Impact of <i>E</i> × <i>B</i> flow shear stabilization on particle confinement and density peaking at JET

Buangam, W; García, J.; Onjun, T.; Contributors, Jet

doi:10.1088/2058-6272/ab7b0e

Cited by 4 publications

(5 citation statements)

References 33 publications

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“…The fraction ⟨| ⃗ ∇ρ t |⟩/⟨| ⃗ ∇ρ t | 2 ⟩ varies between 0.83 and 0.92 for JET and 0.69 and 0.87 for DIII-D and the fraction ⟨| ⃗ ∇ρ t |⟩ 2 /⟨| ⃗ ∇ρ t | 2 ⟩ varies between 0.93 and 0.97 for JET and 0.85 and 0.95 for DIII-D. These values are true between ρ t = 0.5 and 0.8 The first term on the RHS is the peaking that comes from the turbulent transport, the same term as displayed in equation (17). This term is entirely determined by the ratio of the particle balance pinch and diffusion.…”

Section: Particle Balance Diffusion and Pinchmentioning

confidence: 82%

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Comparing particle transport in JET and DIII-D plasmas: gyrokinetic and gyrofluid modelling

et al. 2020

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Transport modelling, for two dimensionless collisionality scaling experiments at the Joint European Torus (JET) and DIII-D with three discharges each, is presented. Experimental data from JET (Tala et al 2019 Nucl. Fusion 59 126030) and DIII-D (Mordijck et al 2020 Nucl. Fusion 60 066019) show a dissimilar dependence in the density peaking from the source and turbulent transport. The discharges from the JET collisionality scan show that the source is dominant for the density peaking, which is contrary to DIII-D where the transport is the main cause for the peaking. In this article, the different dependency on the source is studied by investigating the zero flux density gradient (peaking factor) at radial position ρ t = 0.6 and by calculating the averaged perturbed diffusion and pinch between ρ t = 0.5 and ρ t = 0.8. Results show that the difference of the normalized temperature gradients have the largest and considerable impact on the peaking factor. The calculated diffusion and pinch showed good match with the experimental measured perturbed values. The calculated ratio of the particle balance pinch and diffusion explained the difference in peaking from turbulent transport, a high ratio for DIII-D yielding high peaking and a low ratio for JET yielding low peaking. However the particle balance diffusion, which suppresses the peaking from the source, was high for DIII-D and low for JET. Thusly, explaining the particle source much larger impact on the peaking at JET.

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Section: Particle Balance Diffusion and Pinchmentioning

confidence: 82%

“…It adds rotation to the plasma which changes the E × B shear which affects the turbulent transport [14,15]. It has been shown that this increase in E × B shear adds to the inward pinch [16,17]. The NBI also creates a locally higher current which changes the magnetic field.…”

Section: Introductionmentioning

confidence: 99%

Comparing particle transport in JET and DIII-D plasmas: gyrokinetic and gyrofluid modelling

et al. 2020

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“…[14] The 𝐸 × 𝐵 flows play a central role in regulating the saturation level of the turbulence and turbulent transport. [15] The 𝐸 × 𝐵 velocity shear caused the reduction in turbulence and transport. [16] On the other hand, the flow shear may also make a destabilizing contribution as well.…”

Section: Introductionmentioning

confidence: 99%

Role of the zonal flow in multi-scale multi-mode turbulence with small-scale shear flow in tokamak plasmas

Li¹,

Li²,

Wang³

et al. 2022

Chinese Phys. B

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The structural characteristics of zonal flows and their roles in the nonlinear interaction of multi-scale multi-mode turbulence are investigated numerically via a self-consistent Landau-fluid model. The multi-mode turbulence here is composed of a shorter wavelength electromagnetic (EM) ion temperature gradient (ITG) mode and a Kelvin-Helmholtz (KH) instability with long wavelengths excited by externally imposed small-scale shear flows. For strong shear flow, a prominent periodic intermittency of fluctuation intensity except for dominant ITG component is revealed in turbulence evolution, which onset time depends on the ion temperature gradient and the shear flow amplitudes corresponding to different KH instabilities. It is identified that the intermittency phenomenon results from the zonal flow dynamics, which is mainly generated by the KH mode and back-reacts on it. It is demonstrated that the odd symmetric components of zonal flow (same symmetry as the external flow) make the radial parity of the KH mode alteration through adjusting the drift velocities at two sides of the resonant surface so that the KH mode becomes bursty first. Afterwards, the ITG intermittency follows due to nonlinear mode coupling. Parametric dependences of the features of the intermittency are elaborated. Finally, associated turbulent heat transport is evaluated.

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“…The related codes have been widely developed to study the properties of ITG and TEM [3] turbulence. In addition, transport behavior in the experiments is analyzed [4]. Direct numerical simulations have successfully provided tremendous insight into the underlying transport physics, and they are currently a powerful tool in transport study.…”

Section: Introductionmentioning

confidence: 99%

Machine learning of turbulent transport in fusion plasmas with neural network

Li¹,

Fu²,

Li³

et al. 2021

Plasma Sci. Technol.

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Turbulent transport resulting from drift waves, typically, the ion temperature gradient (ITG) mode and trapped electron mode (TEM), is of great significance in magnetic confinement fusion. It is also well known that turbulence simulation is a challenging issue in both the complex physical model and huge CPU cost as well as long computation time. In this work, a credible turbulence transport prediction model, extended fluid code (ExFC-NN), based on a neural network (NN) approach is established using simulation data by performing an ExFC, in which multi-scale multi-mode fluctuations, such as ITG and TEM turbulence are involved. Results show that the characteristics of turbulent transport can be successfully predicted including the type of dominant turbulence and the radial averaged fluxes under any set of local gradient parameters. Furthermore, a global NN model can well reproduce the radial profiles of turbulence perturbation intensities and fluxes much faster than existing codes. A large number of comparative predictions show that the newly constructed NN model can realize rapid experimental analysis and provide reference data for experimental parameter design in the future.

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Impact of E × B flow shear stabilization on particle confinement and density peaking at JET

Cited by 4 publications

References 33 publications

Comparing particle transport in JET and DIII-D plasmas: gyrokinetic and gyrofluid modelling

Comparing particle transport in JET and DIII-D plasmas: gyrokinetic and gyrofluid modelling

Role of the zonal flow in multi-scale multi-mode turbulence with small-scale shear flow in tokamak plasmas

Machine learning of turbulent transport in fusion plasmas with neural network

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