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184 records · Page 11

Divertor detachment characterization in negative triangularity discharges in DIII-D via 2D edge-plasma transport modeling

Edge fluid modeling of the first divertor-plasma detachment experiments in negative triangularity (NT) discharges in the DIII-D tokamak is presented using the 2D multifluid edge transport code UEDGE, including cross-field particle drifts. Experiments were performed where the lower single-null magnetic equilibrium had a strong NT (δ≈−0.5), that is, where the magnetic X-point is at a larger major radius than the core magnetic axis. Divertor-plasma detachment was induced by increasing the core plasma density in DIII-D via intrinsic gas puffing. Here density scans are performed with UEDGE to reach a detached plasma and to quantitatively recover the experimental rollover of the ion saturation current on the outer divertor target plate. The simulations cover experiments with both signs of the toroidal magnetic field, B T , where the ion magnetic Grad-B drifts are directed into (forward B T ) and out of (reverse B T ) the divertor region. Consistent with experiments with neutral beam power injection, the NT simulations reproduce: 40% higher density is needed to reach detachment onset with forward B T compared with reverse B T , and the absence of deep detachment is found with reverse B T . Similarly, comparison between Ohmic discharges in NT and positive triangularity (PT) shaping confirms that a substantially higher density is needed to achieve detachment in NT than in PT, with NT requiring an line-average density of at least the Greenwald density or higher. Simulation results suggest that higher densities are needed to reach detachment in negative compared to PT because these discharges have a shorter midplane-to-target distance along the total magnetic field B, a shorter outer divertor poloidal leg length (0.06 m vs 0.2 m), and reduced radial transport [near-scrape-off layer (SOL) D ⊥ /χ ⊥ =0.3/0.5 vs D ⊥ /χ ⊥ =1.0/1.0, all in (m 2 /s)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle balance of deuterium during deuterium shattered pellet injection shutdown in DIII-D

A particle balance analysis was conducted during a deuterium (D 2 ) shattered pellet injection-induced plasma shutdown on the DIII-D tokamak to determine why less than 20% of the pellet material is assimilated into the core plasma by the mid-current quench (CQ). Initially, most of the D 2 is injected as frozen shards and ionized upon entering the vessel. During the thermal quench, ionized particles move to the divertors and subsequently to the center post (CP) walls, where they rapidly recycle and partially accumulate as neutrals without assimilating into the core plasma. In contrast, the particle flux to the outer midplane walls is negligible, despite being accompanied by hot plasma with electron temperatures exceeding 100 eV. During mid-CQ, volume recombination effects, although not large enough to impact overall particle balance, were significant enough to require accounting for accurate interpretation of fast-framing camera D-alpha signals and the estimation of the CP wall particle flux. In addition, toroidal asymmetries, observed in measurements of toroidal electron density perturbations and the phase of magnetohydrodynamic modes, are present throughout the shutdown and can account for a discrepancy in the assimilation rate for up to 50% of the observed D 2 particle inventory. These sources and sinks of particles and fluxes were identified using absolutely calibrated D-alpha brightness and Langmuir probes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sparsified time-dependent Fourier neural operators for fusion simulations

This paper presents a sparsified Fourier neural operator for coupled time-dependent partial differential equations (ST-FNO) as an efficient machine learning surrogate for fluid and particle-based fusion codes such as NIMROD (Non-Ideal Magnetohydrodynamics with Rotation - Open Discussion) and GTC (Gyrokinetic Toroidal Code). ST-FNO leverages the structures in the governing equations and utilizes neural operators to represent Green's function-like numerical operators in the corresponding numerical solvers. Once trained, ST-FNO can rapidly and accurately predict dynamics in fusion devices compared with first-principle numerical algorithms. In general, ST-FNO represents an efficient and accurate machine learning surrogate for numerical simulators for multi-variable nonlinear time-dependent partial differential equations, with the proposed architectures and loss functions. The efficacy of ST-FNO has been demonstrated using quiescent H-mode simulation data from NIMROD and kink-mode simulation data from GTC. The ST-FNO H-mode results show orders of magnitude reduction in memory and central processing unit usage in comparison with the numerical solvers in NIMROD when computing fields over a selected poloidal plane. The ST-FNO kink-mode results achieve a factor of 2 reduction in the number of parameters compared to baseline FNO models without accuracy loss.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulations of the churning mode: Toroidally symmetric plasma convection and turbulence around the X-points in a snowflake divertor

Using a reduced MHD model, extended to include field-aligned thermal conduction, we present numerical simulations of the churning mode (CM): a toroidally symmetric, non-linear plasma vortex in the vicinity of the null points in a snowflake (SF) divertor [D. D. Ryutov et al., Phys. Scr. 89, 088002 (2014)]. Simulations are carried out across a range of inter-null separations, d xx ⁠, and inter-null orientations, θ⁠, primarily in conditions relevant to the MAST-U tokamak. We find that, when d xx is small, the CM induces additional transport across the X-points when β pm ≳8%, where β pm is the ratio of the plasma pressure in the null region to poloidal magnetic pressure at the midplane. This transport also increases approximately linearly as d xx is reduced. A diffusive model of this transport is shown to predict the total transport across the null points, where diffusion coefficients of up to ∼ 10 2 m 2 s −1 centered on a small region around the X-points are used. However, the CM also results in significant changes to the flux surfaces in the null region, which is not captured by this diffusive model. The changes in magnetic geometry mean the fractional exhaust power delivered to each divertor leg is highly sensitive to β pm ⁠, d xx ⁠, and θ⁠. For small values of θ⁠, the CM can induce a change in topology, redirecting exhaust power from a secondary divertor leg on the high field side to one on the low field side. Similar behavior is found in the fraction of exhaust power going to the inner and outer divertor. Such changes in the flux surfaces may not be captured by Grad–Shafranov solvers and so may be a source of error in the magnetic reconstruction of SF experiments. We consistently find that the fractional exhaust power going to a secondary divertor leg on the high field side is small, consistent with SF experiments.

Computer simulation↗