Bulletin of the American Physical Society
62nd Annual Meeting of the APS Division of Plasma Physics
Volume 65, Number 11
Monday–Friday, November 9–13, 2020; Remote; Time Zone: Central Standard Time, USA
Session NP16: Poster Session: Magnetic Confinement: Other Tokamaks (9:30am - 12:30pm)On Demand
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NP16.00001: HBT-EP Program: MHD Dynamics and Active Control through 3D Fields and Currents G.A. Navratil, J. Bialek, J.W. Brooks, R.N. Chandra, J.P. Levesque, Boting Li, M.E. Mauel, A. Saperstein, I.G. Stewart, Y. Wei, C.J. Hansen The HBT-EP active mode control research program aims to: (i) understand the physics of scrape-off layer currents (SOLC) and interactions between the helical plasma edge and conducting boundary structures, (ii) test new methods for measurement and mode control that integrate optical and magnetic detector arrays with both magnetic and SOLC feedback, and (iii) understand fundamental MHD issues associated with disruptions, resonant magnetic perturbations, and SOLC. A two-color multi-energy EUV/SXR tangential array has been installed for the study of internal MHD mode structure and tearing mode dynamics, together with poloidal arrays of SOLC sensors. A biased electrode in the plasma edge was used to induce a strong layer of sheared ExB flow to achieve the first H-mode plasmas on HBT-EP, and the first characterization of edge turbulence dominated by the ion temperature gradient mode extending previous findings of EAST and TCABR. Previous GPU control system results demonstrating active control of MHD using non-magnetic EUV plasma emission have been extended with the first demonstration of active control of plasma rotation and rotating n$=$1 magnetic instability amplitude suppressed by 50{\%} using a toroidal electrode array. Further improvement of the GPU active control system is being pursued using tomographic reconstruction of the poloidal EUV emissivity profile. [Preview Abstract] |
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NP16.00002: Suppression of Edge and Blob-Filament Turbulence on HBT-EP I.G. Stewart, J.W. Brooks, J.P. Levesque, M.E. Mauel, G.A. Navratil Recent work has shown that the ion temperature gradient mode (ITG) dominates the edge turbulence on HBT-EP, while blob-filament turbulence is present in the scrape-off layer (SOL). Measurements of the radial wavenumber spectrum of floating potentials at the edge show that the ITG turbulence intensity decreases with increasing shift in the spectrum average $\langle k_{r} \rangle$ when increasing amounts of bias probe voltage (and increasing amounts of flow shear) is applied. These measurements extend previous findings on EAST and TCABR, which support the spectral shift model proposed by Staebler et al.\footnote{Staebler G. M. et al. 2013 \textit{Phys. Rev. Lett.} \textbf{110} 055003} for turbulence suppression via sheared flow. In addition, abrupt suppression of blob-filament turbulence in the SOL occurs at lower electrode voltages and currents than that required for the L-H transition. The SOL turbulence also remains low throughout dithering transitions, despite the modulation of turbulence levels in the nearby edge. In this way, the SOL turbulence ``decouples" from the edge turbulence. [Preview Abstract] |
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NP16.00003: Tearing mode structure study using tangential EUV/SXR diagnostic system on HBT-EP tokamak Boting Li, J.P. Levesque, G.A. Navratil, M.E. Mauel, I.G. Stewart, A. Saperstein, R.N. Chandra, C. Hansen Measuring and analyzing the intensity of the extreme ultraviolet (EUV) and soft x-ray (SXR) is an effective way to study the internal characteristics of MHD mode structures, including the temperature profiles. We present the progress on the two-color multi-energy EUV/SXR diagnostic system in the HBT-EP tokamak. A filter wheel with five groups of dual-filter structure is adopted to implement multiple combinations of filters, accomplish easier calibration and protect the filters during discharge cleaning. By using a combination of 100 nm Aluminum and 200 nm Titanium filters with identical plasma views and two 16-channel diode arrays, this system allows reconstruction of temperature profile versus time by the ratio of the amplitudes of the signals from different filters, calibrated with Thomson scattering system. The initial results on the dynamics of the m/n=2/1 tearing mode are studied using the new system. The line-integrated signals are used to reconstruct the emission and temperature profiles of the tangential cross section of the plasma. The synthetic diagnostics and experimental results are compared to assess the system’s ability to identify the island structure. [Preview Abstract] |
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NP16.00004: Progress Toward Real-Time Control of Plasma Dynamics and Equilibrium via Tomographic Inversion of EUV Emissivity Profiles on the HBT-EP Tokamak Rian Chandra, Boting Li, John Brooks, Jeffrey Levesque, Yumou Wei, Ian Stewart, Alex Saperstein, Christopher Hansen, Gerald Navratil, Michael Mauel In pursuit of fully nonmagnetic plasma control, this poster presents continuing progress on the Extreme-Ultraviolet (EUV) emission feedback system installed on the HBT-EP tokamak. The system consists of four fan arrays installed in a poloidal plane, capturing 15-10$^4$eV photons through a 100nm aluminum filter. Emissivity topologies are recovered via tomographic inversion from the photocurrents in a 22$\mu$s cycle on a NVIDIA 580 GTX GPU. These 2D inverted profiles are the target of feedback, building on prior work [1] in which basis structures extracted from the raw EUV data were tracked, and feedback applied based on their assumed underlying m/n structure. Forty inductive coils providing $\pm$60 Gau{\ss} each provide actuation at ten toroidal and four poloidal locations. Real time EUV sensor data is projected in parallel onto multiple basis modes, and the optimal mode is selected by minimizing reconstruction error. In this way, the magnetic structure for mode canceling feedback is chosen adaptively. The same technique is demonstrated in control of the plasma equilibrium major radius. Error reduction schemes and of the techniques of refinement of the basis functions used are further shown.\\ $[1]$ Levesque J.P $et\,al\:2019,\,APS$-$DPP$ [Preview Abstract] |
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NP16.00005: Overview of mode control methods on the HBT-EP tokamak J.P. Levesque, J.W. Brooks, R.N. Chandra, Boting Li, M.E. Mauel, G.A. Navratil, A. Saperstein, I.G. Stewart, Y. Wei, C. Hansen We present an overview of recent and upcoming experiments for feedback-controlling kink and tearing modes on the High Beta Tokamak -- Extended Pulse (HBT-EP). Mode amplitude and phase for feedback are determined using either magnetic sensors or chord-integrated extreme ultraviolet (EUV) emission. Feedback algorithms are implemented using a Graphics Processing Unit (GPU)-based controller. Actuators include arrays of biasable electrodes located inside the plasma and at its edge, as well as in-vessel magnetic control coils near the plasma surface. Current injected by the probes follows a path aligned with the edge field helicity, naturally producing fields with appropriate geometry for mode control. The feedback systems are able to suppress or amplify modes, and control rotation frequency. Upcoming control experiments will include adding biasable tiles in the scrape-off layer (SOL), and utilizing SOL current sensors in the feedback loop. One mission of this work is to develop robust mode control techniques that do not require 3D magnetic coils, applicable to a reactor environment. [Preview Abstract] |
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NP16.00006: Measurements of Scrape-Off Layer Current (SOLC) Structures and Edge Magnetic Perturbations in HBT-EP A. Saperstein, J.P. Levesque, J.W. Brooks, G.A. Navratil, M.E. Mauel Recently installed poloidal arrays of scrape-off layer current (SOLC) sensors on HBT-EP have found that the currents flowing between the plasma edge and the walls have global helical structures that correlate well with kink and tearing mode fluctuations. The phase relationships between these current structures and magnetic fluctuations during the pre-disruption phase of the plasma are seen to depend on plasma equilibrium parameters and the type of MHD instability present at the time, with the currents being in phase with either the poloidal or radial field at the location of the current sensor. In some cases, these relationships have been found to vary sensor to sensor, implying that the geometry of the system is likely playing a significant role. These phase relationships are analyzed in the contexts of potential current driving mechanisms, and provide insight into how discharge parameters and instabilities can influence SOLC structures. [Preview Abstract] |
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NP16.00007: A Dimensionality Reduction Algorithm for Mapping Tokamak Operation Regimes Using Variational Autoencoder (VAE) Neural Network Y. Wei, J.W. Brooks, R. Chandra, J.P. Levesque, Boting Li, A. Saperstein, I.G. Stewart, M.E. Mauel, G.A. Navratil, C. Hansen Variational autoencoder (VAE) is a type of unsupervised neural network which is able to learn meaningful data representation in a reduced dimension. We present an application of VAE for analyzing plasma discharges. Comparing to disruption prevention algorithms using supervised learning approaches, VAE maps the input signals onto a lower dimensional latent space by their similarities with neighboring samples. This creates a smooth operation space map in which individual discharges form continuous trajectories as they evolve from stable toward unstable regions in latent space, and information of latent space topography can be useful for steering discharge away from impending disruptive event using relevant actuators in addition to issuing warning to terminate discharge. This algorithm has been implemented using a dataset consisting of over 4000 discharges from HBT-EP tokamak. Training result shows smoother latent space and better separation of stable and unstable plasma states comparing to linear PCA-based dimensionality reduction scheme. A proof-of-principle actuator control experiment using open-loop applied vertical field pulse to control plasma position has also been conducted and analyzed. This work represents the first machine learning-based study on HBT-EP tokamak. [Preview Abstract] |
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NP16.00008: High-throughput ML/AI methods to use multiple data-streams from different diagnostics to characterize dynamic tokamak discharges Michael Mauel, James Anderson, R.N. Chandra, J.P. Levesque, Boting Li, A. Saperstein, I.G. Stewart, Y. Wei, G.A. Navratil Modern magnetic fusion research involves high-resolution temporal and spatial diagnostics from multiple sensor arrays and provides opportunities to apply modern fusion-specific numerical linear algebra methods ({\it i}) to identify and optimize data reduction methods for real-time discharge control and ({\it ii}) to advance our understanding of fundamental behaviors of magnetically-confined plasma. This presentation uses measurements from recently expanded diagnostics on Columbia University's High Beta Tokamak-Extended Pulse (HBT-EP) that capture complex behaviors and records high-resolution, high-speed streams of magnetic, soft-x-ray, current, and optical data. The results of numerical analyses of these data streams from HBT-EP are examined, as well as how statistical methods such as the time-domain singular value decomposition and novel applications of methods from the field of ``randomized numerical linear algebra'' (rNLA) can be applied to fusion diagnostic data. [Preview Abstract] |
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