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Simulations of saturated MHD activity in the HBT-EP tokamak

The NIMROD code is used to perform simulations of MHD activity in the HBT-EP tokamak, including the effect of a resistive wall. Linear simulations are conducted to scan current and pressure profiles to establish self-consistent baseline equilibria that result in MHD instabilities with low error between experimental diagnostics and synthetic equivalents. A family of such equilibria is found with relatively peaked current and pressure profiles. Nonlinear simulations are performed using the optimal equilibrium, which is linearly unstable to a Resistive Wall Mode—stable in the ideal wall limit and with an Alfvénic growth rate in the no-wall limit. Using resistive wall boundary conditions, nonlinear Hall MHD simulations yield a rotating, saturated n=1 mode similar to the type observed experimentally in HBT-EP discharges. An n=1 mode around the q=2 surface mediates a localized axisymmetric perturbation that flattens the plasma current from a linearly unstable state to a 3D, rotating, stable state. During the saturated period, periodic changes in inter-diagnostic phase lag allow for qualitative estimations of effective, macroscopic transport coefficients used in MHD closure models and could be extended to model post-disruption MHD structure rotation after thermal quenches seen in HBT-EP.

Arnold, David A. (ORCID:0009000059535761)↗

Sawtooth suppression by flux pumping on HBT-EP

Abstract This study examines the mechanisms underlying sawtooth suppression in the High Beta Tokamak-Extended Pulse (HBT-EP) device. It is observed that strong-intensity sawtooth activities correlate with reduced-amplitude magnetohydrodynamics (MHD) edge modes which are identified as m / n = 3 / 1 external kink modes, while sawtooth suppression correlates with larger and saturated edge mode amplitudes. To further investigate these correlations, the plasma–wall coupling was manipulated by adjusting the positions of the conducting walls in HBT-EP. It was found that strong sawtooth events occur when the normalized wall radius b / a is within a critical value. This implies that the plasma–wall distance must be sufficiently small to ensure effective stabilization of the edge mode. Even slight differences in major radius result in significantly different discharge styles, categorized as ‘sawtoothing discharges’ and ‘sawtooth-suppressed discharges’ respectively. Through a series of mode structure analyses, we confirm the coexistence and coupling of the m / n = 1 / 1 helical core, m / n = 2 / 1 tearing mode, and m / n = 3 / 1 external kink mode during sawtooth-suppression, and that this coupling induces anomalous current broadening. Based on these findings, we conclude that sawtooth suppression in the HBT-EP tokamak is consistent with the process of magnetic flux pumping.

Physics↗

Suppression of ITG turbulence due to spectral shift during biasing induced H-mode on HBT-EP

Investigations of biasing induced H-mode discharges on HBT-EP show that the edge turbulence is consistent with the ion temperature gradient) mode and have allowed for the controlled observation of the effect of applied flow shear on the turbulence. Measurements of the radial wavenumber spectrum of floating potentials at the edge show that the turbulence intensity decreases with increasing shift in the spectrum average ⟨ k r ⟩ when increasing amounts of bias probe voltage (and increasing amounts of flow shear) is applied. This is in agreement with the spectral shift model [Staebler et al., Phys. Rev. Lett. 110, 055003 2013] for turbulence suppression via sheared flow. A shift in the wavenumber spectrum occurs at applied electrode voltages and currents below the threshold needed for an L–H transition, and a dithering transition is obtained when biasing near the threshold. Suppression of blob-filament turbulence in the scrape-off layer (SOL) precedes the L–H transition, with the SOL turbulence remaining low throughout the dithering phase, despite the modulation of turbulence levels in the nearby edge. This demonstrates that the SOL turbulence “decouples” from the edge turbulence. The spectral shift in the measured radial wavenumber is corroborated by the direct measurement of eddy tilt angle using a novel time delay analysis technique first developed for Doppler reflectometry [Pinzon et al., Plasma Phys. Controlled Fusion 61, 105009 (2019)] but adapted here for floating potential measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Disruption halo current rotation scaling on Alcator C-Mod and HBT-EP

Asymmetric halo currents (HCs) can exert large net forces on the vacuum vessel and other components during disruptions on tokamaks. The displacements caused by these forces can then be amplified if these asymmetric forces rotate at frequencies resonant with the vessel. This paper reports on the investigation of a recently proposed scaling law for the disruption HC rotation frequency [Saperstein et al., “Halo current rotation scaling in post-disruption plasmas,” Nucl. Fusion 62, 026044 (2022)] that combines measurements on Alcator C-Mod with those on HBT-EP. We find that a new non-circular version of the scaling law [ ⟨ f rot ⟩ m / ⟨ m ⟩ ∝ 1 B T ( S / π )] takes into consideration the dependence of frot on the poloidal structure of the MHD instability (m) driving the asymmetry and describes the disruption-averaged rotation frequency on C-Mod. Disruption rotation is also found to be insensitive to the vertical position and impurity content of the plasma at the onset of the disruption. However, a stagnation in the time evolution of frot is occasionally observed. In conclusion, observations are consistent with the dominance of poloidal rotation during the disruption, which is motivated by the poloidal drift nature of the scaling law.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of Simulation Models for Wall-Connected Scrape off Layer Currents during MHD Activity in the HBT-EP Tokamak (Final Report)

This is the final report for the DOE award DE-SC0021325, titled “Validation of Simulation Models for Wall-Connected Scrape off Layer Currents during MHD Activity in the HBT-EP Tokamak” for the period September 1, 2020 – May 31, 2023. This award is part of a broader collaborative project, which supported training of a PhD student at Columbia University under the joint supervision of Dr. Hansen and Columbia project members. The award supported research into computational models for plasma and 3D conducting structures in the vicinity relevant to tokamak disruptions and other mode activity (eg. RWMs) using the NIMROD, and PSI-Tet, codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of Simulation Models for Wall-Connected Scrape off Layer Currents during MHD Activity in the HBT-EP Tokamak

This is the final report for the DOE award DE-SC0021657, titled “Validation of Simulation Models for Wall-Connected Scrape off Layer Currents during MHD Activity in the HBT-EP Tokamak” for the period September 1, 2020 – April 30, 2025. This award is part of a broader collaborative project, which supported training of a PhD student at Columbia University under the joint supervision of Dr. Levesque and Dr. Hansen (on award DE-SC0021325). The award supported research into computational models for plasma and 3D conducting structures in the vicinity relevant to tokamak disruptions and other mode activity (eg. RWMs) using the NIMROD and PSI-Tet codes. Additional detail on progress in support of these tasks is provided below.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A dimensionality reduction algorithm for mapping tokamak operational regimes using a variational autoencoder (VAE) neural network

Abstract A variational autoencoder (VAE) is a type of unsupervised neural network which is able to learn meaningful data representations in a reduced dimensional space. We present an application of VAE in identifying the operational stability boundary of tokamak plasma discharges. This model was implemented using a dataset of over 3000 discharges from the high beta tokamak-extended pulse (HBT-EP) device. We found the VAE model to be capable of forming a continuous low-dimensional operational space map and identifying the operational boundaries using a specified warning time window. By projecting the operational parameters onto the same reduced space, this provides an intuitive way for the machine operator or an automated control system to perform disruption avoidance using a relevant control actuator as a discharge approaches a boundary. Pre-programmed GPU control experiments were conducted to demonstrate this control technique using HBT-EP’s saddle control coils as a horizontal position actuator, showing the ability to avoid the oncoming disruptive event and extend the duration of the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Suppression of MHD modes with active phase-control of probe-injected currents

Abstract Active phase-control of probe-injected current is shown to both suppress and amplify long-wavelength rotating magnetohydrodynamic instabilities in the HBT-EP tokamak. Four probes are connected in quadrature and energized to drive non-axisymmetric currents through the edge of the tokamak, creating magnetic perturbations comparable to previously-studied saturated kink modes or resonant magnetic perturbations that are generated by an external control coil array. Measurements of the magnetic perturbations from the probe-injected currents determine a set of current-carrying helical filaments used to model active feedback control of resistive wall modes. These experiments suggest current-injection feedback may be an effective alternative to external control coils for control of RWMs and other long-wavelength kink-like modes at the edge of tokamaks.

Physics↗

An optical-input Maximum Likelihood Estimation feedback system demonstrated on tokamak horizontal equilibrium control

A readily parallelized Maximum Likelihood Estimation (MLE) algorithm with linear computational complexity is demonstrated in real time using only measurements from an extreme ultraviolet (EUV) diagnostic to control the horizontal position of a tokamak plasma. A set of trial emissivity profiles are parameterized by the control quantity of interest (R m ), and the MLE is identified from the profile which minimizes the signal reconstruction residual. The algorithm depends on an empirically determined likelihood function with exponential form. EUV emission (λ ≈ 15eV-1keV) is captured in a poloidal plane by four 16-channel AXUV diodes mounted at different poloidal angles with radial and angular resolution sufficient to discern plasma equilibrium evolution in HBT-EP. Calculations of the plasma major radius by the system are consistent within diagnostic uncertainty for the majority of the discharge with those of: a weighted average of vertical soft X-ray or EUV chords, magnetic sensors, and an equilibrium reconstruction. The feedback system corrects for a horizontal displacement of the major radius equal to 20% of the plasma minor radius by adjusting the vertical field produced from 40 in-vessel control coils in real time. The MLE calculation is performed on a GPU in a 15 μs cycle, with similar performance in this application to a simple weighted average of vertical chords. Finally, results demonstrate horizontal position control using magnetic actuators and an optical observer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MHD mode tracking using high-speed cameras and deep learning

Abstract We present a new algorithm to track the amplitude and phase of rotating magnetohydrodynamic (MHD) modes in tokamak plasmas using high speed imaging cameras and deep learning. This algorithm uses a convolutional neural network (CNN) to predict the amplitudes of the n = 1 sine and cosine mode components using solely optical measurements from one or more cameras. The model was trained and tested on an experimental dataset consisting of camera frame images and magnetic-based mode measurements from the High Beta Tokamak - Extended Pulse (HBT-EP) device, and it outperformed other, more conventional, algorithms using identical image inputs. The effect of different input data streams on the accuracy of the model’s predictions is also explored, including using a temporal frame stack or images from two cameras viewing different toroidal regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Halo current rotation scaling in post-disruption plasmas

Abstract Halo current (HC) rotation during disruptions can be potentially dangerous if resonant with the structures surrounding a tokamak plasma. We propose a drift-frequency-based scaling law for the rotation frequency of the asymmetric component of the HC as a function of toroidal field strength and plasma minor radius ( f rot ∝ 1/ B T a 2 ). This scaling law is consistent with results reported for many tokamaks and is motivated by the faster HC rotation observed in the HBT-EP tokamak. Projection of the rotation frequency to ITER and SPARC parameters suggest the asymmetric HC rotation will be on the order of 10 Hz and 60 Hz, respectively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Developing ML/AI Methods for High-Throughput Characterization of Multiple-Sensor Streams of Tokamak Dynamics for High-Speed Control (Final Report)

This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗