual applications. Furthermore, these processes are encumbered by the need for sophisticated plasma and power handling systems that are generally quite inefficient and have historically resulted in large, massive spacecraft designs. Here we present a comparatively new approach, Magnetized Target Fusion (MTF), which offers a nearer-term avenue for realizing the tremendous performance benefits of fusion propulsion'. The key advantage of MTF is its less demanding requirements for driver energy and power processing. Additional features include: 1) very low system masses and volumes, 2) high gain and relatively low waste heat, 3) substantial utilization of energy from product neutrons, 4) efficient, low peak-power drivers based on existing pulsed power technology, and 5) very high Isp, specific power and thrust. MTF overcomes many of the problems associated with traditional fusion techniques, thus making it particularly attractive for space applications. Isp greater than 50,000 seconds and specific powers greater than 50 kilowatts/kilogram appear feasible using relatively near-term pulse power and plasma gun technology.

Thio, Y. C. F.↗

Perspectives and challenges of ultra-high temperature ceramics for fusion plasma-facing applications

Ultra-high temperature ceramics (UHTCs) offer several potential advantages as plasma-facing components (PFCs) in fusion reactors due to their extreme melting points, tailorable thermal conductivity, and attractive unirradiated mechanical properties including fracture toughness comparable or superior to tungsten. Here, recent developments and material properties of UHTCs are briefly reviewed, along with an overview of limited studies on their responses to neutron irradiation and an evaluation of plasma-surface interactions. Five key research pathways, primarily focused on irradiation effects, for advancing UHTCs in PFC applications are discussed: (1) assessing irradiation effects on the coupled thermal–mechanical performance (2) addressing the lack of studies on irradiation, plasma-surface interactions, and their synergistic effects; (3) investigating high-temperature (>1000 °C) neutron irradiation effects critical for PFC performance; (4) optimizing multi-component UHTC compositions or composites to improve thermal or mechanical properties; (5) enhancing radiation resistance to mitigate microcracking and void swelling through strategies such as increasing sink strength by reducing grain size, introducing fine particles, and leveraging complex concentrated alloy concepts.

36 MATERIALS SCIENCE↗

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Laser Powder Bed Fusion of Steels for Nuclear Applications

This report provides an update on laser powder bed fusion of steels for nuclear applications. This report is a Milestone 3 deliverable in FY2024, under work package CT-24AN130401 to support research and qualification activities supported by the Advanced Materials and Manufacturing Technologies (AMMT) program here at Argonne National Laboratory (ANL). Continuing from FY23, the focus of FY24 for ANL includes further optimization of process parameters for three alloys: A709, G91, G92. The work package also includes fabricating test samples to conduct a thorough microstructural analysis and perform preliminary mechanical testing. For the same, we have used CALPHAD-based thermodynamic kinetic modeling to optimize the experimental activities.

36 MATERIALS SCIENCE↗

Effects of HFIR neutron irradiation on fracture toughness properties of standard and Ni-doped F82H

F82H is the Japanese reference reduced-activation ferritic-martensitic (RAFM) steel for fusion blanket applications. The harsh environment of a fusion reactor, such as neutron irradiation and He/H damage, can result in significant degradation of F82H fracture toughness. Therefore, understanding the fracture toughness behavior of F82H in the fusion environment is critical to ensure the long-term safe operation of the fusion reactor. Here, we summarize seven irradiation campaigns of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) covering five variants of F82H steels, including F82H IEA, F82H Mod3, F82H doped with 1.4% natural Ni, F82H doped with 1.4% 58 Ni, and F82H doped with 1.4% 60 Ni. The irradiation temperatures covered the range from 220 °C to 530 °C and the neutron irradiation dose spanned 4 dpa to 70 dpa. The effects of neutron irradiation temperature, dose, materials composition, Ni doping, and He production on F82H fracture toughness are discussed. Our results showed that irradiation embrittlement monotonically decreased with increasing irradiation temperature until 400 °C for F82H IEA and F82H Mod3. F82H Mod3 showed better fracture toughness than F82H IEA both before and after neutron irradiation. We determined that 1.4% Ni alloying can be applied to F82H for simulating He effect in a fission reactor without jeopardizing the fracture toughness of the material. However, more studies are needed to understand the effect of high dose (>20 dpa) and He production on F82H fracture toughness.

36 MATERIALS SCIENCE↗

A quinary WTaCrVHf nanocrystalline refractory high-entropy alloy withholding extreme irradiation environments

In the quest of new materials that can withstand severe irradiation and mechanical extremes for advanced applications (e.g. fission & fusion reactors, space applications, etc.), design, prediction and control of advanced materials beyond current material designs become paramount. Here, through a combined experimental and simulation methodology, we design a nanocrystalline refractory high entropy alloy (RHEA) system. Compositions assessed under extreme environments and in situ electron-microscopy reveal both high thermal stability and radiation resistance. We observe grain refinement under heavy ion irradiation and resistance to dual-beam irradiation and helium implantation in the form of low defect generation and evolution, as well as no detectable grain growth. The experimental and modeling results—showing a good agreement—can be applied to design and rapidly assess other alloys subjected to extreme environmental conditions.

36 MATERIALS SCIENCE↗

Electromagnetic coil optimization for reduced Lorentz forces

Abstract The reduction of magnetic forces on electromagnetic coils is an important consideration in the design of high-field devices such as the stellarator or tokamak. Unfortunately, these forces may be too time-consuming to evaluate by conventional finite element modeling within an optimization loop. Although mutual forces can be computed rapidly by approximating large-bore coils as infinitely thin, this approximation does not hold for self-forces as it leads to an unphysical divergence. Recently, a novel reduced model for the self-field, self-force, and self-inductance of electromagnetic coils based on filamentary models was rigorously derived and demonstrated to be highly accurate and numerically efficient to evaluate (Hurwitz et al 2024 IEEE Trans. Magn. 60 7001614). In this paper, we present an implementation of the reduced self-force model employing automatic differentiation within the simsopt stellarator design software and use it in derivative-based coil optimization for a quasi-axisymmetric stellarator. We show that it is possible to significantly reduce point-wise forces throughout the coils, though this comes with trade-offs to fast particle losses and the minimum distance between coils and the plasma surface. The trade-off between magnetic forces and coil-surface distance is mediated by the minimum coil–coil distance for coils near the inboard side of the ‘bean’ cross-section of the plasma. The relationship between forces and fast particle losses is mediated by the normal field error. Coil forces can be lowered to a threshold with minimal deterioration to losses. Importantly, the magnet optimization approach here can be used also for tokamaks, other fusion concepts, and applications outside of fusion.

Hurwitz, Siena (ORCID:0000000166599659)↗

Scalable Multiphysics Block Preconditioning for Low Mach Number Compressible Resistive MHD with Application to Magnetic Confinement Fusion

This study investigates multiphysics block preconditioners that are critical in devising scalable Newton–Krylov iterative solvers for longer time-scale fully implicit fluid plasma models. The specific model of interest is the visco-resistive, low Mach number, compressible magnetohydrodynamics (MHD) model. This model describes the dynamics of conducting fluids in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics. The specific application of interest that motivates this study is the macroscopic simulation of longer time-scale stability and disruptions of magnetic confinement fusion devices, specifically the ITER Tokamak. The computational solution of the governing balance equations for mass, momentum, heat transfer, and magnetic induction for resistive MHD systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena as well as the significant range of time and length scales that the interactions of these physical mechanisms produce. To handle the range of time and spatial scales of interest, a fully implicit unstructured variational multiscale finite element formulation is employed. For the scalable solution of the Newton linearized systems, fully coupled block preconditioners are designed to leverage algebraic multigrid subsolves. In conclusion, results are presented for the strong and weak scaling of the method as well as the robustness of these techniques for a large range of Lundquist numbers.

97 MATHEMATICS AND COMPUTING↗

Performance potential of gas-core and fusion rockets - A mission applications survey.

This paper reports an evaluation of the performance potential of five nuclear rocket engines for four mission classes. These engines are: the regeneratively cooled gas-core nuclear rocket; the light bulb gas-core nuclear rocket; the space-radiator cooled gas-core nuclear rocket; the fusion rocket; and an advanced solid-core nuclear rocket which is included for comparison. The missions considered are: earth-to-orbit launch; near-earth space missions; close interplanetary missions; and distant interplanetary missions. For each of these missions, the capabilities of each rocket engine type are compared in terms of payload ratio for the earth launch mission or by the initial vehicle mass in earth orbit for space missions (a measure of initial cost). Other factors which might determine the engine choice are discussed. It is shown that a 60 day manned round trip to Mars is conceivable.-

Fishbach, L. H.↗

A methodology for corrosion testing ODS steels in liquid tin under reactor conditions in HFIR

Liquid metal–based divertor concepts have promising attributes for application in fusion reactors. Liquid tin is being considered as one of those liquid metals due to its excellent thermophysical properties. However, tin is extremely corrosive to steels at elevated temperatures, and the coupled effects of corrosion with neutron irradiation for application in fusion reactors have not been quantified. Researchers at Oak Ridge National Laboratory (ORNL) have designed and irradiated a series of capsules in the High Flux Isotope Reactor (HFIR) to help address gaps in the literature with respect to coupled corrosion and neutron irradiation effects. The capsules are filled with solid tin designed to melt due to the gamma heating in HFIR and allow interaction with the specimens. The capsules contain a SiC thermometer for post-irradiation temperature verification. Five capsules were irradiated in HFIR for 10.5 days, accumulating 0.93 dpa in the FeCrAl specimens. Post-irradiation temperature verification was performed on the SiC thermometers, and temperatures were observed to be higher than what was expected from thermal models. An explanation for the model underprediction is given herein. In conclusion, the capsules described within this article are the first to irradiate liquid metal within the HFIR flux trap and demonstrated the safety basis for continued liquid coolant studies in HFIR.

FeCrAl↗

Specimen Size and Geometry Effects on the Master Curve Fracture Toughness Measurements of EUROFER97 and F82H Steels

EUROFER97 and F82H are two leading reduced-activation ferritic-martensitic (RAFM) steels for fusion blanket applications. Exposure to the harsh environment of fusion reactors can result in severe degradation of materials fracture toughness (FT). Thus, the post-irradiation evaluation of FT is critical to understanding the material behavior. Due to the space constraint of irradiation facilities, the development of small specimen test techniques (SSTT) is necessary to evaluate the performance of irradiated materials. In this study, we evaluated the specimen size and geometry effects on the ductile-to-brittle transition FT of EUROFER97 batch-3 and F82H-BA12 steels. The specimen thicknesses ranged from 1.65 to 12.7 mm and the geometries included 1.65 mm bend bar, 4 mm mini-compact tension (miniCT), and 0.5T compact tension (CT) specimens. Fracture toughness testing and evaluations were performed using the Master Curve method in the ASTM E1921-19 standard. After size correction to 1T size using the Master Curve method, no specimen size effect was observed between the 4 mm miniCT and 0.5T CT specimens for the Master Curve reference temperature T0Q, while the bend bars yielded a higher T0Q. A strong effect of fatigue precrack front straightness on T0Q for 0.5T CT specimens was observed. The minimum number of specimens needed for each specimen geometry has been determined.

Chen, Xiang↗

Plasma Liner Development for MTF Applications: A Status Report

An experimental plasma gun for Magnetic Target Fusion (MTF) applications under development at the NASA Marshall Space Flight Center is described. This gun has been tested experimentally and plasma jet velocities of approximately 50 km/sec have been obtained. The plasma jet structure has been photographed with 10 ns exposure times to reveal a stable and repeatable plasma structure. Data for velocity profile information has been obtained using light pipes embedded in the gun walls to record the plasma transit at various barrel locations. A high speed triggering system has been developed and tested as a means of reducing the gun "jitter". This jitter has been characterized and future work for second generation "ultra-low jitter" gun development is identified.

Eskridge, R. E.↗

Space-Time Data fusion for Remote Sensing Applications

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

carbon dioxide↗