Simulation prediction of micro-instability transition and associated particle transport in tokamak plasmas

Li, Hui; Li, Jiquan; Fu, Yanlin; Wang, Jialei; Jiang, Min

doi:10.1088/1741-4326/ac486b

Cited by 13 publications

(15 citation statements)

References 66 publications

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“…2021 b ; Li et al. 2022; Rodriguez-Fernandez et al. 2022 b ) have found that the total particle flux can be a sensitive function of the mix of ITG and TEM turbulence present, and gyrokinetic simulations have shown that nonlinear couplings between these modes are possible (Merz & Jenko 2010).…”

Section: Core Transportmentioning

confidence: 99%

Development of compact tokamak fusion reactor use cases to inform future transport studies

Holland,

Bass,

Orlov

et al. 2023

J. Plasma Phys.

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The OMFIT STEP (Meneghini et al., Nucl. Fusion, vol. 10, 2020, p. 1088) workflow has been used to develop inductive and steady-state H-mode core plasma scenario use cases for a $B_0 = 8 \, {\rm T}$ , $R_0 = 4 \, {\rm m}$ machine to help guide and inform future higher-fidelity studies of core transport and confinement in compact tokamak reactors. Both use cases are designed to produce 200 MW or more of net electric power in an up-down symmetric plasma with minor radius $a = 1.4 \, {\rm m}$ , elongation $\kappa = 2.0$ , triangularity $\delta = 0.5$ and effective charge $Z_{{\rm eff}} \simeq 2$ . Additional considerations based on the need for compatibility of the core with reactor-relevant power exhaust solutions and external actuators were used to guide and constrain the use case development. An extensive characterization of core transport in both scenarios is presented, the most important feature of which is the extreme sensitivity of the results to the quantitative stiffness level of the transport model used as well as the predicted critical gradients. This sensitivity is shown to arise from different levels of transport stiffness exhibited by the models, combined with the gyroBohm-normalized fluxes of the predictions being an order of magnitude larger than other H-mode plasmas. Additionally, it is shown that although heating in both plasmas is predominantly to the electrons and collisionality is low, the plasmas remain sufficiently well coupled for the ions to carry a significant fraction of the thermal transport. As neoclassical transport is negligible in these conditions, this situation inherently requires long-wavelength ion gyroradius-scale turbulence to be the dominant transport mechanism in both plasmas. These results are combined with other basic considerations to propose a simple heuristic model of transport in reactor-relevant plasmas, along with simple metrics to quantify coupling and core transport properties across burning and non-burning plasmas.

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Section: Core Transportmentioning

confidence: 99%

Development of compact tokamak fusion reactor use cases to inform future transport studies

Holland,

Bass,

Orlov

et al. 2023

J. Plasma Phys.

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“…Jonas et al successfully apply AI to automatically control a variety of plasma boundary shapes on the TCV device [17] . In numerical simulations, Zhao et al accomplished quick prediction of beta limits in HL-2M device via AI, with an accuracy rate being as high as 95% [18] . Li et al build a surrogate model through AI to predict the transition of micro-instability in fusion devices [19] .…”

Section: The Rise Of Artificial Intelligent (Ai) Trendsmentioning

confidence: 99%

Intelligent control for predicting and mitigating major disruptions in magnetic confinement fusion

Liu

Tang

et al. 2022

iEnergy

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Magnetic confinement fusion is believed to be one of the promising paths that provides us with an infinite supply of an environmentfriendly energy source, naturally contributing to a green economy and low-carbon development. Nevertheless, the major disruption of high temperature plasmas, a big threat to fusion devices, is still in the way of mankind accessing to fusion energy. Although a bunch of individual techniques have been proved to be feasible for the control, mitigation, and prediction of disruptions, complicated experimental environments make it hard to decide on specific control strategies. The traditional control approach, designing a series of independent controllers in a nested structure, cannot meet the needs of real-time complicated plasma control, which requires extended engineering expertise and complicated evaluation of system states referring to multiple plasma parameters. Fortunately, artificial intelligence (AI) offers potential solutions towards entirely resolving this troublesome issue. To simplify the control system, a radically novel idea for designing controllers via AI is brought forward in this work. Envisioned intelligent controllers should be developed to replace the traditional nested structure. The successful development of intelligent control is expected to effectively predict and mitigate major disruptions, which would definitely enhance fusion performance, and thus offers inspiring odds to improve the accessibility of sustainable fusion energy.

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“…Further details of the equations and the simulation code were shown in our recent work. [35,36] The ITG and TEM instabilities are involved in this multi-mode model, including plasma density 𝑛e, electron temperature 𝑇e, vorticity 𝛺, parallel ion velocity 𝜐 ‖ and ion temperature 𝑇i:…”

mentioning

confidence: 99%

Global Effects on Drift Wave Microturbulence in Tokamak Plasmas

Li 李,

Wang 王

2023

Chinese Phys. Lett.

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In this paper, microturbulence excited by ion temperature gradient (ITG)-dominant and trapped electron mode (TEM)-dominant instabilities is investigated employing an extended fluid code (ExFC) based on the so-called Landau-Fluid model, which includes the trapped electron dynamics. Firstly, the global effect is emphasized through direct comparison of ITG and TEM instability domains based on local and global simulations. The global effect makes differences in both linear instability and nonlinear transport, including the fluxes and the structure of zonal flow (ZF). The transitions between ITG, TEM and ITG & TEM instabilities/turbulence depend not only on the three key drive forces (R/Ln ,R/LTe ,R/LTi ) but also on their global (profile) effects. Secondly, a lot of electrostatic linear gyrofluid simulations are concluded to obtain a distribution of the instability.

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Simulation prediction of micro-instability transition and associated particle transport in tokamak plasmas

Cited by 13 publications

References 66 publications

Development of compact tokamak fusion reactor use cases to inform future transport studies

Development of compact tokamak fusion reactor use cases to inform future transport studies

Intelligent control for predicting and mitigating major disruptions in magnetic confinement fusion

Global Effects on Drift Wave Microturbulence in Tokamak Plasmas

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