Bulletin of the American Physical Society
63rd Annual Meeting of the APS Division of Plasma Physics
Volume 66, Number 13
Monday–Friday, November 8–12, 2021; Pittsburgh, PA
Session TO08: MFE: Disruptions and Runaway ElectronsOn Demand
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Chair: Carl Sovinec, University of Wisconsin - Madison Room: Rooms 317-318 |
Thursday, November 11, 2021 9:30AM - 9:42AM |
TO08.00001: Real-time estimation of the safe operating region and disruption proximity in tokamaks Mark D Boyer, Cristina Rea, Mitchell D Clement A novel real-time capable algorithm for identifying the safe operating region around a tokamak operating point has been developed. The region is defined by a convex set of linear constraints, from which the proximity of a point to a disruptive boundary can be calculated. The disruptivity of points is calculated from an empirical machine learning predictor that generates the likelihood of disruption. While the likelihood generated by such empirical models can be compared to a threshold to trigger a disruption mitigation system, the safe operating region calculation enables active optimization of the operating point to maintain a safe margin from disruptive boundaries. The safe operating region identification algorithm is applied to historical data from DIII-D showing the evolution of disruptive boundaries and the potential impact of optimization of the operating point. Real-time relevant execution times are achieved by parallelizing many of the calculation steps and implementing the algorithm on a graphics processing unit (GPU). |
Thursday, November 11, 2021 9:42AM - 9:54AM |
TO08.00002: Machine learning methods for probabilistic locked-mode predictors in tokamak plasmas John M Finn, Cihan Akcay, Dylan P Brennan, Thomas Burr, Doga Kurkcuoglu A rotating tokamak plasma can resonantly interact with an an error field, leading to locking and disruptions. Here we use machine learning (ML) methods to predict locking, to explore the avoidance of locking in real time. We use a simple coupled third order ODE model of the interaction of the magnetic perturbation with the error field, to gain experience with large sample sets for training the ML algorithms. This model describes qualitatively the locking and unlocking bifurcations. The independent ODE variables are the magnitude of the reconnected magnetic flux, its phase, and the plasma rotation, all at the mode rational surface; these quantities are the order parameters, completely characterizing the state, locked or unlocked (L,U). We have two control parameters: the magnitude of the error field and the rotation frequency associated with the momentum source. We use clustering methods to classify L and U states, and note the crucial importance of using normalized order parameters. We estimate the probability of locking in the region of control parameter space with hysteresis, i.e. with both L and U states. We note the analogy with phase transitions. We have modeled nonlinear saturation and resistive wall effects, resulting in a 5th order ODE system. |
Thursday, November 11, 2021 9:54AM - 10:06AM |
TO08.00003: Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks Jinxiang Zhu, Cristina Rea, Robert S Granetz, Earl S Marmar, Kevin Montes, Ryan Sweeney, Roy A Tinguely, Dalong Chen, Biao Shen, Bingjia Xiao, David A Humphreys, Jayson L Barr, Orso-Maria O Meneghini Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device’s HP operation based on its low performance (LP) data is one key to success. In this presentation, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy and the suitable predictivity of the HP regime for the target machine can be achieved by combining LP data from the target with HP data from other machines. These results provide a possible disruption predictor development strategy for next generation tokamaks, such as ITER and SPARC, and highlight the importance of developing baseline scenario discharges of future tokamaks on current machines. |
Thursday, November 11, 2021 10:06AM - 10:18AM |
TO08.00004: Progress in Tokamak Disruption Simulation (TDS) SciDAC Project Xianzhu Tang The Tokamak Disruption Simulation (TDS) SciDAC project aims to develop |
Thursday, November 11, 2021 10:18AM - 10:30AM |
TO08.00005: Formation and propagation of cooling front in open-field-line-plasma Yanzeng Zhang, Jun Li, Xianzhu Tang When the magnetic field lines suddenly intercept solid surfaces that recycle the plasma particle and energy, a magnetized plasma can undergo a thermal collapse that is dominated by parallel transport of extreme kinetic character. This can happen, for example, in the thermal quench during a tokamak disruption when large-scale MHD activities can turn nested flux surfaces into globally stochastic field lines that connect fusion grade core plasma directly to the divertor/first wall. In fully kinetic VPIC simulations of thermal collapse in open field line plasmas intercepting a recycling wall, we find that the thermal quench comes in the form of a cooling front that propagates at ion thermal speed from the wall into the core plasma. Such a cooling front is driven by the cold plasmas from the wall that significantly reduces the perpendicular electron and ion temperature, especially in weakly collisional case. Inside the cooling front, the ion dynamics are not affected by the cold recycling particles, where a steady recession of ion parameters is found. Whereas outside the cooling front, the plasma changes abruptly in a narrow region. One direct result is that a whistler instability is driven locally by trapped electrons in the cooling front affecting the thermal quench process. |
Thursday, November 11, 2021 10:30AM - 10:42AM |
TO08.00006: BOUT++ simulation of edge plasma dynamics during during thermal quench Ben Zhu, Xueqiao Xu, Xianzhu Tang Recently upgraded BOUT++ six-field drift-reduced Landau fluid turbulence model with flux-driven capability is applied to investigate plasma turbulence and transport dynamics at the tokamak edge region, as well as the divertor power loads during the thermal quench phase of a disruption. In this study excessive particle and power are applied at the pedestal region for a short period of time (about 10-20% of the stored thermal energy within 0.1-1ms) to mimic the intensive particle and energy outflow from the core during the onset of thermal quench. 50 times larger than normal maximum divertor heat load and 4 times wider width are observed, for both DIII-D and ITER-like H-mode plasmas. These dramatic divertor heat load and width are due to enhanced turbulence activity inside the separatrix. As the particle and energy influx from core steepen plasma profiles, not only the level of turbulence fluctuation increases, but also the dominant modes (ballooning-type) shift to lower k (hence larger eddies). Meanwhile, magnetic perturbation amplifies at least one order of magnitude, particularly at the pedestal top and in the SOL. As a result, turbulence becomes a much more efficient radial transport channel to rapidly deposit particle and energy outflow from core to the divertor plates. |
Thursday, November 11, 2021 10:42AM - 10:54AM |
TO08.00007: Thermal quench in ITER locked mode disturbances Henry R Strauss Disruptions in ITER could be much milder in ITER than in JET and |
Thursday, November 11, 2021 10:54AM - 11:06AM |
TO08.00008: Dispersive Shell Pellet Modeling Validation and Extrapolation to ITER Valerie Izzo Dispersive shell pellet (DSP) injection as an alternate disruption mitigation technique to shattered pellet injection (SPI) was demonstrated in DIII-D experiments [Hollmann, Phys. Rev. Lett. 122, 65001 (2019)] wherein diamond shells filled with boron dust triggered an inside-out thermal quench (TQ). MHD modeling of DSP reproduces several experimental trends and suggests that a predictive model is feasible. Simulations explain the generation of runaway electrons only for the most centered payload, which also maximizes TQ mitigation efficiency. Modeling also replicates the experimentally observed reduction of the Ip-spike amplitude for faster pellets. The Ip-spike results from edge current-profile flattening by a 3/1 double tearing mode, whose non-local radial structure stochasticizes much of the plasma volume. Assuming faster pellets, extrapolation of the shell material quantity to ITER should benefit from the reduced surface-to-volume ratio for larger pellets. Initial ITER shell and (beryllium) payload quantity scoping indicates that the payload needed for an ITER TQ is less than what would be obtained using the DIII-D quantity scaled up by the stored thermal energy (roughly 360x). |
Thursday, November 11, 2021 11:06AM - 11:18AM |
TO08.00009: NIMROD Simulations of Multi-Injector Shattered Pellet Injection Charlson C Kim, Brendan C Lyons, Joseph Mcclenaghan, Paul B Parks, Lang L Lao Shattered Pellet Injection (SPI) is the primary candidate for disruption mitigation in ITER. Single injector SPI |
Thursday, November 11, 2021 11:18AM - 11:30AM |
TO08.00010: MHD Modeling of SPI Injection in JET and KSTAR Joseph T McClenaghan, Brendan C Lyons, Charlson C Kim, Nicholas Eidietis, Lang L Lao Nonlinear 3D MHD simulations of shattered-pellet injection (SPI) in JET have been performed using the M3D-C1 and NIMROD extended-MHD codes with a single, monolithic pellet show a prototypical SPI-driven disruption. NIMROD simulations show a radiative thermal quench (TQ) which becomes more rapid as the pellet passes the safety factor q=3 surface. The results are similar for both a single, monolithic pellet and a pencil-beam model for the SPI plume. A scan in viscosity from 200-2000 m2/s for 2D MHD simulations using NIMROD shows no significant change to the predicted radiative collapse. An initially radiation-driven TQ is accelerated by MHD activity as the pellet crosses the q=2 and q=3/2 surfaces, leading to a radiation spike, global stochasticization of the magnetic field, and a complete TQ. Eventually a current quench (CQ), preceded by a current spike is seen as the ohmic heating balances the radiative cooling. Simulations of KSTAR SPI experiments have also been performed. These simulations lay the ground work for more-sophisticated validative and predictive modeling of SPI in JET and KSTAR and development of SPI disruption mitigation scenarios in ITER using both M3D-C1 and NIMROD. |
Thursday, November 11, 2021 11:30AM - 11:42AM |
TO08.00011: 2D-2P multiscale semi-Lagrangian algorithm for fast electron transport in the relativistic Vlasov-Fokker-Planck equation Luis Chacon, Don Daniel, William T Taitano For sufficiently strong electric fields, electrons may break away from thermal equilibrium and approach relativistic speeds. Such “runaway” electrons, common in tokamak disruptions, traverse orbits at much faster time scales than collisional ones, while dynamics of interest saturate on time scales much longer than these. In this study, we propose a 2D-2P semi-Lagrangian scheme to efficiently bridge these temporal scales. The approach reformulates the Vlasov equation as an integro-differential operator using Green’s functions along electron orbits, and employs operator splitting to decouple integrals over the relativistic collisional source [1,2]. We consider 2D magnetic fields, but the formulation generalizes to arbitrary 3D magnetic fields. The proposed 2D-2P treatment is formally first-order accurate in time, but (i) preserves asymptotic properties associated with stiff Vlasov term, (ii) is uniformly accurate in Δt/ε, where Δt is the timestep and ε is the ratio of advection to collisional time scales, and (iii) is optimal (i.e., scalable with the total number of mesh points in the domain). We will demonstrate the algorithm in circular tokamak geometries [3]. |
Thursday, November 11, 2021 11:42AM - 11:54AM |
TO08.00012: Runaway to Ohmic Conversion in Tokamak Disruptions Chris McDevitt, Xianzhu Tang The termination of an existing runaway electron (RE) beam has emerged as a central thrust in disruption research. An intriguing scenario for achieving this result is by inducing a RE to Ohmic conversion, whereby REs are either decayed in energy or expelled from the plasma leaving near bulk electrons to carry the plasma current. We have investigated this scenario in two limits. The first is for the case of an axisymmetric plasma such that the RE to Ohmic conversion can only be realized by slowing down the existing REs. A hybrid fluid-kinetic model of the coupled system is employed whereby fluid equations are used to describe the bulk plasma, whereas REs are described kinetically. This framework is utilized to impose constraints on the bulk plasma that must be achieved in order to induce the RE to Ohmic conversion in an axisymmetric plasma. The second limit considered corresponds to the case where a large fraction of REs are lost via an MHD event. In this limit, a critical question is whether remnant REs are able to reform by the avalanche amplification mechanism. A sharp transition is identified in the phase space defined by the amount of injected material and the strength of the MHD event that delineates regimes where a RE to Ohmic conversion can be achieved. |
Thursday, November 11, 2021 11:54AM - 12:06PM |
TO08.00013: Tearing mode induced generation and transport of non-thermal electrons in ADITYA-U tokamak. Sharvil Patel, Joydeep Ghosh, Malay Bikas Chowdhury, K. B. K. Mayya, Tanmay Macwan, Shishir Purohit, Manoj Gupta, Suman Aich, Suman Dolui, Kaushlender Singh, Rohit Kumar, Nandini Yadava, Ranjana Manchanda, Nilam Ramaiya, Abha Kanik, Sameer Jha, Kumudini Tahiliani, Umesh Nagora, Surya Pathak, Kumarpalsinh A Jadeja, Rakesh Tanna Study of runaway electrons (RE’s) with energies in the several keV to tens of MeV is important as its interaction with PFC’s results in large heat loads, sputtering and melting of the vacuum chamber, especially for reactor-scale devices like ITER. To minimize the harmful effects of RE’s on PFC’s, a good understanding of RE generation and transport is required. In tokamak, RE’s are produced during the thermal quench, impurity pellet injection and magnetic reconnection. Amongst these, observation of energetic particle generation due to magnetic reconnection in tokamaks is scarce. In ADITYA-U, Quasi-coherent oscillations are observed in HXR emission from the limiter in synchronous with MHD mode oscillation. The MHD analysis shows, m/n = 4/1 tearing mode is excited with periodic gas puffing and later it transforms to 3/1 tearing mode. With large growth rate of 3/1 tearing mode, MHD modulation starts appearing in HXR emission, C2+ spectral line emission and electron density. This work presents a plausible explanation for the experimental observation by invoking non-thermal electron generation due to induced electric field at X-point of 3/1 magnetic island via magnetic reconnection and how this electric field influences transport of these RE’s resulting in the observed periodic burst. |
Thursday, November 11, 2021 12:06PM - 12:18PM Not Participating |
TO08.00014: A recovery-based numerical scheme for full Fokker-Planck collisions Petr Cagas, Ammar Hakim, Bhuvana Srinivasan Fokker-Planck collision model is important for accurate simulations of many problems relevant to magnetic confinement fusion, for example, |
Thursday, November 11, 2021 12:18PM - 12:30PM |
TO08.00015: Nonnegative Gaussian process on quasi-periodic noise for plasma radiation tomography during a disruption Jaewook Kim, Jayhyun Kim, Juhyeok Jang, Sehyun Kwak, Y.-c. Ghim In cases where the data collected from plasmas contain high level quasi-periodic noise and it is difficult to perform tomography reconstruction based on a least square method, we have developed a method to infer a plasma state using Bayesian probability theory and Gaussian process with non-negativity priors. Since most fusion devices utilize magnetic fields to control plasma, the plasma itself and the control coils may produce electromagnetic noises that affect the integrity of the diagnostics. In KSTAR, we use fast bolometer with Absolute Extreme Ultra-Violet (AXUV) detectors to measure radiated power during plasma disruption. In this work, we introduce a method of extracting radiation signals from the raw signals, which are contaminated by quasi-coherent noise, using Bayesian inference and Gaussian process. When a solution of the least square estimation for tomography reconstruction is difficult to obtain due to lack of line integrated signals, prior knowledge is often reflected in finding solutions using a regularization technique. Here, we use Gaussian process prior as a regularization for statistical image reconstruction of AXUV signals. The non-negativity prior is utilized for tomography reconstruction as the radiation can not have negative values. |
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