New millimeter-wave diagnostics to locally probe internal density and magnetic field fluctuations in National Spherical Torus Experiment-Upgrade (invited).

A set of new millimeter-wave diagnostics will deliver unique measurement capabilities for National Spherical Torus Experiment-Upgrade to address a variety of plasma instabilities believed to be important in determining thermal and particle transport, such as micro-tearing, global Alfvén eigenmodes, kinetic ballooning, trapped electron, and electron temperature gradient modes. These diagnostics include a new integrated intermediate-k Doppler backscattering (DBS) and cross-polarization scattering (CPS) system (four channels, 82.5-87 GHz) to measure density and magnetic fluctuations, respectively. The system can access reasonably large normalized wavenumbers kθρs ranging from ≤0.5 to 15 (where ion sound gyroradius ρs = 1 cm and kθ is the binormal density turbulence wavenumber). The system addresses the challenges for making useful DBS/CPS measurements with a remote control of launch polarization (X- or O-mode), probed wavenumber, polarization match of the launch beam with the edge magnetic field pitch angle, and beam steering of the launched beam for wave-vector alignment. In addition, a low-k DBS system consisting of eight fixed frequencies (34-52 GHz) and four tunable frequencies (55-75 GHz) for low-k density turbulence and fast ion physics will be located at a nearby port location. The combined systems cover the near LCFS and pedestal regions (34-52 GHz), the pedestal or mid-radius (50-75 GHz), and core plasmas (82.5-87 GHz).

Using convolutional neural networks to detect edge localized modes in DIII-D from Doppler backscattering measurements.

In H-mode tokamak plasmas, the plasma is sometimes ejected beyond the edge transport barrier. These events are known as edge localized modes (ELMs). ELMs cause a loss of energy and damage the vessel walls. Understanding the physics of ELMs, and by extension, how to detect and mitigate them, is an important challenge. In this paper, we focus on two diagnostic methods-deuterium-alpha (Dα) spectroscopy and Doppler backscattering (DBS). The former detects ELMs by measuring Balmer alpha emission, while the latter uses microwave radiation to probe the plasma. DBS has the advantages of having a higher temporal resolution and robustness to damage. These advantages of DBS diagnostic may be beneficial for future operational tokamaks, and thus, data processing techniques for DBS should be developed in preparation. In sight of this, we explore the training of neural networks to detect ELMs from DBS data, using Dα data as the ground truth. With shots found in the DIII-D database, the model is trained to classify each time step based on the occurrence of an ELM event. The results are promising. When tested on shots similar to those used for training, the model is capable of consistently achieving a high f1-score of 0.93. This score is a performance metric for imbalanced datasets that ranges between 0 and 1. We evaluate the performance of our neural network on a variety of ELMs in different high confinement regimes (grassy ELM, RMP mitigated, and wide-pedestal), finding broad applicability. Beyond ELMs, our work demonstrates the wider feasibility of applying neural networks to data from DBS diagnostic.

Design elements and first data from a new Doppler backscattering system on the MAST-U spherical tokamak.

A new Doppler backscattering (DBS) system has been installed and tested on the MAST-U spherical tokamak. It utilizes eight simultaneous fixed frequency probe beams (32.5, 35, 37.5, 40, 42.5, 45, 47.5, and 50 GHz). These frequencies provide a range of radial positions from the edge plasma to the core depending on plasma conditions. The system utilizes a combination of novel features to provide remote control of the probed density wavenumber, the launched polarization (X vs O-mode), and the angle of the launched DBS to match the magnetic field pitch angle. The range of accessible density turbulence wavenumbers (kθ) is reasonably large with normalized wavenumbers kθρs ranging from ≤0.5 to 9 (ion sound gyroradius ρs = 1 cm). This wavenumber range is relevant to a variety of instabilities believed to be important in establishing plasma transport (e.g., ion temperature gradient, trapped electron, electron temperature gradient, micro-tearing, kinetic ballooning modes). The system is specifically designed to address the requirement of density fluctuation wavevector alignment which can significantly reduce the SNR if not accounted for.

Evaluation of a new DIII-D Doppler backscattering system for higher wavenumber measurement and signal enhancement.

The high density fluctuation poloidal wavenumber, kθ (kθ > 8 cm-1, kθρs > 5, ρs is the ion gyro radius using the ion sound velocity), measurement capability of a new Doppler backscattering (DBS) system at the DIII-D tokamak has been experimentally evaluated. In DBS, wavenumber (k) matching becomes more important at higher wavenumbers, owing to the exponential dependence of the measured signal loss factor on wave vector mismatch. Wave vector matching allows for the Bragg scattering condition to be satisfied, which minimizes the signal loss at higher k's. In the previous DBS system, without toroidal wave vector matching, the measured DBS signal-to-noise ratio at higher kθ (>8 cm-1) is substantially reduced, making it difficult to measure higher kθ turbulence. The new DBS system has been optimized to access higher wavenumber, kθ ≤ 20 cm-1, density turbulence measurement. The optimization hardware addresses fluctuation wave vector matching using toroidal steering of the launch mirror to produce a backscattered signal with improved intensity. The probe's sensitivity to high-k density fluctuations has been increased by approximately an order of magnitude compared to the old system that has been in use at DIII-D. Note that typical measurement locations are above or below the tokamak midplane on the low field side with normalized radial ranges of 0.5-1.0. The new DBS probe system with the toroidal matching of fluctuation wave vectors is thought to be critical to understanding high-k turbulent transport in fusion-relevant research at DIII-D.

Validating and optimizing mismatch tolerance of Doppler backscattering measurements with the beam model (invited).

We use the beam model of Doppler backscattering (DBS), which was previously derived from beam tracing and the reciprocity theorem, to shed light on mismatch attenuation. This attenuation of the backscattered signal occurs when the wavevector of the probe beam's electric field is not in the plane perpendicular to the magnetic field. Correcting for this effect is important for determining the amplitude of the actual density fluctuations. Previous preliminary comparisons between the model and Mega-Ampere Spherical Tokamak (MAST) plasmas were promising. In this work, we quantitatively account for this effect on DIII-D, a conventional tokamak. We compare the predicted and measured mismatch attenuation in various DIII-D, MAST, and MAST-U plasmas, showing that the beam model is applicable in a wide variety of situations. Finally, we performed a preliminary parameter sweep and found that the mismatch tolerance can be improved by optimizing the probe beam's width and curvature at launch. This is potentially a design consideration for new DBS systems.