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At least 19 records

Tokamak Disruption Simulation (Final Technical Report)

The Tokamak Disruption Simulation collaboration was a SciDAC (Scientific Discovery through Advanced Computing) program led by Xianzhu Tang of the Los Alamos National Laboratory but with separate grants to each institution. I was the PI for Columbia University and the only person at Columbia directly funded by this SciDAC. Disruptions are a sudden loss of confinement in tokamaks, and a reliable method of preventing disruptions must be developed before tokamak fusion power plants become feasible. A related plasma confinement concept, the stellarator, is the only way known way of preventing disruptions with the required reliability. The largest devices, both existing and under construction, for confining plasmas for fusion using magnetic fields are tokamaks, so it is important to solve their disruption issues. The sudden loss of confinement in tokamaks can be from a bit of material falling into the plasma, which causes the plasma energy to be quickly lost by radiation, or by an instability causing a breakup of the confining surfaces formed by the magnetic field. This breakup can occur more than a million times faster than one would naively think possible. The sudden breakup of surfaces is called a fast magnetic reconnection and also results in a sudden cooling of the plasma.

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Tokamak disruption simulation

UT contribution in this Tokamak Disruption Simulation (TDS) is to develop a parallel high‐order hybridized Discontinuous Galerkin (HDG) methods for large‐s cale MHD simulations. The following are the major goals: 1) Construction of HDG methods for linearized MHD, 2) Rigorous analysis for the HDG formulations for linearized MHD, 3) 2D and 3D simulations to verify the convergent of the HDG methods for linearized MHD, 4) multigrid solvers/preconditioners for HDG formulations, 5) HDG for reconnection problems, 6) Divergence cleaning with HDG, 7) HDG formulations for nonlinear MHD, 8) Picard fixed point HDG approach, 9) IMEX HDG‐DG for nonlinear HDG; 10) parallel large‐scale HDG for linear and nonlinear MHD simulations.

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DOE Final Report on Virginia Tech’s contribution to “Tokamak Disruption Simulation”

This work was performed by Virginia Tech in collaboration with multiple institutions led by Los Alamos National Laboratory as a part of the Tokamak Disruption Simulation SciDAC (Scientific Discovery through Advanced Computing) project supported jointly by the Department of Energy Office of Science and Ad- vanced Scientific Computing Research. This report summarizes Virginia Tech’s contributions to the Sci- DAC project. Virginia Tech researchers (presently University of Washington researchers) focused on the fundamental role of plasma-material interaction on transport, which could then have macroscopic effects on simulations of tokamak disruptions. The plasma sheath, which regulates plasma particle and energy fluxes to the wall, is an essential component in the study of plasma-material interaction (PMI). Understanding sheath theory by accounting for finite sheath thickness and transport in the vicinity of the sheath entrance can sig- nificantly modify typical assumptions that are made in the Bohm speed analysis, where the Bohm speed provides the lower bound of the plasma exit flow speed. Our work provides a modified Bohm speed formu- lation that accounts for the critical role of transport and for applications that are away from the asymptotic limits that are typically assumed.

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The impact of collisionality on the runaway electron avalanche during a tokamak disruption

The exponential growth (avalanching) of runaway electrons (REs) during a tokamak disruption continues to be a large uncertainty in RE modeling. The present work investigates the impact of tokamak geometry on the efficiency of the avalanche mechanism across a broad range of disruption scenarios. It is found that the parameter ν *,crit ⁠, describing the collisionality at the critical energy to run away, delineates how toroidal geometry impacts RE formation. In particular, utilizing a reduced but self-consistent description of plasma power balance, it is shown that for a high-density deuterium-dominated plasma, ν *,crit is robustly less than one, resulting in a substantial decrease in the efficiency of the RE avalanche compared to predictions from slab geometry. In contrast, for plasmas containing a substantial quantity of neon or argon, ν *,crit ≳1, no reduction of the avalanche is observed due to toroidal geometry. This sharp contrast in the impact of low- vs high-Z material results primarily from the relatively strong radiative cooling from high-Z impurities, enabling the plasma to be radiatively pinned at low temperatures and thus large electric fields, even for modest quantities of high-Z material.

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Self-Consistent Simulation of the Excitation of Compressional Alfvén Eigenmodes and Runaway Electron Diffusion in Tokamak Disruptions

Alfvénic modes in the current quench (CQ) stage of the tokamak disruption have been observed in experiments. In DIII-D the excitation of these modes is associated with the presence of high-energy runaway electrons (REs), and a strong mode excitation is often associated with the failure of RE plateau formation. In this work we present results of self-consistent kinetic-MHD simulations of RE-driven compressional Alfvén eigenmodes (CAEs) in DIII-D disruption scenarios, providing an explanation of the CQ modes. Simulation results reveal that high energy trapped REs can have resonance with the Alfvén mode through their toroidal precession motion, and the resonance frequency is proportional to the energy of REs. The mode frequencies and their relationship with the RE energy are consistent with experimental observations. Further, the perturbed magnetic fields from the modes can lead to spatial diffusion of REs including the nonresonant passing ones, thus providing the theoretical basis for a potential approach for RE mitigation.

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Tokamak Disruption Simulation (Final Technical Report)

This was a multi-institutional project concerned with simulation of tokamak disruption – rapid termination of the plasma and confining magnetic field in a tokamak fusion reactor – with the aim of quantifying the physics associated with disruption mitigation. The PI’s role is as one of a group of computational scientists concerned with development of effective solution algorithms for the underlying models of magnetohydrodynamics and transport that represent the physical processes, and to develop techniques of uncertainty quantification for treating unknown aspects of the model such as boundary conditions and effects of impurities in plasmas.

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Corrigendum: Simulations of stand-off runaway electron beam termination by tungsten particulates for tokamak disruption mitigation (2024 Nucl. Fusion 64 056019)

In the original article, we inadvertently omitted a reference which previously introduced the concept of tungsten injection for 'Disruption Mitigation in Tokamak Reactor via Reducing the Seed Electrons of Avalanche.' In that reference, the authors have proposed injection of a tungsten cylinder of 80 mm by 8 mm dimensions, by rail guns, to absorb the runaway seed population. This can be contrasted with another interesting idea of using small tungsten pellets coated with a low Z material for depleting the runaway seeds as an option for upgrade of the ITER Disruption Mitigation System. Interested readers are referred to those two papers on the tungsten injection for runaway seed removal/reduction, and the related issue of not shortening the current quench excessively. The application focus of was not on reducing the runaway seeds in the initial Ohmic-to-runaway current conversion phase, but on safe termination of a fully formed and likely decaying runaway beam that is about to scrape off against the first wall, which can be accelerated by vertical displacement events. This scheme thus serves as a last line of defense against potential wall damage. The choice here is locally released tungsten particulates, similar to the previous idea of using tungsten particulates as a dust shield for the divertor. The most significant finding of is that strong pitch angle scattering, in addition to energy attenuation and absorption, of high-energy runaways by tungsten particulates, provides a transport mechanism by which runaways damage of the first wall can be mitigated by reducing and spreading the runaway wall load. We regret the omission in the original article, and thank the authors of the cited article for bringing this matter to our attention. We also find the possibility of using the injected tungsten rod from to terminate the runaways, as opposed to the cloud of tungsten particulates in intriguing. In that context, it is of interest to mention another possibility of a retractable tungsten metal arm that can be swung out for deployment in runaway termination, which would remove the need for post-mitigation recovery of tungsten debris in injection schemes.

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Deep convolutional neural networks for multi-scale time-series classification and application to tokamak disruption prediction using raw, high temporal resolution diagnostic data

In this paper we discuss recent advances in deep convolutional neural networks (CNN) for sequence learning, which allow identifying long-range, multi-scale phenomena in long sequences, such as those found in fusion plasmas. We point out several benefits of these deep CNN architectures, such as not requiring experts such as physicists to hand-craft input data features, the ability to capture longer range dependencies compared to the more common sequence neural networks (recurrent neural networks like long short-term memory (LSTM) networks), and the comparative computational efficiency. We apply this neural network architecture to the popular problem of disruption prediction in fusion energy tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. Initial results trained on a large ECEi dataset show promise, achieving an F 1 -score of ~91% on individual time-slices using only the ECEi data. This indicates the ECEi diagnostic by itself can be sensitive to a number of pre-disruption markers useful for predicting disruptions on timescales not only for mitigation but also avoidance. Future opportunities for utilizing these deep CNN architectures with fusion data are outlined, including impact of recent upgrades to the ECEi diagnostic.

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Electric field effects during disruptions

Tokamak disruptions are associated with breaking magnetic surfaces, which makes magnetic field lines chaotic in large regions of the plasma. The enforcement of quasi-neutrality in a region of chaotic field lines requires an electric potential that has both short and long correlation distances across the magnetic field lines. The short correlation distances produce a Bohm-like diffusion coefficient ∼Te/eB and the long correlation distances aT produce a large scale flow ∼Te/eBaT. This cross-field diffusion and flow are important for sweeping impurities into the core of a disrupting tokamak. The analysis separates the electric field in a plasma into the sum of a divergence-free, E→B, and a curl-free, E→q, part, a Helmholtz decomposition. The divergence-free part of E→ determines the evolution of the magnetic field. The curl-free part enforces quasi-neutrality, E→q=−∇→Φq. Magnetic helicity evolution gives the required boundary condition for a unique Helmholtz decomposition and an unfortunate constraint on steady-state tokamak maintenance.

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DECAF Cross-device characterization of tokamak disruptions indicated by abnormalities in plasma vertical position and current

Abnormal (deviating from target) variations in the plasma vertical position Z and current I p (such as vertical displacements, transient I p 'spikes' and quenches) constitute common elements of a disruption, a phenomenon that is to be mitigated, or ultimately avoided in future reactor-relevant tokamaks. While those abnormalities are generally recognized cross-shot and cross-device, details in terms of appearance (or not) and order of those abnormalities in disruption event chains is bound with the plasma state at the time of the chain initiation. Detection of those abnormalities is thus indicative not only of the onset of the plasma collapse itself, but also of the disruption driving cause that is promoted at the particular plasma state. Here, occurrence of disruptions, explored via detection of a Ip quench, and analysis of disruption event chains constituted by Ip and Z abnormalities, is reported for in total 7 full years of operation of 3 devices (KSTAR, MAST-U and NSTX-U) using the DECAFTM code expanded tools and capabilities. It is shown that the disruption occurrence depends not only on details of the plasma state, but also on (device-dependent) technical elements of the shot exit scenario. A year-to-year change in main disruption causes and a reduction of the disruptivity rate, bound with device and operation upgrades, are reported. Particular trigger instances of disruption event chains (and the full chains, when applicable) are shown to occupy different parts of the operation space diagrams, in accordance with prior expectation. Plasma elongation is identified as an important factor influencing details of the chains and its role will be further explored.

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Experimental evidence of runaway electron tail generation via localized helical structure in pellet-triggered tokamak disruptions

A novel detector, using stacked BGO crystals, is developed for runaway electron (REs) studies in the DIII-D tokamak. It is able to resolve fast dynamics of high-energy tail formation of REs with an ultra-high time resolution of ~1 μs. As a cost, the detector estimates the `effective' energy of a given shape of γ-ray spectra and sacrifices the energy resolution. In aid of the new measurement capability, a rapid, inhomogeneous growth of RE tail is observed in detail during a major disruption triggered by an argon pellet. It is found that both the population and energy of a well-confined RE tail significantly oscillate at the early period of the growth. The oscillation phase is locked to a slow rotating magnetohydrodynamic instability, which is briefly destabilized for only ~1 ms at the early period of the current quench. The oscillation ceases promptly, when the mode disappears. As a result, the data suggests that the high-energy RE tail is well-confined and accelerated via a localized helical structure in the plasma core.

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A laser inverse Compton scattering diagnostic to study runaway electron dynamics during tokamak disruptions

Both technical and simulation progress has been made toward implementing a laser inverse Compton scattering diagnostic on the DIII-D tokamak. This is a novel diagnostic which uses a short (sub-ns) pulse laser together with a fast (sub-ns) gated x-ray detector to measure relativistic electrons inside a tokamak plasma. The study of these relativistic electrons is important to make sure they can be removed from any tokamak-based power reactor, as they could damage vessel walls and cooling lines. This diagnostic is completely new for magnetic fusion research and has never been implemented before on a tokamak. It is found that good signals and radial profiles could be obtained with an optimized high-energy (7 Joule) laser. Using a standard off-the-shelf Nd:YAG (0.7 Joule) laser would give some signals above the noise but no ability to measure the relativistic electron radial profile.

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A laser inverse Compton scattering diagnostic to study runaway electron dynamics during tokamak disruptions

The goal is to design a new diagnostic based on laser inverse Compton scattering (LICS) to study the dynamics of runaway electron formation and their subsequent loss during triggered disruptions in DIII-D. It is known that better measurements of the runaway electron population, throughout the evolution of a disruption, is critical for mitigating the impact of energetic electron beams especially in high plasma current discharges such as those in reactor relevant burning plasmas. The goal of the LICS approach being designed for DIII-D is to measure the timeresolved spatial profile and energy distribution of the runaway electrons while they are in the core of the tokamak plasma. During the last year, a code was developed to simulate the signals from a new laser scattering diagnostic for DIII-D, which will measure the relativistic electron population expected in DIII-D after disruptions triggered by argon pellet injection.

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Simulations of stand-off runaway electron beam termination by tungsten particulates for tokamak disruption mitigation

Abstract Stand-off runaway electron termination by injected tungsten particulates offers a plausible option in the toolbox of disruption mitigation. Tungsten is an attractive material choice for this application due to large electron stopping power and high melting point. To assess the feasibility of this scheme, we simulate runaway collisions with tungsten particulates using the MCNP program for incident runaway energies ranging from 1 to 10 MeV. We assess runaway termination from energetics and collisional kinematics perspectives. Energetically, the simulations show that 99% of runaway beam energy is removed by tungsten particulates on a timescale of 4–9 µ s. Kinematically, the simulations show that 99% of runaways are terminated by absorption or backscattering on a timescale of 3–4 µ s. By either metric, the runaway beam is effectively terminated before the onset of particulate melting. Furthermore, the simulations show that secondary radiation emission by tungsten particulates does not significantly impact the runaway termination efficacy of this scheme. Secondary radiation is emitted at lower particle energies than the incident runaways and with a broad angular distribution such that the majority of secondary electrons emitted will not experience efficient runaway re-acceleration. Overall, the stand-off runaway termination scheme is a promising concept as a last line of defense against runaway damage in ITER, SPARC, and other future burning-plasma tokamaks.

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Disruption event characterization and forecasting in tokamaks

Disruption prediction and avoidance is a critical need for next-step tokamaks, such as ITER. Disruption Event Characterization and Forecasting (DECAF) research fully automates analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or complete avoidance of the disruption. Disruption event chains related to local rotating or global magnetohydrodynamic (MHD) modes and vertical instability are examined with warnings issued for many off-normal physics events, including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 to 1 × 10 6 tested sample times per device. An initial multi-device database comparison illustrates a highly important result that plasma disruptivity does not need to increase as βN increases. Global MHD instabilities, such as resistive wall modes (RWMs), can give the briefest time period of warning before disruption compared to other physics events. In an NSTX database with unstable RWMs, the mode onset, loss of boundary and current control, and disruption event warnings are found in all cases and vertical displacement events are found in 91% of cases. An initial time-dependent reduced physics model of kinetic RWM stabilization created to forecast the disruption chain predicts instability 84% of the time for experimentally unstable cases with a relatively low false positive rate. Instances of the disruption event chain analysis illustrate dynamics including H–L back transitions for rotating MHD and global RWM triggering events. Furthermore, disruption warnings are issued with sufficient time before the disruption (on transport timescales) to potentially allow active profile control for disruption avoidance, active mode control, or mitigation.

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Resistive wall tearing mode disruptions in DIII-D and ITER tokamaks

Disruptions are a serious problem in tokamaks, in which thermal and magnetic energy confinement is lost. This paper uses data from the DIII-D experiment, theory, and simulations to demonstrate that resistive wall tearing modes (RWTMs) produce the thermal quench (TQ) in a typical locked mode shot. Analysis of the linear RWTM dispersion relation shows the parameter dependence of the growth rate, particularly on the resistive wall time. Linear simulations of the locked mode equilibrium show that it is unstable with a resistive wall and stable with an ideally conducting wall. Nonlinear simulations demonstrate that the RWTM grows to sufficient amplitude to cause a complete thermal quench. The RWTM growth time is proportional to the thermal quench time. Here, the nonlinearly saturated RWTM magnetic perturbation amplitude agrees with experimental measurements. The onset condition is that the q = 2 rational surface is sufficiently close to the resistive wall. Collectively, this identifies the RWTM as the cause of the TQ. In ITER, RWTMs will produce long TQ times compared to present-day experiments. ITER disruptions may be significantly more benign than previously predicted.

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