Bulletin of the American Physical Society
60th Annual Meeting of the APS Division of Plasma Physics
Volume 63, Number 11
Monday–Friday, November 5–9, 2018; Portland, Oregon
Session GI3: Disruptions, Stellarators |
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Chair: Jeremy Lore, Oak Ridge National Lab Room: OCC Oregon Ballroom 204 |
Tuesday, November 6, 2018 9:30AM - 10:00AM |
GI3.00001: Direct Measurements of Internal Structures of Born-locked Modes and the Key Role in Triggering Tokamak Disruption Invited Speaker: Xiaodi Du The internal structure of a born-locked mode in an Ohmic-heated, low-density plasma is directly measured for the first time. A novel dual soft X-ray imaging system has recently been developed in the DIII-D tokamak to measure the radiation symmetry breaking by the presence of static, three-dimensional helical structures. Small locked island chains with helicities of m=3/n=1 and m=4/n=1 are observed simultaneously with the m=2/n=1 island (m, n: poloidal and toroidal number) and the locked phase of each island chain is uniquely determined. It is found that the 3/1 and 4/1 island, initially well separated from the major 2/1 island, govern the cooling process in a long quasi-stationary phase, but later trigger thermal quench, when starting to overlap. A simulation of intrinsic error field penetration at multiple rational surfaces and its impact on electron thermal transport by a non-linear single fluid MHD code (TM1) is qualitatively consistent with the observations. The result shows the essential role of co-existing multiple locked islands in the deterioration of global thermal confinement preceding thermal quench.It should be emphasized that this study is important for the understanding of potential major disruption in the current ramp-up phase of ITER discharge, since the amplitude of fully penetrated resonant n=1 error field locked modes was demonstrated to be independent of resonant intrinsic error field correction in DIII-D tokamak [1]. [1] R.J. La Haye, C. Paz-Soldan and E.J. Strait, Nucl. Fusion 55 023011 (2015). |
Tuesday, November 6, 2018 10:00AM - 10:30AM |
GI3.00002: Disruption Event Characterization and Forecasting in Tokamaks Invited Speaker: Steven Anthony Sabbagh High reliability disruption prediction and avoidance are critical needs for next-step tokamaks such as ITER. The Disruption Event Characterization and Forecasting (DECAF) code was written to automate analysis of tokamak data determining chains of events leading to disruptions and to forecast their evolution. This approach provides a flexible framework to evaluate the proximity of plasma states to disruption events by coupled physics analyses, model criteria, and machine learning techniques. An expansive list of events including MHD modes, density limits, off-normal plasma motion, and mismatch of plasma current feedback target are evaluated. The expanding tokamak database includes KSTAR, NSTX/-U, MAST, DIII-D, and TCV. Automated analysis of rotating MHD modes allows identification of coupling, bifurcation, locking, and potential triggering by other MHD activity. Resistive stability including Delta’ calculation by the Resistive DCON code is evaluated on long pulse KSTAR plasmas using kinetic equilibrium reconstructions with magnetic field pitch angle data to determine capability for instability forecasting. Greenwald density fraction and local island power balance theory are evaluated for disruption forecasting. As density increases towards or surpasses empirical / theoretical limits, the onset of MHD activity and subsequent disruption are observed. Insights are also gained connecting mode activity to density limit models by their coupling through plasma rotation. In an NSTX database exhibiting global MHD, resistive wall mode (RWM) and loss of boundary control events are always found and VDE events are found in over 90% of plasmas. A reduced kinetic RWM stability physics model computes the evolving proximity of discharges to marginal stability. Stringent marginal stability evaluation with a non-optimized model shows high success (greater than 85%) as a disruption predictor. |
Tuesday, November 6, 2018 10:30AM - 11:00AM |
GI3.00003: Path to Stable Tokamak Operation: Plasma stability analysis using physics-based and data-based approaches for real-time control Invited Speaker: Egemen Kolemen Fusion reactors will need stability calculations during operations to steer the plasma from disruptions. Both plasma-physics-based and experimental-data-driven real-time stability analysis techniques are presented that were applied to control DIII-D. A δW stability analysis method with a Hamilton-Jacobi theory was formulated that converts the stability calculation to a Riccati differential equation. This brings numerical methods that are well suited to robust, fast solution of ideal mode stability in ~200 ms, as implemented on DIII-D. Resistive stability was studied using the STRIDE code that expands upon the ideal case. Resistive MHD ∆′matrices for DIII-D discharges were calculated in ~300 ms. The stability error bar is obtained using an Unscented Transform method, which is thousands of times faster than a Monte-Carlo approach. Tearing instability analysis enabled by this method shows that the stability error bar increases by an order of magnitude before a mode onset in most cases. This shows the plasma equilibrium becomes “touchy” before tearing, i.e. minor variations in profiles can lead to instability. Data-based Machine Learning Algorithms (MLA) are necessary because not all instabilities can be quantified with first-principle approaches. The best MLA predicted DIII-D disruptions correctly >90% of the time with <1% false positives. To show the feasibility of predicting 15 MA ITER disruptions with data only from low current disruptions (required by safety), MLA trained with low I_{p }DIII-D data were applied to high I_{p }with appropriate scaling laws. Encouraging results predict disruptions correctly >90% of the time with <5% false positives. Based on this method, a plasma control algorithm was implemented on DIII-D that regulates neutral beams to keep the plasma stable; if this fails and the predicted disruptivity becomes too high, the system ramps down the plasma. |
Tuesday, November 6, 2018 11:00AM - 11:30AM |
GI3.00004: Shattered Pellet Injection Simulations With NIMROD Invited Speaker: Charlson ChiSun Kim Using the newly developed Particle-in-Cell (PiC) based Shattered Pellet Injection (SPI) model in the NIMROD code, nonlinear 3D extended MHD initial value SPI driven thermal quench simulations show that MHD activity triggered by injection of impurity fragments strongly impacts the thermal quench dynamics and alters the mixing and radiation efficiency and toroidal peaking factor. Given the critical nature of the Disruption Mitigation System (DMS) in the operation of ITER, accurate simulations are essential to developing Disruption Mitigation Strategies for ITER. SPI is the primary candidate for ITER's DMS. Building upon prior work on Massive Gas Injection (MGI) simulations by V. A. Izzo (Nuclear Fusion 55, 073032 (2015)), we have developed a PiC based model to mimic the fragment plume of the injected shattered pellet. An analytic expression has been developed to model the ablation of the frozen impurity mixture assuming each fragment is a isolated uniform sphere. This discrete PiC based SPI plume model captures the essential features of the plume front shielding the fragments that follow and offers the flexibility to conveniently vary trajectory, size, and distribution of the fragments that make up the shattered plume. D3D and ITER SPI simulations indicate that the thermal quench proceeds in two phases. Initially, the outer plasma is shed via interchange-like filaments while preserving the core temperature. This results in a steep gradient and triggers the second phase of the thermal quench, an external kink-like event that collapses the core. Based on these simulations we will comment on advanced mitigation scenarios such as multiple SPI injectors and the prospects for the ITER DMS. |
Tuesday, November 6, 2018 11:30AM - 12:00PM |
GI3.00005: Computing local sensitivities and tolerances of stellarators using shape gradients Invited Speaker: Matt Landreman Tight tolerances have been a leading driver of cost in recent stellarator experiments, so improved definition and control of tolerances can have significant impact on progress in the field. Here we relate tolerances to the shape gradient representation that has been useful for shape optimization in industry, used for example to determine which regions of a car or aerofoil most affect drag, and we demonstrate how the shape gradient can be computed for physics properties of toroidal plasmas. The shape gradient gives the local differential contribution to some scalar figure of merit by normal displacement of the shape. In contrast to derivatives with respect to quantities parameterizing a shape (e.g. Fourier amplitudes), which have been used previously for optimizing plasma and coil shapes, the shape gradient gives spatially local information and so is more easily related to engineering constraints. The shape gradient for any figure of merit can be computed using the parameter derivatives that are already routinely computed for stellarator optimization. Examples of shape gradients for plasma and electromagnetic coil shapes are given. We also derive and present examples of an analogous representation of the local sensitivity to magnetic field errors; this magnetic sensitivity can be rapidly computed from the shape gradient. The shape gradient and magnetic sensitivity can both be converted into local tolerances, which inform how accurately the coils should be built and positioned, where trim coils and structural supports for coils should be placed, and where magnetic material and current leads can best be located. Both sensitivity measures provide insight into shape optimization, enable systematic calculation of tolerances, and connect physics optimization to engineering criteria that are more easily specified in real space than in Fourier space. |
Tuesday, November 6, 2018 12:00PM - 12:30PM |
GI3.00006: Using Turbulent Saturation Physics to Optimize Stellarator Confinement Invited Speaker: Chris Hegna The goal of this work is to find mechanisms to improve stellarator confinement by optimally using 3D shaping to affect turbulent saturation levels. An analytic theory for saturation of ion temperature gradient driven turbulence is developed for general 3D equilibrium [1]. The theory relies on the premise that coupling of linear instabilities to damped eigenmodes at comparable wave number is the dominant saturation process. The dominant nonlinear energy transfer from unstable to damped modes is enabled by a three-wave interaction, where the third mode depends upon the properties of the 3D shaping. The theory identifies an important metric, the produce of a turbulent correlation lifetime and a geometric coupling coefficient, which quantifies nonlinear energy transfer. Large values of this metric correspond to small values of ITG-induced turbulent transport. As an application of the theory, the nonlinear transfer metrics are quantified for two classes of quasi-symmetric stellarator configurations. While nonlinear transfer physics in quasi-axisymmetry is largely determined by three-wave interactions involving zonal flows, in quasi-helically symmetry (QHS) there are additional nonlinear energy transfer channels involving nearly marginally stable eigenmodes. The reason for this difference is primarily geometric. QHS has relatively short connection lengths which enables vigorous non-zonal energy transfer. This suggests that QHS has an inherent advantage with regard to turbulent saturation physics. The nonlinear energy transfer metric is being incorporated into the stellarator optimization schemes to produce configurations with reduced turbulent transport. Quantification of the turbulent transport improvement for the optimized configurations is provided by nonlinear gyrokinetic simulations using GENE. [1] C. C. Hegna et al, Phys. Plasm 25, 022511 (2018). |
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