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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 55 records · Page 3

CORE-BFS: Communication-Optimized REctangular-partitioned BFS Achieving 160.845 TeraTEPS on Frontier Supercomputer

Distributed Breadth-First Search (BFS) is fundamental to many large-scale graph applications, but its performance on parallel systems is often limited by high communication overhead. This paper presents CORE-BFS, an extremely scalable GPU-based BFS implementation that introduces a unique rectangular 2D partitioning-based design for Frontier supercomputer. To further improve performance, we propose four key optimizations: (1) Rectangular 2D-partition specific data formats that use two compressed row and one compressed column status array bitmaps combined with a Double Compressed Sparse Row (DCSR) format per partition, reducing memory footprint and inter-rank traffic; (2) Adaptive frontier & communication strategy that unifies top-down and bottom-up traversal on the rectangular layout, uses lazy synchronization in top-down levels, and switches variants based on frontier size to minimize communication overhead; (3) Frontier-split degree-aware update that maps frontier vertices to thread-centric, wavefront-centric, and block-centric kernels based on their degree to improve GPU utilization and memory coalescing; (4) Row-reduction pipeline that overlaps bottom-up adjacency list processing with row-wise bitmap reduction to hide inter-rank latency. Together, these techniques increase parallelism while reducing memory and communication overhead. On the Graph500 benchmark, CORE - BFS scales up to 9,248 Frontier nodes with scale-42 graphs and reaches 160.845 TTEPS, delivering a 5.42 × speedup over our previous Frontier implementation.

Yang, Haoshen [Rutgers University]↗

Pathways towards Valid Data: Assessment of Optimized Packaging Strategies for Core Components - 18158

Every company that runs nuclear power plants needs a strategy for disposal of the radioactive waste and for decommissioning and dismantling of its nuclear reactors. The dismantling progress of several German NPPs is already in an advanced stage. Hence, particularly highly activated core components have to be disposed of as radioactive waste. Nevertheless, this is also an issue during the operating phase due to necessary replacements of highly activated core components such as PWR control elements or RPV heads. The conditioning of waste packages for final disposal in the German repository Konrad requires the core components to be dismantled, packaged and dried. Therefore, a qualified packaging strategy is needed to ensure a reliable compliance with the protection objectives of the repository and an optimized utilization of prescribed contingents. Exemplified by PWR control elements a pathway is drawn how to perform an optimized packaging strategy in compliance with the protection objectives of the repository based on only few relevant radionuclides derived from activation calculations. For these calculations, particularly the influence of trace impurities in the materials has to be considered and their amounts have to be verified or analyzed by sampling. Furthermore, low nuclide activities from contamination cannot simply be neglected because some of them are obliged to be declared or their radiological relevance has not been sufficiently determined. Due to various influence factors, qualified sampling strategies need carefully considered concepts. Therefore, detailed planning facilitates the qualification and approval process and reduces the costs for analyses and the number of containers. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Bayesian Optimization for Reactor Design Optimization

This study present a test case in which the Bayesian Optimization method is applied to a simulation-based reactor core design optimization problem. The test case aims to showcase the potential of an automated design optimization algorithm for reactor designs by streamlining the reactor core design workflow, given the high computational cost of simulations. The contributions of this work are threefold. First, the existing HTGR model is converted into a simulation-based design optimization test case by developing a pipeline that enables modification of key design parameters and evaluates design performance based on simulation outputs. Second, Bayesian Optimization is implemented and adapted to demonstrate the feasibility of automatic design optimization for nuclear reactor core. Proposed approach leverages Gaussian Process models to characterize the relationship between design variables and performance metrics, while incorporating novel acquisition functions that balance exploration of the design space with exploitation of promising configurations. This implementation lays the foundation for the future developments of reactor design optimization algorithms.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

A Metaheuristic Optimization Tool for High Flux Isotope Reactor Low-Enriched Uranium Core Design

A metaheuristic optimization tool was developed for design optimization studies of a High Flux Isotope Reactor low-enriched uranium core. Low-enriched uranium core design presents a multidimensional, multi-objective optimization problem that requires a systematic approach to avoid arbitrary design decisions. This tool searches this multidimensional design space to generate an optimum design, considering a weighted design performance metric that includes several parameters. The search methods are discussed herein, and the tool is applied to uranium silicide fuel designs.

Variansyah, I.↗

PWR loading pattern optimization with reinforcement learning

The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stochastic Optimization to Find Optimum Beginning-of-Life Core Configuration of Stable Salt Reactor with Online Refueling

A stochastic optimization method has been developed to find an optimum equilibrium cycle core configuration of the waste-burning stable salt reactor, which is a fast-spectrum molten salt reactor with frequent online refueling. An optimum core configuration was determined with the goal of minimizing radial power peaking. Because of the vast number of potential candidate core configurations, stochastic optimization was applied based on simulated annealing and an additional acceleration method, which screened out unpromising core configurations. It has been demonstrated that the developed stochastic optimization method successfully finds the optimal core configuration regardless of the initial guess and outperforms the gradient descent approach. In addition, it has been observed that the use of a so-called out-in core configuration as the initial guess speeds up convergence of the iterative solution more than five times. Based on the searched optimum equilibrium cycle core configuration, new beginning-of-life (BOL) core configurations have been developed. In conclusion, the new BOL core configurations will be used in developing optimum refueling strategies.

Moltex static salt reactor↗

A strategy for automated core design to increase economic viability and minimize fuel fragmentation, relocation, and dispersal susceptibility in high-burnup cores

The nuclear industry aims to increase the cycle length of pressurized water reactors from 18 to 24 months to increase power plant capacity factors and economic viability. These cycle length extensions will inherently require fuel rods to exceed the current peak rod average burnup limit of 62 GWd/MTU. A chief concern of operating beyond the current burnup limit is the fuel fragmentation, relocation, and dispersal (FFRD) phenomenon in which pulverized fuel fragments can axially relocate and escape through a burst in the cladding formed during a loss-of-coolant accident. In this work, we demonstrate an approach for automating core design employing an optimization tool based on a penalty-free, parallel simulated annealing algorithm to produce pressurized water reactor core designs with two different optimization objectives. The two objectives were to produce core designs with (1) mitigated FFRD susceptibility while achieving 24-month cycle lengths (2) maximum cycle length with no regard for the likelihood of FFRD. Batch size was considered in tandem with both cases to maximize economic viability. The PARCS nodal model was the primary reactor physics tool used in the optimizations and used nuclear cross sections calculated with 2D Polaris lattice physics models. Reactor performance and safety characteristics of the optimized cores were verified using high-fidelity Virtual Environment for Reactor Applications models. The core designs produced by the optimization tool are compared with each other and to a high-burnup core design produced and analyzed in previous works to highlight the fuel management strategies that may enhance high-burnup reactor safety and economic viability. The optimized cores satisfied their respective objective functions, producing a maximum cycle length of 720 effective full-power days in one core design and one that may reduce FFRD susceptibility by up to 50% based on the first-order approximation to FFRD risk formulated in this work. The optimized cores met most constraints but exceeded the hot channel factor limit, especially in FFRD cases where fresh fuel carried more power. Furthermore, this highlights the need for future lattice-level optimizations and broader assembly options.

Cycle length↗

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Geometries of edge and mixed dislocations in bcc Fe from first principles calculations

We use density functional theory (DFT) to compute the core structures of $a_0[100](010)$ edge, $a_0[100](011)$ edge, $a_0/2[\bar{1}\bar{1}1](1\bar{1}0)$ edge, and $a_0/2[111](1\bar{1}0)$ $71^{\circ}$ mixed dislocations in body-centered cubic (bcc) Fe. The calculations are performed using flexible boundary conditions (FBC), which effectively allow the dislocations to relax as isolated defects by coupling the DFT core to an infinite harmonic lattice through the lattice Green function (LGF). We use the LGFs of the dislocated geometries in contrast to most previous FBC-based dislocation calculations that use the LGF of the bulk crystal. The dislocation LGFs account for changes in the topology of the crystal in the core as well as local strain throughout the crystal lattice. A simple bulk-like approximation for the force constants in a dislocated geometry leads to dislocation LGFs that optimize the core structures of the $a_0[100](010)$ edge, $a_0[100](011)$ edge, and $a_0/2[111](1\bar{1}0)$ $71^{\circ}$ mixed dislocations. This approximation fails for the $a_0/2[\bar{1}\bar{1}1](1\bar{1}0)$ dislocation however, so in this case we derive the LGF from more accurate force constants computed using a Gaussian approximation potential. The standard deviations of the dislocation Nye tensor distributions quantify the widths of the dislocation cores. The relaxed cores are compact, and the local magnetic moments on the Fe atoms closely follow the volumetric strain distributions in the cores. We also compute the core structures of these dislocations using eight different classical interatomic potentials, and quantify symmetry differences between the cores using the Fourier coefficients of their Nye tensor distributions. Most of the core structures computed using the classical potentials agree well with the DFT results. Furthermore the DFT core geometries provide benchmarking for classical potential studies of work-hardening, as well as substitutional and interstitial sites for computing solute-dislocation interactions that serve as inputs for mesoscale models of solute strengthening and solute diffusion near dislocations.

36 MATERIALS SCIENCE↗

Scenario optimization for the tokamak ramp-down phase in RAPTOR: Part B. safe termination of DEMO plasmas

An optimized plasma current ramp-down strategy is critical for safe and fast termination of plasma discharges in a tokamak demonstration fusion reactor (DEMO), both in planned and emergency scenarios, avoiding plasma disruptions and excessive heat loads to the first wall. Plasma stability limits and machine-specific technical requirements constrain the stable envelope through which the plasma must be navigated. Large amounts of auxiliary heating are required throughout the ramp-down phase, to avoid a radiative collapse in the presence of intrinsic tungsten and seeded xenon impurities, as quantitatively estimated in this work. As the plasma current is reduced, the current density becomes increasingly peaked, reflected by a growing value of the internal inductance $\ell$ $i3$ , resulting in reduced controllability of the vertical position of the plasma. The feasibility of different plasma current ramp-down rates is tested by applying an automated optimization framework embedding the RAPTOR core transport solver. Optimal time traces for plasma current $I$ $p$ $(t)$ and plasma elongation $κ(t)$ are proposed, to satisfy an $I$ $p$ -dependent upper limit on the plasma internal inductance, as obtained from vertical stability studies using the CREATE-NL code, as well as a constraint on the time evolution of $q$ 95 , to avoid an ideal MHD mode. A negative current density near the plasma edge is observed in our simulations, even for the most conservative $I$ $p$ ramp-down rate, indicating significant transient dynamics due to a large resistive time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Abstract for CRADA between NETL and Rivalia Chemical Co

The National Energy Technology Laboratory (NETL) will assist Rivalia Chemical Co (Participant) with system analyses to aid the Participant with setting priorities and securing funding. The Participant is an early-stage startup pioneering new chemical extraction technology to solve two important problems: critical mineral scarcity and coal ash waste management. The U.S. generates coal fly ash from coal combustion for power generation and has amassed over two billion metric tons of ash, which contains valuable rare earth elements. The ash is often stored in unlined ponds and frequently contaminates the local environment. The Participant’s patent-pending process harvests rare earths from ash, then transforms the residual ash for use in green concrete, providing an economic pathway for utilities to empty and remediate the ash ponds. Founder Laura Stoy created the company in July 2022 after developing the core intellectual property during her Ph.D. at the Georgia Institute of Technology. Stoy is currently participating in the Chain Reactions Innovations (CRI) program at the U.S. Department of Energy (DOE) Argonne National Laboratory (ANL) where she will be optimizing the core technology and scaling from bench scale to demonstration scale. The technology has been validated at bench scale (TRL3); the goal is to approach TRL5 by the conclusion of the CRI program and prepare to raise capital investment for a pilot facility. NETL and the Participant will develop an updated technoeconomic analysis (TEA) and identify key sustainability performance parameters to inform ’s research and development priorities and de-risk the technology. NETL will also provide the Participant with guidance to prepare a more detailed life cycle assessment (LCA), and a narrative on the Participant’s product markets. These tools will aid the Participant with the next steps of commercialization.

01 COAL, LIGNITE, AND PEAT↗

Core design and performance of the Westinghouse lead fast reactor with UO 2 and MOX configurations

For this work, Westinghouse partnered with Argonne National Laboratory to design, model and optimize UO 2 - and MOX-fueled core designs for a medium size (950 MWt) Lead Fast Reactor that was pursued by Westinghouse. Using Argonne’s suite of reactor analysis codes together with Westinghouse fuel cost economic models, thousands of candidate cores were considered to achieve the economics-optimized cores presented in this paper. This optimization process considered detailed reactor physics, fuel performance, transient performance, and fuel economics models. The reactor performance of the resulting optimized UO 2 - and MOX-fueled core designs are described and compared in this paper. Both cores show fuel performance and transient behavior that is considered acceptable for the optimization presented herein, while further testing campaigns on material performance in high-temperature liquid lead will be required to confirm acceptability at the operating conditions chosen. A multi-batch strategy was selected for the UO 2 core for best fuel utilization with minimum fuel inventory costs. A single-batch fuel management was instead selected for the MOX core to maximize cycle length and minimize the impact of the longer refueling outage resulting from the higher decay heat of the discharged MOX fuel relative to the discharged UO 2 fuel, requiring a longer cooling time before dry-lift of discharged fuel could take place.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

RISMC Industry Application no. 1 (ECCS/LOCA) Core characterization automation: Reference PWR designs for IA no. 1

The U.S. NRC is currently proposing rulemaking '10 CFR 50.46c' to revise the loss-of-coolant-accident (LOCA) and emergency core cooling system (ECCS) acceptance criteria to include the effects of higher burn-up on cladding performance. The key implications of this proposition are that both cladding and ECCS performance need to be considered in a coupled manner. This implies that LOCA methodologies will need to be updated for regulatory purposes. The Risk-Informed Safety Margin Characterization (RISMC) Pathway, as part of the DOE Light Water Reactor Sustainability (LWRS) research and development program initialed several programs at the Idaho National Laboratory (INL) to support the industry by offering potential solutions to this new LOCA/ECCS analysis. One of these programs is the Industry Application no. 1 (IA1). It's goal is to develop an integrated evaluation model called LOCA Toolkit for the US (LOTUS) to revisit how risks are evaluated in a LOCA under 10 CFR 50.46c. The focus of LOTUS is to establish the automation interfaces among the physics disciplines involved, namely the core design automation, the fuels/clad performance, the system analysis, the risk assessment and the core design optimization. The risk-informed margins management approach for IA1 will provide a means of quantifying the impact on the key LOCA analysis figures-of-merit like peak cladding temperature (PCT), equivalent cladding reacted (ECR), etc. of a change in LOCA analysis inputs. The information obtained can then be used for decision-making and margin management. The modular approach for LOTUS will enable plant owners/vendors to further customize the LOTUS framework for use within their established codes and methods. One of the LOTUS modules deals with the core design automation (CD-A). The purpose of this module is to supply the LOCA analysis with initial conditions, i.e. assembly/pin power histories, power shapes, etc. to be employed by the Fuels/Clad Performance (EP) and System Analysis (SA) modules. In the CD-A module, the plant owner/operator will characterize his core design with the tools he has. For the current LOTUS demonstration, the tools used are the already coupled codes PHISICS and RELAP5-3D2,3. Cross section generation will be done using the Studsvik lattice code HELIOS-2.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of New Reactor Core Configuration for Power Uprate - Fuel Reload & Heat Processing Analyses, Core Design, System Safety Assessments, and Fuel Performance Analyses

With the passage of the Infrastructure Investment and Jobs Act in 2021 and the Inflation Reduction Act (IRA) in 2022, the United States stands at a critical juncture for the future of nuclear power. These landmark policies provide significant support for clean energy initiatives, positioning nuclear power as a key component of the nation’s strategy to reduce carbon emissions and achieve energy security. This growing emphasis on nuclear energy is driven by the need for reliable, low-carbon power sources as the country transitions away from fossil fuels. Federal policy, along with increasing state-level support, is encouraging investment in nuclear technology advancements to meet these demands. Building new nuclear power plants (NPPs), however, presents significant challenges due to high costs and long construction timelines. As a result, increasing the power output of existing NPPs through power uprates has emerged as a more feasible and cost-effective strategy. One key area of advancement is the development of accident-tolerant fuel (ATF), such as chromium-coated zirconium alloy cladding, which offers enhanced material performance, enabling power uprates in light water reactors (LWRs). Given the growing demand for nuclear energy fueled by federal policies and state initiatives, it is essential to evaluate the feasibility and benefits of significant power uprates in existing pressurized water reactors (PWRs) using advanced fuel technologies. The introduction of ATF concepts opens new opportunities for safely and economically achieving these power increases. Assessing whether these innovations can support substantial power uprates while maintaining operational safety is crucial to maximizing the potential of the nation’s existing nuclear infrastructure. This project aims to explore how power uprates can be achieved by boosting reactor thermal power output and optimizing reactor core design, while ensuring the safety and economic viability of NPPs. Specifically, it will focus on demonstrating the technical and economic feasibility of power uprates in a PWR using low 5-10% enrichment uranium (LEU+) high burnup (HBU) fuel combined with ATF concepts. In fiscal year 2024 (FY24), the research and development focus on building foundational models and conducting multi-physics performance and safety analyses to support the power uprate. The findings of the study would be shared through LWRS Seasonal Meetings, conferences and workshops with utility companies and researchers. These also serve as a basis for further study of fuel reloading optimization with ATF claddings.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dependence of the boundary heat flux width on core and edge profiles in Alcator C-Mod

This work presents new evidence that the heat flux width, λ q , in the Alcator C-Mod tokamak scales with the edge electron pressure, as observed in the ASDEX Upgrade (AUG) tokamak, but the scaling with volume-averaged pressure, $\bar{p}$, from the plasma stored energy, is a better predictor of λ q in Alcator C-Mod than the edge electron pressure. These previous studies, which find that λ q decreases with increasing plasma pressure, imply that a high performance core at high pressure will lead to challenging heat and particle exhaust due to very small λ q . This concern has led to our significant enlargement of the C-Mod database with the electron density, temperature, and pressure profile data from the Thomson scattering and electron cyclotron emission diagnostics. Using the C-Mod database augmented with new profile data, we find that λ q decreases with increasing edge electron pressure as ${\lambda }_{q}\propto {p}_{\mathrm{e},95}^{-0.26}$, similar to results from AUG, and showing the strength of cross-machine comparisons. We also find that ${\lambda }_{q}\propto {p}_{\mathrm{e},\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e}}^{-0.56}$, consistent with the original finding from C-Mod that the heat flux width scales as ${\bar{p}}^{-0.48}$. The scalings of λ q with separatrix pressure and gradient scale length are found to match the AUG results qualitatively. The C-Mod scalings with edge plasma quantities have more scatter than the $\bar{p}$ scaling, and, importantly, show different trends for H-modes relative to L- and I-mode. Furthermore, investigating the source of this discrepancy presents an opportunity for further study that may improve our ability to predict the heat flux width in different confinement scenarios in the pursuit of optimizing core-edge performance in future reactors.

Alcator C-Mod↗

Optimization of COMPASS-U Support Structure

The global support structure for Compass Upgrade (COMPASS-U) employs many bolted and pinned components to improve the manufacturability of the whole structures. This is a departure from other designs used for highly loaded tokamaks, like Alcator C-Mod which used large forgings. Modeling of the numerous connections and interfaces was a challenge. This article will describe how to optimize the C-frame support structure with the goal to eliminate differential displacements at those interfaces and, importantly, minimize toroidal mutual displacement at the sliding joint of the toroidal field (TF) coils. The global support structure consists of 16 C-frames, and it can be simplified as a 1/8th cyclic symmetry model due to the eight vertical rods mounting that connect bottom CS and PF1-3 assemblies to the C-frames. Structure variants with different connection webs between two neighboring C-frames have been analyzed. The preloading of bolts can be split into several preload substeps to simulate the real assembly process of the COMPASS-U support structure. Additionally, the TF crown and the wedge plate can be further improved to become a solid part to better hold the TF coils.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Studies of the outer-off-midplane lower hybrid wave launch scenario for plasma start-up on the TST-2 spherical tokamak

Abstract Establishment of an efficient central solenoid (CS) free tokamak plasma start-up method may lead to an economical fusion reactor. CS-free start-up using lower hybrid (LH) waves has been studied on the TST-2 spherical tokamak. Plasma current of about a quarter of CS-driven discharges has been obtained fully non-inductively using the outer-midplane and top LH launchers. Recently, an outer-off-midplane LH launcher was developed to achieve higher plasma current by optimizing for core absorption and minimal fast electron losses. Using the (outer-)off-midplane launcher, fully non-inductive plasma current start-up up to about 8 kA was achieved. Coupled ray-tracing and Fokker–Planck simulation was performed on equilibria reconstructed with an extended MHD model. It was found that the experimentally observed plasma current was in reasonable agreement with the numerical simulation. The simulation predicted appreciable orbit losses for the off-midplane launcher driven discharge at the present parameters, which was consistent with the experimentally observed x-ray radiation characteristics. The simulation showed that the current density was saturated for the present off-midplane launcher discharges and higher density and higher LH power was necessary to achieve higher plasma current.

Physics↗