The vertical instability of the plasma is one of the main causes of large disruption. For the operation of an elongated tokamak plasma, it is necessary to control the vertical instability of the plasma effectively. This article implements a new vertical position control algorithm by using a neural network model for more accurate vertical position estimation. Meanwhile, a high-speed acquisition and fast control system is designed, which can reduce latency and provide sufficient computing resources for the neural network. Besides, the control algorithm is deployed in the new system with a separate server. Finally, the benefit of using a neural network in the new control system to control vertical position is confirmed by EAST experiments. Experimental results indicate that the neural network can accurately calculate the vertical position under different configurations, and the high-speed acquisition and fast control system reduces the response transmission delay and enhances the vertical position control.

Implementation of EAST Fast Vertical Position Control With Neural Network-Based Estimator


 HT-6M tokamak is restarted for Thailand Institute of Nuclear Technology, TINT. In order to ensure the smooth breakdown of plasma and obtain plasma discharge parameters, the optimization of poloidal field coils and upgrade of magnetic diagnostics are described in this article. A perfect null field (the stray field in main chamber < 10G) is obtained using ohmic heating field. To get the main information of plasma, an external magnetic diagnostics system is designed and calibrated, including Rogowski coil (measuring plasma current), magnetic probe (measuring external field), diamagnetic loops (measuring β
 
 p
 ) and so on. Besides, in order to realize high frequency signal measurement and transmission, a series of frequency response with the magnetic probe and transmission line are tested. Later in the paper, to verify the null field, a fitting code was developed to reconstruct the stray field in vacuum chamber based on measured magnetic probes and flux loops. The result shows the error is within 1.5%. This indicates the accuracy of the magnetic measurement system and ensures the preparation for the breakdown of plasma.

Upgrade of magnetic diagnostic system for HT-6M operation restart

The HT-6M tokamak at the Thailand Institute of Nuclear Technology has been restarted. In order to ensure the smooth breakdown of plasma and obtain plasma discharge parameters, optimization of the poloidal field coils and upgrade of the magnetic diagnostics are described in this article. A perfect null field (stray field in the main chamber < 10 G) is obtained using an ohmic heating field. To obtain important information about the plasma, an external magnetic diagnostics system is designed and calibrated, including a Rogowski coil (measuring plasma current), a magnetic probe (measuring external field), diamagnetic loops (measuring β p) and so on. In order to realize high-frequency signal measurement and transmission, a series of frequency responses with the magnetic probe and transmission line are tested. Later, to verify the null field, a fitting code is developed to reconstruct the stray field in the vacuum chamber based on magnetic probe measurements and flux loops. The results show that the error is within 1.5%. This indicates the accuracy of the magnetic measurement system and ensures the preparation for the breakdown of plasma.

Upgrade of the magnetic diagnostic system for restart of HT-6M operation

Electric fields are commonplace in plasmas and affect transport by driving currents and, in some cases, instabilities. The necessary condition for instability in collisionless plasmas is commonly understood to be described by the Penrose criterion, which quantifies a sufficient relative drift between different populations of particles that must be present for wave amplification via inverse Landau damping. For example, electric fields generate drifts between electrons and ions that can excite the ion-acoustic instability. Here, we use particle-in-cell simulations and linear stability analysis to show that the electric field can drive a fundamentally different type of kinetic instability, named the electron-field instability. This instability excites electron plasma waves with wavelengths ≳30λDe, has a growth rate that is proportional to the electric field strength, and does not require a relative drift between electrons and ions. The Penrose criterion does not apply when accounting for the electric field. The large value of the observed frequency, near the electron plasma frequency, further distinguishes it from the standard ion-acoustic instability, which oscillates near the ion plasma frequency. The ubiquity of macroscopic electric fields in quasineutral plasmas suggests that this instability is possible in a host of systems, including low-temperature and space plasmas. In fact, damping from neutral collisions in such systems is often not enough to completely damp the instability, adding to the robustness of the instability across plasma conditions.

Electron-field instability: Excitation of electron plasma waves by an electric field

The measurements by diamagnetic loops in EAST

Electrostatic fluctuations driven by runaway electrons (REs) have been observed following a thermal quench during Experimental Advanced Superconducting Tokamak–intended disruptions, which are triggered by massive gas injection. Electrostatic fluctuations are clearly detected using several radiation-related diagnostics and in two distinct frequency bands: 10–20 kHz and 30–40 kHz. The appearances of fluctuations are directly correlated with REs. Fluctuations observed during argon injection and neon injection have significantly different evolution with time, whereas no fluctuations can be found with helium injection. The measured frequency scales with different amounts of injected gases finally tend to be saturated. A clear phase difference is detected, and a mode structure of (m, n) = (1, 0) is identified in the soft x-ray detector array. Here, m and n are the poloidal and toroidal mode numbers, respectively. The geodesic acoustic mode proposed as a candidate instability is further discussed, and the barely trapped/passing electrons can contribute to drive the mode. Fluctuations are also correlated with significant RE loss, which supports the possibility of kinetic instability for RE mitigation in a tokamak reactor.

/pdf/observation-of-electrostatic-fluctuations-driven-by-runaway-4p3wq6uz.pdf

Observation of electrostatic fluctuations driven by runaway electrons in EAST disruptions

Plasma vertical displacement control is essential for the stable operation of tokamak devices. The traditional plasma vertical displacement calculation method is not suitable for balancing speed and accuracy simultaneously, which is necessary for real-time feedback control. In this study, neural networks are used to rapidly detect vertical displacement recognition. Based on a fully connected neural network, the vertical displacement calculation model is trained and tested using magnetic data of approximately 2000 shots. To compare the effects of different inputs on vertical displacement calculation, different magnetic measurement diagnostic signals are used to train and test the model. Compared with a full magnetic measurement dataset, 39 magnetic measurement signals (38 magnetic probes and plasma current) show better accuracy with mean square error <0.0005. The model is tested using historical experimental data, and it demonstrates accurate vertical displacement calculation even in the case of a vertical displacement event. In general, neural network algorithm has great application potential in vertical displacement calculation.

Research on plasma vertical displacement calculation based on neural network

This paper describes scalings of the H-mode confinement database of neutral beam injection (NBI)-lower hybrid wave (LHW) and electron cyclotron resonant heating-LHW plasmas in the EAST tokamak. Fundamental information of the EAST H-mode database and the details of calculation of the thermal energy confinement time in EAST are presented. The result of the scaling model τE,EASTS,H,NBI - LHW of the thermal energy confinement time in NBI-LHW plasmas with root-mean-square-error RMSE=5.5% , compared with the multi-machine scaling model τth,98y2 derived from the multi-machine database (mainly NBI heating) with RMSE=12.9% , is obtained. The scaling τE,EAST,H,NBI - LHW presents a similar dependency on plasma current and power loss and a lower dependency on plasma density and elongation, but stronger dependency on toroidal field than in τth,98y2 . The scaling τE,EAST,H,ECRH - LHW demonstrates a similar dependency on plasma current and power loss and lower dependency on plasma density, but a negative dependency with large error bars on elongation compared with τE,EAST,H,NBI - LHW in NBI-LHW plasmas. The comparison of EAST models with the more recent multi-tokamak scaling ITPA20-IL shows a similar engineering dependency on plasma current, power loss and plasma density, but opposite dependency on toroidal field.

https://iopscience.iop.org/article/10.1088/1741-4326/acb15f/pdf

The scalings of the thermal energy confinement time in EAST H-mode plasmas

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Papers

The measurements by diamagnetic loops in EAST

Observation of electrostatic fluctuations driven by runaway electrons in EAST disruptions

Research on plasma vertical displacement calculation based on neural network

The scalings of the thermal energy confinement time in EAST H-mode plasmas