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At least 55 records · Page 3

Scrape-off layer stability, turbulence and transport in MAST-U (Final Report)

U.S. Department of Energy (DOE) supported work at Lodestar Research Corporation under grant DE-SC0019270 is summarized in this final report. The research conducted under this grant explored the properties of the edge plasma in spherical torus magnetic fusion devices. Harnessing the energy that is released in fusion reactions would provide a safe and abundant source of power to meet the growing energy needs of the world population. The edge and scrape-off layer (SOL) region of fusion plasmas is the region where the hot core plasma transitions to a cooler surrounding boundary plasma. The properties of this boundary plasma determine how interactions with material surfaces will impact both the overall device performance and the lifetime of crucial components such as the walls of the device chamber and other hardware. The research carried out studied filamentary plasma instabilities and turbulent transport in the edge and SOL of the MAST U spherical torus.

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Simulations of tokamak edge plasma turbulent fluctuations based on a minimal 3D model

In this study, a new simulation model for tokamak boundary plasma, SOLT3D, is implemented in the BOUT++ framework. The simulation model includes a set of dynamic equations describing collisional boundary plasma and neutral gas in the tokamak scrape-off layer and divertor region. The model is verified against standard linear plasma instabilities and available nonlinear results. For L-mode like conditions, SOLT3D reproduces characteristics of boundary plasma turbulent fluctuations that are similar to published experimental data, in terms of the amplitude and spatial dependence of the fluctuations. It also reproduces realistic plasma fluxes on material surfaces and expected Bohm-like effective radial transport. Plasma fluctuations inferred from the simulations imply inevitably a significant level of intrinsic 'noise' for axisymmetric tokamak plasma transport modeling, introducing errors on the order of unity. In particular, the toroidally averaged atomic rates below 5–10 eV are strongly modified by turbulent plasma fluctuations, which should significantly affect the standard axisymmetric modeling of the tokamak edge plasma and divertor.

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Omnigenous umbilic stellarators

To better understand the dependence of the magnetic field structure in the plasma edge on the plasma boundary shape, in the context of X-point and island divertor designs, we define and develop a class of stellarators called umbilic stellarators. These equilibria are characterised by a single continuous high-curvature edge on the plasma boundary that goes around multiple times toroidally before meeting itself. We develop a technique that allows us to simultaneously optimise the plasma boundary along with a curve lying on the boundary on which we impose a high curvature while imposing omnigenity – a property of the magnetic field that ensures trapped particle confinement throughout the plasma volume. We find that umbilic stellarators naturally tend to favour piecewise omnigenity instead of omnigenity with a specific helicity. After generating omnigenous umbilic stellarators, we design coil sets for some of them and explore the fieldline structure in the edge and its sensitivity to small fluctuations in the plasma. Finally, using single-stage optimisation, we simultaneously modify the plasma and coil shape and propose an experiment to modify an existing tokamak to a finite-𝛽 stellarator using this technique and explore a potentially simpler way to convert a limited tokamak into a diverted stellarator.

fusion plasma↗

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗

LLNL FESP Theory Highlights: August 2024

The 2024 ABOUND SciDAC and BOUT++ combined workshop was held August 5-9 th 2024 at the University of California Livermore Collaboration Center (UCLC) in Livermore. Bringing together leading scientists and researchers from across the globe, this pivotal event focused on advancing plasma physics and boundary plasma dynamics within the context of fusion energy research. Key discussions throughout the meeting highlighted significant advancements in the BOUT++ framework, including enhanced simulations of small Edge Localized Modes (ELMs) and the initiation of integrating the integration of the 5D GEM gyrokinetic turbulence core code with the 2D SOLPS-ITER boundary transport code. These developments are crucial for managing heat loads in fusion reactors and supporting the longevity of plasma-facing components. The event also featured a session on Inter-SciDAC Collaborations, where principal investigators from multiple U.S. FES SciDAC tokamak projects explored opportunities for cross-collaboration. Additionally, the meeting showcased cutting-edge advancements in GPU acceleration and AI/ML technologies, poised to drive the next generation of fusion research. In his closing remarks, Dr. Xueqiao Xu emphasized the importance of the collaborative efforts and discussions that took place, noting their potential to shape future breakthroughs in fusion energy. The event underscored the global nature of the BOUT++ collaboration, with contributions from over 57 institutions worldwide. The 2024 BOUT++ and ABOUND Joint Hybrid Meeting continues to drive forward the research and innovations needed to achieve fusion energy, setting the stage for future collaboration and discovery.

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Divertor detachment in the pre-fusion power operation phase in ITER during application of resonant magnetic perturbations

Detachment of the divertor plasma during application of resonant magnetic perturbation (RMP) fields is evaluated for hydrogen H-mode plasma during the first pre-fusion power operation (PFPO-1) phase in ITER by 3D plasma boundary modelling with EMC3–EIRENE. Plasma response effects from a linearized, resistive, single fluid MHD model are discussed, which includes partial screening of the externally applied field—but also field amplification near the separatrix. Furthermore, this field amplification is found to play a pivotal role for the magnetic footprint on the divertor targets, but is sensitive to model parameters. Extensions of the footprint beyond the straight portions of the ITER vertical divertor targets, optimized for high stationary heat flux handling, may be possible depending on the level of toroidal rotation in the plasma. Exhaust from the bulk plasma is guided by the helical corrugations (lobes) of the perturbed separatrix, and this results in an upstream heat flux that is distributed over these lobes with lower peak values than in the typical radial heat flux profiles seen in the absence of magnetic perturbations. As a consequence, an earlier onset (with respect to the upstream density) of detachment is found in the traditional strike zone when RMPs are applied, but secondary, non-axisymmetric strike locations appear—and those remain attached at temperatures above 10 eV. Neon seeding can mitigate these non-axisymmetric heat loads, but this becomes less efficient for large magnetic footprints.

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Latent space mapping: Revolutionizing predictive models for divertor plasma detachment control

The inherent complexity of boundary plasma, characterized by multi-scale and multi-physics challenges, has historically restricted high-fidelity simulations to scientific research due to their intensive computational demands. Consequently, routine applications such as discharge control and scenario development have relied on faster but less accurate empirical methods. This work introduces DivControlNN, a novel machine-learning-based surrogate model designed to address these limitations by enabling quasi-real-time predictions (i.e., ~ 0.2 ms) of boundary and divertor plasma behavior. Trained on over 70,000 2D UEDGE simulations from KSTAR tokamak equilibria, DivControlNN employs latent space mapping to efficiently represent complex divertor plasma states, achieving a computational speed-up of over 10 8 compared to traditional simulations while maintaining a relative error below 20% for key plasma property predictions. During the 2024 KSTAR experimental campaign, a prototype detachment control system powered by DivControlNN successfully demonstrated detachment control on its first attempt, even for a new tungsten divertor configuration and without any fine-tuning. These results highlight the transformative potential of DivControlNN in overcoming diagnostic challenges in future fusion reactors by providing fast, robust, and reliable predictions for advanced integrated control systems.

Artificial neural networks↗

Influence of up-down asymmetry in plasma shape on RMP response

Shaping effect on the plasma response to the externally applied resonant magnetic perturbation field is investigated for both DIII-D and MAST experiments, utilizing toroidal modeling. The plasma boundary shape is systematically varied ranging from single-null (SN) to double-null (DN) configurations, while other equilibrium quantities are kept largely unchanged. The relative amplitude of the computed plasma surface displacement, between the top/bottom of the torus and the outboard mid-plane, is identified as the most reliable indicator that distinguishes the plasma response between the SN and DN configurations. Here, the underlying physics is the weakening of the edge-peeling component in the plasma response with increasing up-down symmetry of the plasma boundary shape.

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Validation of MARS-F modeling of plasma response to RMPs using internal measurements on DIII-D

The linear resistive plasma response model is validated against the plasma internal measurement data from DIII-D edge-localized mode (ELM) control experiments with applied resonant magnetic perturbation (RMP). Considered are DIII-D discharges where the n = 1, 2, and 3 (n is the toroidal mode number) RMP field was applied. Experimental data for the plasma boundary displacement, as well as the three-dimensional (3D) pressure perturbation in the edge pedestal region, are deduced from the vertical Thomson scattering (TS) system and the horizontal charge exchange recombination (CER) system on DIII-D. The linear response model produces results that are in reasonable quantitative agreement with the DIII-D internal measurements. The plasma boundary displacement of up to 15 mm is modeled, with the pedestal pressure perturbation reaching 3 kPa. As an important insight, the larger plasma displacement measured by the vertical TS system, as compared to that measured by the horizontal CER system, is due to the contribution from the tangential component of the plasma displacement to the former. This mixing of displacement components is also found to influence the sensitivity of the CER measurement comparisons. The results of this study provide further confidence in the linear resistive plasma response model for analyzing ELM control experiments.

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Effects of plasma squareness on RMP response in MAST-U

The effect of the squareness of the plasma boundary shape on the plasma response to the applied n = 2 (n is the toroidal mode number) resonant magnetic perturbation, and consequently on controlling the edge-localized mode (ELM) in MAST-U in the double-null configuration, is numerically systematically investigated. The modeling is performed utilizing three different plasma response models: the single-fluid model, the two-fluid model and the magnetohydrodynamic-kinetic hybrid model. The effect of the plasma squareness on ELM control is found to depend on the equilbrium kinetic profiles. Fixing the equilibrium radial profiles to that from a recent MAST-U discharge, the experimental plasma shape is found to be close to optimal for ELM control in terms of squareness. The optimal coil phasing does not significantly vary with varying plasma squareness. These findings robustly hold with (i) two figures of merit (FoMs) defined for predicting the ELM control feasibility, and (ii) three plasma response models employed for evaluating these FoMs.

MAST-U↗

Heuristic predictions of RMP configurations for ELM suppression in ITER burning plasmas and their impact on divertor performance

Abstract A subspace of resonant magnetic perturbation (RMP) configurations for edge localized mode (ELM) suppression is predicted for H-mode burning plasmas at 15 MA current and 5.3 T magnetic field in ITER. Perturbations to the core plasma can be reduced by a factor of 2 for equivalent edge stability proxies, while the perturbed plasma boundary geometry remains mostly resilient. The striated domain of perturbed field lines connecting from the main plasma (normalized poloidal flux < 1 ) to the divertor targets is found to be significantly larger than the expected heat load width in the absence of RMPs. This facilitates heat load spreading with peak values at an acceptable level below 10 MW m − 2 on the outer target already at moderate gas fueling and low Ne seeding for additional radiative dissipation of the 100 MW of power into the scrape-off layer (SOL). On the inner target, however, re-attachment is predicted away from the equilibrium strike point due to increased upstream heat flux, higher downstream temperature and less efficient impurity radiation.

3D plasma boundary modeling↗

Interplay between beam-driven chirping modes and plasma confinement transitions in spherical tokamak ST40

Experiments on the high field spherical tokamak ST40 have led to the recent observation of interplay between beam-driven modes of sweeping frequency (chirping modes) and transitions to the enhanced global confinement regime (H-mode) and back to the low confinement regime (L-mode). The H-modes of plasma confinement are identified from decreased intensity of D α signal and from clear distinctions in the edge gradients of the visible plasma boundary (observed as a sharp plasma edge in camera images). The beam-driven chirping modes, identified as ideal magnetohydrodynamics beta-induced Alfvén acoustic eigenmodes modes, are observed in Mirnov coil signals, interferometry, and soft x-ray diagnostics. A moderate amplitude ‘primer’ chirping mode usually precedes an H–L transition. This is followed by a ‘dominant’ chirping mode with higher amplitude during the L-mode. The L–H transition back to the improved confinement occurs on a longer time scale of tens of ms, consistent with the slowing down time scale of fast beam ions. A dramatic decrease in toroidal plasma rotation is systematically observed associated with chirping modes sweeping down to zero frequency. Resonance maps built for the beam-driven chirping modes with the ASCOT (accelerated simulation of charged particle orbits in torodoial devices) code show that the resonant beam ions have orbits near the trapped-passing boundary. The ASCOT modelling assesses how losses of the resonant fast ions caused by the chirping modes with high enough amplitude modify the torque, potentially affecting the plasma rotation.

magnetic confinement fusion↗

Coupled model for liquid lithium plasma facing components

Numerical analysis provides the design choice and operating window of liquid metal Plasma Facing Components (PFC) concepts. Coupled analysis of boundary plasma together with the surrounding boundary structures is required. Here, to achieve this goal, PPPL is developing a comprehensive multi-physics model for modeling of PFCs in fusion devices. The model includes the fluid-kinetic code SOLPS-ITER and the flow and heat transfer code CFX from ANSYS. SOLPS-ITER was augmented with a liquid metal boundary condition algorithm, allowing direct two-way coupling of the plasma analysis with the two-dimensional analytical slab flow model which includes heat convection in the liquid metal PFC. The target heat flux resulting from this coupled analysis is used as a boundary condition for detailed 3D Computational Fluid Dynamics (CFD) Magneto Hydro Dynamics (MHD) and heat transfer analysis. A new formulation of MHD equations is introduced in the numerical procedure ensuring current conservation of the discretized equations. Results of the 3D analysis are used for final validation of the coupled model. A PFC design where a porous wall is used to stabilize the liquid metal surface, while MHD drive is used to push the liquid metal flow inside the PFC, will be investigated in the regimes where vapor shielding is created for enhanced volumetric plasma heat dissipation.

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Investigation of Drift Effects in UEDGE Simulations of NSTX-U Edge Plasma With Lithium Divertors

Lithium is a low-Z material, and lithium-based plasma-facing components (PFCs) are planned for the National Spherical Torus Experiment Upgrade (NSTX-U) to explore potential benefits for divertor power exhaust and core plasma management. NSTX-U is a medium-sized spherical tokamak with up to 12 MW of auxiliary heating, capable of generating reactor-relevant plasma conditions. This work presents boundary plasma simulations for NSTX-U with lithium PFCs using the UEDGE code, incorporating full magnetic and 𝐄 ×𝐁 drift physics. The simulations show that drifts strongly influence heat and particle transport: they enhance convective transport, broaden the scrape-off layer heat-flux width 𝜆 𝑞 , and reduce the anomalous heat diffusivity 𝜒 required to reproduce predicted SOL heat-flux width. 𝐄 ×𝐁 drifts provide poloidal transport, while ∇𝐵 (which includes both gradB and curvature) drifts provide radial heat and particle transport. Lithium transport is also affected by drifts, with lithium ions migrating from the outer divertor to the inner divertor through the private flux region (PFR) following the 𝐄 ×𝐁 drifts flow, lowering upstream impurity lithium densities. UEDGE is self-consistently coupled with the Wall-Li model to study plasma lithium PFC interactions depending on the local lithium sourcing based on local plasma conditions and lithium surface temperature. In these simulations, lithium evaporation shows a vapor-shielding effect that reduces divertor heat flux and increases radiative losses once surface temperatures exceed 450°C. This research work provides a first step toward self-consistent modeling of lithium PFCs in NSTX-U, demonstrating the impact of drift-driven plasma transport in SOL and divertor regions.

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Realization of a gas puff imaging system on the Wendelstein 7-X stellarator

A system for studying the spatiotemporal dynamics of fluctuations in the boundary of the W7-X plasma using the “Gas-Puff Imaging” (GPI) technique has been designed, constructed, installed, and operated. This GPI system addresses a number of challenges specific to long-pulse superconducting devices, such as W7-X, including the long distance between the plasma and the vacuum vessel wall, the long distance between the plasma and diagnostic ports, the range of last closed flux surface (LCFS) locations for different magnetic configurations in W7-X, and management of heat loads on the system’s plasma-facing components. The system features a pair of “converging–diverging” nozzles for partially collimating the gas puffed locally ≈135 mm radially outboard of the plasma boundary, a pop-up turning mirror for viewing the gas puff emission from the side (which also acts as a shutter for the re-entrant vacuum window), and a high-throughput optical system that collects visible emission resulting from the interaction between the puffed gas and the plasma and directs it along a water-cooled re-entrant tube directly onto the 8 × 16 pixel detector array of the fast camera. The DEGAS 2 neutral code was used to simulate the Hα (656 nm) and HeI (587 nm) line emission expected from well-characterized gas-puffs of H2 and He and excited within typical edge plasma profiles in W7-X, thereby predicting line brightnesses used to reduce the risks associated with system sensitivity and placement of the field of view. Operation of GPI on W7-X shows excellent signal-to-noise ratios (>100 at 2 Mframes/s) over the field of view for minimally perturbing gas puffs. The GPI system provides detailed measurements of the two-dimensional (radial and poloidal) dynamics of plasma fluctuations in the W7-X edge and scrape-off layer and in and around the magnetic islands outside the LCFS that make up the island divertor configuration employed on W7-X.

Instruments & Instrumentation↗

Modeling transient edge plasma transport with dynamic recycling

The work presents numerical simulation studies of the role that dynamic plasma recycling on the main wall and divertor target surfaces plays in transient edge plasma transport phenomena, such as edge localized modes (ELMs). The studies are performed by coupling the edge plasma transport code UEDGE [Rognlien et al., J. Nucl. Mater. 196–198, 347 (1992)] and the wall reaction–diffusion transport code FACE [Smirnov et al., Fusion Sci. Technol. 71, 75 (2017)]. The two-dimensional, time-dependent, two-way coupling of the codes, in a realistic tokamak geometry, is accomplished using the Integrated Plasma Simulator framework [Elwasif et al., in 18th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2010), Pisa, Italy (IEEE, 2010), pp. 419–427] for all modeled material plasma boundaries. The simulations show that dynamic plasma recycling has substantially different characteristics on the main wall and on the divertor plates. It is demonstrated that during an ELM cycle the outer wall can dynamically absorb and release a number of particles comparable to that expelled by the ELM from the core plasma, by far exceeding the dynamic retention capacity of the divertor surfaces. The resulting evolution of the edge and divertor plasma conditions during an ELM cycle is analyzed.

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Model predictive control of KSTAR equilibrium parameters enabled by TRANSP

Due to the complex behavior of tokamak plasmas and the importance of optimizing performance while avoiding instabilities and machine limits, plasma control algorithms are becoming increasingly dependent on sophisticated model-based control approaches. It is anticipated that the use of integrated modeling codes in the model-based control design process will reduce the amount of experimental time needed to implement new control algorithms by facilitating development of control-oriented models and enabling higher-fidelity closed-loop simulations. In this work, a reduced model is developed from a series of TRANSP simulations and is used to develop a model predictive control (MPC) algorithm for controlling important equilibrium parameters in KSTAR [1] discharges. The control algorithm uses the KSTAR neutral beam injection system and the target plasma current and plasma boundary as actuators, and optimizes the plasma stored energy, loop voltage, and internal inductance while avoiding constraints that could lead to disruptions. Higher fidelity testing of the control algorithm is performed using a flexible framework for enabling external processes to actively control plasma parameters in TRANSP simulations. Furthermore, closed-loop simulations demonstrate the ability of the control algorithm to respond to disturbances in density and confinement, handle actuator failures, and move the discharge to high non-inductive fraction conditions.

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