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At least 55 records · Page 3

Broadening of microwave heating beams in the DIII-D tokamak by edge turbulence

Abstract We have demonstrated for the first time that turbulent plasma density fluctuations in the edge of the DIII-D tokamak are responsible for substantial broadening of an injected microwave beam by successful quantitative comparison between experimental observations and first principles 2D full-wave simulations. The broadening of the beam has important implications for control of tokamak discharges through localized electron cyclotron deposition needed for eliminating magnetohydrodynamic instabilities. This new predictive capability is mandatory to design & operate present & future tokamaks in such a way that microwave heating schemes achieve their intended objectives.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Control of internal transport barriers in magnetically confined tokamak burning plasmas

The initiation, termination, and control of internal transport barriers associated with E × B flow shear near local minima of magnetic shear are examined for burning plasmas to determine if the positive feedback loops between profiles, instability, transport, and flow shear operate in regimes with fusion self-heating. A five-field transport model for the evolution of profiles of density, ion and electron temperature, ion and electron fluctuations, and radial electric field is utilized to examine the efficacy of controls associated with external inputs of heat and particles, including neutral beam injection, RF, pellets, and gas puffing. The response of the plasma to these inputs is studied in the presence of self-heating. The latter is affected by the external inputs and their modification of profiles and is, therefore, not an external control. Provided sufficient external power is applied, internal transport barriers can be created and controlled, both in ion and electron channels. Barrier control is sensitive to the locations of power deposition and pellet ablation, as well as temporal sequencing of external inputs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of the KSTAR experiments and future plan

The Korea Superconducting Tokamak Advanced Research (KSTAR) device has recently entered a new phase of operation following the installation of a tungsten mono-block divertor, providing a unique platform to investigate high-performance, long-pulse plasma scenarios for future reactors. The 2023–2024 experimental campaigns demonstrated significant progress in commissioning the tungsten divertor, developing plasma operation scenarios, and achieving real-time control. Comparative studies revealed increased core radiation losses and associated performance degradation relative to the carbon divertor environment. Alleviation strategies, such as optimized neutral beam injection timing, boron powder seeding, and impurity control through gas puffing, were shown to reduce tungsten accumulation and extend high-performance phases, including record H-mode operation exceeding 100 s. International collaboration enabled the first demonstration of high poloidal beta scenarios with an internal transport barrier on KSTAR. Advances in control included upgraded real-time resonant magnetic perturbation schemes and disruption forecasting. Furthermore, divertor detachment control using a new surrogate-model-based approach with real-time radiation imaging demonstrated active impurity and heat flux management. Supported by enhanced heating, current drive, and diagnostic systems, these achievements offer valuable insights into tungsten impurity behavior, transport physics, and control strategies for future reactors including ITER. Planned upgrades toward a full-tungsten wall and ITER-aligned real-time plasma control will further establish KSTAR as a leading experimental platform for developing operational scenarios required to achieve steady-state, burning plasma conditions.

KSTAR↗

Simultaneous control of the electron temperature and safety factor profiles in DIII-D using model-based optimal control techniques

Future tokamak power plants will likely operate using a single, well-defined plasma scenario, either in steady state or for very long pulse lengths. In order to enhance the robustness of the scenario, feedback controllers for a variety of plasma properties will be necessary to counteract any disturbances and ensure safe operation. However, only a limited set of actuators will be available to control many different quantities. Because of this, it is necessary to develop controllers that are able to regulate multiple plasma properties using a limited set of actuators. To this end, a controller has been developed for the simultaneous regulation of both the electron temperature and safety factor profiles in DIII-D. This algorithm uses a linear quadratic integral control synthesis approach based on a linearized model of the dynamics of the two profiles. Two neural network surrogate models, NubeamNet and MMMnet, are included to improve the fidelity of the model. Furthermore, the controller has been tested in simulation using COTSIM, and has demonstrated the ability to simultaneously track changes in both the electron temperature and safety factor targets, including changes in both the magnitude and the shape of the profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High precision strike point control to support experiments in the DIII-D small angle slot divertor

Improvements in strike point control enabled tests with the new Small Angle Slot (SAS) divertor installed at DIII-D with precision as tight as ±1 mm, barring brief perturbations from ELMs. Aside from being narrower than previous baffle structures in DIII-D, simulations indicate that performance of the SAS divertor should be very sensitive to strike point position, making the improved strike point control essential for experiments with the SAS divertor. Improved control entails regulating more divertor geometry target locations than before and setting higher gain on the strike point target. This is achieved by tasking more poloidal field (PF) shaping coils with divertor topology control, fine tuning of the coil configuration and algorithm gains, and adding regulation of the power supply common rail. Here, the result is that although more variables are controlled, precision is better: high frequency jitter in the strike point position is lower on average compared to related discharges with standard divertor shape control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An analysis of controlled detachment by seeding various impurity species in high performance scenarios on DIII-D and EAST

Experiments at DIII-D and EAST have demonstrated simultaneous high confinement, divertor detachment, and active control of detachment level, all of which are required for ITER. Comparing detachment control via T e and J sat , it appears that is the most straightforward sensor to use for accessing detachment onset, while J sat offers more precise control of degree of detachment. Based on these results, control using nitrogen seeding has so far shown the best ability to follow a target value with the low disruptivity and little to no degradation of performance when an Internal Transport Barrier (ITB) is present, but not all facilities allow its use. Neon seeding also can be paired with feedback control with low impact on core performance as long as there is no disruption, however shots with neon seeding commonly disrupted during these experiments. Argon is effective in EAST, but tends to degrade performance (by ≈ 10%β p ) when detachment is achieved. With ideal conditions and strike point position control, data from a single Langmuir probe are an acceptable input to the control algorithm, but this simple system is easily defeated by strike point displacement comparable to the T e or J sat scale lengths. The presence of an ITB seems to be critical to retaining core performance in detachment in these parameter ranges, as the pedestal pressure tends to decrease as a result of impurity seeding.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Characterization and controllability of radiated power via extrinsic impurity seeding in strongly negative triangularity plasmas in DIII-D

Experiments with extrinsic impurity seeding in strongly negative triangularity shapes in DIII-D achieved radiated power fractions (relative to input power) of up to ≈85% total radiation and ≈55% core radiation in steady-operating conditions. The relationship between core and total radiation was sensitive to impurity species and input power. Attempts to reach higher radiation levels via higher impurity flows resulted in radiative collapse disruptions. Nitrogen, neon, argon, and krypton were tested. Injection was by gas puffing, usually controlled by feeding back real-time estimates for core or total radiating fractions ($P_\textrm{rad} / P_\textrm{input}$). Argon and krypton were controlled by feeding back total radiating fraction, whereas neon was controlled by feeding back the core radiating fraction, due to the lower efficiency of neon as a divertor radiator. Nitrogen flows were pre-programmed. Reasonable total $P_\textrm{rad}$ control target following was achieved with argon or krypton. Control was more challenging with the neon/core radiation configuration, which was more prone to slow response and overshooting of the control target. Poor particle removal contributed to the control challenge: neon particle inventory within the last closed flux surface was roughly constant for up to 1 s (the longest duration tested) after neon injection was halted. However, separate experiments with laser-blow off of non-recycling impurities measured a short impurity confinement time, on the scale of the energy confinement time of ∼100 ms. Modeling with the Aurora impurity transport simulation matched experimental neon density profiles with full recycling (R = 1.0) and weak pumping but predicted rapid decreases in neon inventory if pumping were increased or recycling decreased. This indicates that changes outside the confined plasma (adding a well-placed pump) would improve controllability for all highly recycling species.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development and experimental qualification of novel disruption prevention techniques on DIII-D

Novel disruption prevention solutions spanning a range of control regimes are being developed and tested on DIII-D to enable ITER success. First, a new real-time control algorithm has been developed and tested for regulating nearness to stability limits and maintaining safety-margins. Its first application has been for reliable prevention of vertical displacement events (VDEs) by adjusting plasma elongation (κ) and the inner-gap between the plasma and inner-wall in response to real- time open-loop VDE growth rate (γ) estimators. VDEs were robustly prevented up to average open-loop growth rates of 800 rad/s with initial tunings, with only applying shape modification when near safety limits. Second, the disruption risk during fast, emergency shutdown after large tearing and locked modes can be significantly improved by transitioning to a limited topology during shutdown. More than 50% of emergency limited shutdowns after locked modes reach a final normalized current I_N < 0.3 before terminating, scaling to the 3 MA ITER requirement. Furthermore, this is in contrast to diverted shutdowns, the majority of which disrupt at I_N > 0.8. Despite improvements, these results highlight the critical importance of early prevention. Third, a novel emergency shut down method has been developed which excites instabilities to form a warm, helical core post-thermal quench. The current quench extends to ~100ms and avoids VDEs and runaway electron generation. Novel real-time machine learning disruption prediction has been integrated with the DIII-D proximity controller, and a real- time compatible multi-mode MHD spectroscopy technique has been developed. Results presented here were enabled by a focused effort, the Disruption Free Protocol, in DIII-D’s 2019-20 campaign to complement disruption prevention experiments with a large piggy-back program. In addition to testing novel techniques, it is estimated to have helped avoid 32 potential disruptions in piggyback operations with rapid, early shutdowns after large rotating n=1 or locked modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Toroidal Field Reversing Switch

A motor-driven, high-current switch is being designed by Stäubli Electrical Connectors in collaboration with Princeton Plasma Physics Laboratory to reverse the DIII-D Toroidal field coil current. The existing field reversing procedure requires approximately 4 h of labor performed between run days to reconfigure the bus work, thus requiring a separate run day to complete experimental scans with both field directions. This typically results in different wall conditions which complicate the results or make them invalid. The proposed switch will complete the reversal process in approximately 4-5 min, between shots, so that wall conditions are not a factor, and easily fits within the 10-12 min DIII-D shot cycle. The switch is a compact design fitting into a 157.5 × 41 cm envelope. The switch uses two copper pins that slide between Stäubli MULTILAM contacts. The switch is rated for total current of 180-kA dc for 10 s with a 12-min repetition rate; the maximum operating coil current is 124-kA dc. The switch diagnostics include: voltage drop, current monitor, thermal monitors, position sensors, and motor torque. Here, the switch is rated for 300 cycles per year, and 3000 cycles overall before contact replacement, with contact inspection yearly. The design details and operation of the switch are covered in this article.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Regulation compliant AI for fusion: explainable image-based feedback control of divertor detachment in DIII-D tokamak

While artificial intelligence (AI) has been promising for fusion control, its inherent black-box nature will make compliant implementation in regulatory environments a challenge. This study implements and validates a real-time AI-enabled linear and interpretable control system for successful divertor detachment control with the DIII-D lower divertor camera. Using D 2 gas, we demonstrate successful feedback divertor detachment control with a mean absolute difference of 2% from the target for both detachment and reattachment. This automatic training and linear processing framework can be extended to any image-based diagnostic for future fusion reactors.

computer vision↗

Prototype tests of the electromagnetic particle injector-2 for fast time response disruption mitigation in tokamaks

Predicting and controlling disruptions is an important and urgent issue for ITER. Some disruptions with a short warning time may be unavoidable. For these cases, a fast time response disruption mitigation method is essential. Experimental tests on a prototype system of a novel, rapid time-response disruption mitigation system being developed for tokamak-based reactors and as a backup option for ITER, referred to as the electromagnetic particle injector (EPI), have been able to verify the primary advantages of the concept. These are its ability to meet short warning time scales of <10 ms while attaining the projected high velocities for deep radiative payload penetration in reactor-scale plasmas. The EPI relies on an electromagnetic propulsion system. A metallic sabot is accelerated electromagnetically to the required velocities (>1 km s -1 ) within 2 ms, at which point it releases a radiative payload consisting of a shell pellet or well-defined microspheres. Initial experimental tests from the prototype system show attainment of over 600 m s -1 in about 1 ms. Finally, essential aspects of payload separation from the sabot and sabot capture have also been demonstrated at 200 m s -1 , and the method can be extended to over 2 km s -1 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Combining physics-based and data-driven models for quantitatively accurate plasma profile prediction that extrapolates well; with application to DIII-D, AUG, and ITER tokamaks

For design, scenario planning, and control, ITER and all other envisioned tokamaks rely on a variety of statistical and physics-based models to extrapolate to unseen regimes; most notably from low plasma current to high. A 'meta-learning' methodology for combining the accuracy of data-driven models with the generalizability of physics-based models is described and tested, yielding a 5–10 percent improvement in performance beyond either alone for the task of extrapolating time-dependent plasma profile prediction from low- to high- plasma current DIII-D tokamak discharges. Meanwhile, it is shown that both machine learning models extrapolated far-distribution and state-of-the-art 'physics-based' profile predictors fare worse than merely assuming plasma profiles do not change from their initial values. Finally, a variety of other mechanisms for helping data-driven models generalize—transfer learning, adding contextual information from physics simulators, and adding data from the ASDEX Upgrade tokamak—are attempted for similar extrapolation tasks but, in the methodology used in this paper, yield no significant improvement beyond simple data-driven models. Results are summarized in figures 15 and 16.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗