Recent Progress of Plasma Exhaust Concepts and Divertor Designs for Tokamak DEMO Reactors
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We propose a general and tunable platform to realize high-density arrays of quantum spin-valley Hall kink (QSVHK) states with spin-valley-momentum locking based on a two-dimensional hexagonal topological insulator. Through the analysis of Berry curvature and topological charge, the QSVHK states are found to be topologically protected by the valley-inversion and time-reversal symmetries. Remarkably, the conductance of QSVHK states remains quantized against both nonmagnetic short- and long-range and magnetic long-range disorder, verified by the Green-function calculations. Based on first-principles results and our fabricated samples, we show that QSVHK states, protected with a gap up to 287 meV, can be realized in bismuthene by alloy engineering, surface functionalization, or electric field, supporting nonvolatile applications of spin-valley filters, valves, and waveguides even at room temperature.
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This article is dedicated to the memory of Massimo Salvatores and offers an overview of the history of the design of the Fast Neutron Source (FNS) flexible experiment system at the University of Tennessee. Our collaboration with Massimo set much of the over-arching design goals and inspired the concept that we have today. The decision to design the FNS as a subcritical assembly rather than a critical one stems back to discussions with Massimo Salvatores and his advocacy for subcritical Accelerator Driven Systems (ADS) which coincides with lower licensing time, costs and greater safety for a university-operated nuclear experimental facility. The second contribution of Massimo to the design concept of the FNS was the direct instruction to design the FNS as an extremely flexible facility. This article provides an update on the current design concept and discusses the future innovations in design optimization of flexible, re-configurable nuclear experiments.
As part of the severe accident analysis collaboration with Sandia National Laboratories (SNL) and the Nuclear Regulatory Commission (NRC), SCALE models were developed for a fast-spectrum heat pipe reactor. These models were based on the Idaho National Laboratory (INL) Design A concept, which is an alternative design to the Los Alamos National Laboratory (LANL) Special Purpose Reactor (SPR), also known as the Megapower reactor. The model contains 1,134 heat pipes, surrounded by hexagonal fuel elements, with a potassium working fluid; the fuel is UO 2 with 19.75 wt% 235 U enrichment. The model contains axial beryllium oxide (BeO) reflectors above and below the active fuel region along with a radial alumina reflector containing 12 B 4 C control drums. The center of the core is left unfueled to make room for two shutdown control rods, one annular and one solid. The active region of the core was discretized into twenty axial and five radial zones to analyze spatial variations in power and burnup. Infinite lattice unit cell sensitivity studies were used to perform verification between the SCALE and INL models. The eigenvalue results agreed well with the reported results to within roughly 50 percent mille (pcm). Full-core model verification was performed by analyzing system eigenvalues with differing configurations of control drum and shutdown rod positions. These full core results all had eigenvalue differences less than 310 pcm. Control drum and shutdown rod worths were also compared, with differences of 3.2% or less. Using the verified model, the isotopic inventory and decay heat, as well as temperature feedback coefficients, were calculated and provided to SNL as input to the MELCOR severe accident code to analyze potential releases from this class of reactor. The results of the MELCOR analysis are provided in a different report.
In a trend toward clean energy alternatives, recent years have seen great strides in the marine energy space. Consequently, there is a pressing need for the design, development, and validation of novel energy harvesting technologies such as hydrokinetic devices, which capture kinetic energy from waves, tides, and currents. However, these devices span numerous concepts and designs that often lack solid benchmark research that can be freely referenced throughout their development. This work focuses on the design process of an open-source composite hydrokinetic turbine blade for a three-bladed marine turbine rotor assembly with a diameter of 2.5 m. The proposed blade consists of two structural composite skins that are bonded with an adhesive and filled with a foam core. This study also explores and contrasts the efficiency and resolution of low-fidelity rapid design methodologies and comprehensive high-fidelity approaches in the context of blade design, modeling, and analysis efforts, a key objective in this research. Blade hydrodynamic loads were modeled and applied to finite-element blade models to study deformations and potential failure. Ongoing and upcoming efforts will result in blade manufacture and structural testing at the National Renewable Energy Laboratory. In future work, multiple blades will be deployed at the Living Bridge site at the University of New Hampshire and will be compared to rigid aluminum blades of the same geometry, developed by Sandia National Laboratories. Ultimately, this research will lay foundational groundwork for researchers and manufacturers, establishing a baseline composite blade design that will serve as a benchmark in the development of future hydrokinetic turbine blades.
Significance The COVID-19 pandemic has had an unprecedented impact. Although several vaccines have received emergency use authorization, demand has created enormous logistical challenges—including supply, access, and distribution—that justify research for alternative strategies. Phage are viruses that only infect bacteria and can be safely administered to humans. Here, as a proof-of-concept study, we demonstrate that aerosol vaccination with lung-targeted phage particles displaying short SARS-CoV-2 S protein epitopes and subcutaneous vaccination with targeted AAVP particles carrying the entire S protein gene both elicit systemic and specific immune responses in immunocompetent mice. Given their unique attributes, including sturdiness, simple-to-engineer platform, cost-effectiveness for rapid large-scale production, and stability at room temperature, these phage-based approaches may become attractive tools for COVID-19 vaccine development.
Advanced non-light-water reactor components may operate at elevated temperature while experiencing cyclic loading, significant neutron irradiation, and exposure to reactor coolant. ASME Boiler and Pressure Vessel Code, Section III, Division 5, provides design rules for elevated-temperature service but does not include specific procedures to account for environmental effects on material properties. This report develops an initial framework and methodology for an Environmental Effects Design Guide (EEDG) focused on neutron irradiation; coolant-environment effects are reserved for future work. The proposed approach treats irradiation as a property-based overlay on the existing Division 5 design process, with two routes: a sparse-data route applying two reduction factors — FCR on creep-rupture strength and FF on fatigue life — for the creep-fatigue evaluations that typically control the design of advanced high-temperature reactor components, and a fuller framework developing the property-to-rule chain across the four Division 5 checks (primary load, strain limits and ratcheting, creep-fatigue, and buckling), together with swelling and weldments as scope items. Both routes are scoped by an in-pile qualification that restricts the use of post-irradiation-examination-derived properties in regimes where an in-pile mechanism could control the design outcome. Illustrative outputs derived on a compiled annealed Type 316 database — FCR ≈ 0.78–0.86 and FF ≈ 0.4 — demonstrate the calculation method within that specific dataset. The framework is an initial, testable design-rule concept; it identifies a practical path for preliminary design evaluations under sparse data and the material data and testing needed to develop the framework further.
A recent major focus of catalyst research has been on improving the selectivity or atom efficiency of catalytic processes. Perhaps the most subtle and difficult form of selectivity to control is enantioselectivity, a catalyst’s ability to preferentially yield one enantiomer of a chiral product. Since two enantiomers are identical in all respects except for their mirror reflection symmetry, both are formed in non-chiral environments at exactly equal rates; only by introducing some type of chiral modification to the system can the rate of formation of one enantiomer be favored over the other. This has been successfully achieved for homogeneous-phase, organometallic catalysts, but the empirical development of heterogeneous-phase analogs has proven elusive. The design of such heterogeneous-phase catalysts would obviate the need for inefficient purification steps to remove the heavy-metal catalysts. The goal of the proposed research by the Chiral Catalysis Group is to understand the interactions of prochiral reactants on chirally modified surfaces that lead to the preferential formation of one enantiomer over the other. There are two general concepts for designing heterogeneous-phase enantioselective catalysts. The first adopts the strategy used in homogeneous phase, by adding a chiral modifier to the surface. This approach, while conceptually simple has challenges associated with modifying an extended surface. The second concept, which is unique to extended surfaces, is the idea of creating surfaces that are themselves naturally chiral. A fundamental understanding of the interactions that control enantioselectivity will enable the Chiral Catalysis Group to develop the concepts necessary to design novel, heterogenous catalytic materials. Enantioselectivity is also central to catalytic processes that underpin the pharmaceutical and agrochemical industries. With funding from the Department of Energy, the Chiral Catalysis Group has played a leading role in developing a fundamental understanding of chiral catalysis and of the adsorbate structures, interactions and kinetic effects that control heterogenous-phase enantioselectivity. The proposed research program is organized conceptually around three types of enantiospecific interactions: interactions with naturally chiral surfaces; those with modified surfaces categorized as chirally templated surfaces; and one-to-one interactions of prochiral molecules with chiral surface modifiers. Our specific goals are to: (1) determine the structures of chiral surfaces, prochiral reactants, chiral products and chiral modifiers; (2) understand the enantiospecific interactions that occur between prochiral reactants and chiral products with chirally modified surfaces; (3) develop methods for detection of enantiospecific surface phenomena; and (4) elucidate enantioselective reaction pathways and the interactions that control them. The range of expertise within the Chiral Catalysis Group includes molecular-scale theory, surface science experiments, state-of-the-art spectroscopic, kinetic and atomic-scale imaging capabilities carried out in vacuum and under more-realistic liquid- and gas-phase environments complemented by catalytic measurements. By fully integrating such a breadth of approaches and extensive expertise, the Chiral Catalysis Group will, for the first time, be able to understand, rationally design and then control active sites for optimal enantioselectivity. In addition to having a significant impact on the field of chiral catalysis, the proposed research program will further our general understanding of the molecular-scale origins of catalytic selectivity.
Novel, direct-energy drilling technologies such as electro-pulse boring, have the potential to significantly increase the speed and depth of geothermal drilling but have not achieved widespread adoption due to several economic and technical barriers. One major challenge is that these drilling systems require electric power downhole. The current practice is to supply power to the drill string components by running electric cables down the geothermal well, but at the targeted well depths, this practice is cost-inhibitive, inefficient in terms of power consumption, and adds an additional failure point with the long cabling going through a highly corrosive, high-temperature environment. A solution to this problem is to develop high-temperature electric generator technology that can generate the required power downhole. Such a generator must also operate with high efficiency at the target downhole ambient temperature of 250 °C. In this paper, we investigate the various design considerations for this concept and subsequently design the downhole electric generator using a multi-objective design optimization approach. Through electromagnetic-, thermal- and short-circuit fault condition analysis, it is demonstrated that the optimized downhole electric generator concept presented in this paper can meet the performance requirements within this extreme drilling environment. Most remarkably, it is shown that a generator efficiency of 90% is achieved. In conclusion, to validate the results presented in this paper, a prototype generator is built and its performance is measured at 250 °C using a test bench uniquely developed for this application.
Recently, significant advances have been made in designing high-temperature capable nuclear fuels. In parallel, important advances have occurred in design of nanophotonic structures (coatings) with ability to shape the frequencies of light being emitted from hot surfaces. In this project, we bring these materials advances together into a design for a new direct conversion nuclear powered system with high thermodynamic efficiency, inherent safety, and unprecedented reduction in size and weight relative to current designs. The concept involves using the heat generated from nuclear fission to raise the temperature of a selective thermal emitter to >800°C. The selective emitter shifts the normal broad brand emissions of light from its hot surface into the correct near- and mid-IR bands that produce electricity with inexpensive photovoltaic cells. We have designed a new annular flow Lead Fast Reactor (LFR) that minimizes overall reactor/power conversion footprint. The results indicate that the overall microreactor/power-system design offers a 2X reduction in size over existing technology that is based on the sCO 2 reverse compression Brayton cycle. Additionally, the only moving part in our design is a circulation pump to cool the PVT panels.
SAND2023-05107O JuliaOceanWaves is a collection of packages and functions for modeling wave energy converters. The open-source software is designed to be used by the wave energy community to model new concepts, perform design optimization, and more. Capabilities include: • A representation of ocean wave spectra and input/output (e.g. read from National Oceanic and Atmospheric Administration buoys) and post-processing functionalities; • A solver for the linear potential flow radiation and diffraction equations for wave forcing on floating structures. • Solving the floating body linear dynamics in the frequency domain. Future additions to the software will include solving non-linear floating body dynamics in the time-domain through time-marching Ordinary Differential Equation solvers and the pseudo-spectral optimization method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The NIF Sustainment project's goal is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, design analysis and validation, and final design. Future work will focus on building and commissioning the system.
The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The goal of the NIF Sustainment Project is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, final design, and design validation. Future work will focus on building and commissioning the system.
The Handling Frame Assembly Table is a custom designed piece of equipment developed to support the NIF Sustainment Project. The goal of the NIF Sustainment Project is to refurbish the National Ignition Facility (NIF), the world’s largest and most energetic laser, so it can continue advancing research in fusion energy, national security, and high energy density physics. A key aspect of this effort involves replacing all 1,728 blast shields on the NIF, which requires specialized equipment such as the Handling Frame Assembly Table to support the production of new blast shields. This project follows a systems engineering approach that guides the design sequence. This report documents the design process from initial concept through final design, including stakeholder analysis, requirements development, conceptual design, final design, and design validation. Future work will focus on building and commissioning the system.
In blankets of a fusion power reactor, liquid metal (LM) breeders, such as pure lithium or lead-lithium alloy, circulate in complex shape blanket conduits for power conversion and tritium breeding in the presence of a strong plasma-confining magnetic field. The interaction of the magnetic field with induced electric currents in the breeder results in various magnetohydrodynamic (MHD) effects on the flow. Of them, high MHD pressure losses in the LM breeder flows is one of the most important feasibility issues. To design new feasible LM breeding blankets or to improve the existing blanket concepts and designs, one needs to identify and characterize sources of high MHD pressure drop, to understand the underlying physics of MHD flows and to eventually define ways of mitigating high MHD pressure drop in the entire blanket and its sub-components. This article is a comprehensive review of earlier and recent studies of MHD pressure drop in LM blankets with a special focus on: (1) physics of LM MHD flows in typical blanket configurations, (2) development and testing of computational tools for LM MHD flows, (3) practical aspects associated with pumping of a conducting liquid breeder through a strong magnetic field, and (4) approaches to mitigation of the MHD pressure drop in a LM blanket.
Cu-based catalysts hold promise for electrifying CO 2 to produce methane, an extensively used fuel. However, the activity and selectivity remain insufficient due to the lack of catalyst design principles to steer complex CO 2 reduction pathways. Herein, we develop a concept to design carbon-supported Cu catalysts by regulating Cu active sites’ atomic-scale structures and engineering the carbon support’s mesoscale architecture. This aims to provide a favorable local reaction microenvironment for a selective CO 2 reduction pathway to methane. In situ X-ray absorption and Raman spectroscopy analyses reveal the dynamic reconstruction of nitrogen and hydroxyl-immobilized Cu 3 (N,OH-Cu 3 ) clusters derived from atomically dispersed Cu–N 3 sites under realistic CO 2 reduction conditions. The N,OH-Cu 3 sites possess moderate *CO adsorption affinity and a low barrier for *CO hydrogenation, enabling intrinsically selective CO 2 -to-CH 4 reduction compared to the C–C coupling with a high energy barrier. Importantly, a block copolymer-derived carbon fiber support with interconnected mesopores is constructed. The unique long-range mesochannels offer an H 2 O-deficient microenvironment and prolong the transport path for the CO intermediate, which could suppress the hydrogen evolution reaction and favor deep CO 2 reduction toward methane formation. Thus, the newly developed catalyst consisting of in situ constructed N,OH-Cu 3 active sites embedded into bicontinuous carbon mesochannels achieved an unprecedented Faradaic efficiency of 74.2% for the CO 2 reduction to methane at an industry-level current density of 300 mA cm –2 . In conclusion, this work explores effective concepts for steering desirable reaction pathways in complex interfacial catalytic systems via modulating active site structures at the atomic level and engineering pore architectures of supports on the mesoscale to create favorable microenvironments.
Splitting method is a powerful method to handle application problems by splitting physics, scales, domain, and so on. Many splitting algorithms have been designed for efficient temporal discretization. Here, in this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up. We propose a machine learning assisted splitting scheme which improves the efficiency of the scheme meanwhile preserves the accuracy. We consider a recently introduced multiscale splitting algorithms, where the multiscale problem is solved on a coarse grid. To approximate the dynamics, only a few degrees of freedom are solved implicitly, while others explicitly. This splitting concept allows identifying degrees of freedom that need implicit treatment. In this paper, we use this splitting concept in machine learning and propose several strategies. First, the implicit part of the solution can be learned as it is more difficult to solve, while the explicit part can be computed. This provides a speed-up and data incorporation for splitting approaches. Secondly, one can design a hybrid neural network architecture because handling explicit parts requires much fewer communications among neurons and can be done efficiently. Thirdly, one can solve the coarse grid component via PDEs or other approximation methods and construct simpler neural networks for the explicit part of the solutions. We discuss these options and implement one of them by interpreting it as a machine translation task. This interpretation of the splitting scheme successfully enables us using the Transformer since it can perform model reduction for multiple time series and learn the connection between them. We also find that the splitting scheme is a great platform to predict the coarse solution with insufficient information of the target model: the target problem is partially given and we need to solve it through a known problem which approximates the target. Our machine learning model can incorporate and encode the given information from two different problems and then solve the target problems. We conduct four numerical examples and the results show that our method is stable and accurate.