ABSTRACT
The path of tokamak fusion and International thermonuclear experimental reactor (ITER) is maintaining high-performance plasma to produce sufficient fusion power. This effort is hindered by the transient energy burst arising from the instabilities at the boundary of plasmas. Conventional 3D magnetic perturbations used to suppress these instabilities often degrade fusion performance and increase the risk of other instabilities. This study presents an innovative 3D field optimization approach that leverages machine learning and real-time adaptability to overcome these challenges. Implemented in the DIII-D and KSTAR tokamaks, this method has consistently achieved reactor-relevant core confinement and the highest fusion performance without triggering damaging bursts. This is enabled by advances in the physics understanding of self-organized transport in the plasma edge and machine learning techniques to optimize the 3D field spectrum. The success of automated, real-time adaptive control of such complex systems paves the way for maximizing fusion efficiency in ITER and beyond while minimizing damage to device components.
ABSTRACT
A scalable system for real-time analysis of electron temperature and density based on signals from the Thomson scattering diagnostic, initially developed for and installed on the NSTX-U experiment, was recently adapted for the Large Helical Device and operated for the first time during plasma discharges. During its initial operation run, it routinely recorded and processed signals for four spatial points at the laser repetition rate of 30 Hz, well within the system's rated capability for 60 Hz. We present examples of data collected from this initial run and describe subsequent adaptations to the analysis code to improve the fidelity of the temperature calculations.
ABSTRACT
A detailed description of a prototype setup for real-time (RT) Thomson scattering (TS) analysis is presented and implemented in the multi-point Thomson scattering (MPTS) diagnostic system at the National Spherical Torus Experiment Upgrade (NSTX-U). The data acquisition hardware was upgraded with RT capable electronics (RT-analog digital converters and a RT server) that allow for fast digitization of the laser pulse signal of eight radial MPTS channels. In addition, a new TS spectrum analysis software for a rapid calculation of electron temperature (Te) and electron density (ne) was developed. Testing of the RT hardware and data analysis software was successfully completed and benchmarked against the standard, post-shot evaluation. Timing tests were performed showing that the end-to-end processing time was reproducibly below 17 ms for the duration of at least 5 s, meeting a 60 Hz deadline by the laser pulse repetition rate over the length of a NSTX-U discharge. The presented RT framework is designed to be scalable in system size, i.e., incorporation of additional radial channels by solely adding additional RT capable hardware. Furthermore, it is scalable in its operation duration and was continuously running for up to 30 min, making it an attractive solution for machines with long discharges such as advanced, non-inductive tokamaks or stellarators.
ABSTRACT
A model-based feedback system is presented enabling the simultaneous control of the stored energy through ßn and the toroidal rotation profile of the plasma in National Spherical Torus eXperiment Upgrade device. Actuation is obtained using the momentum from six injected neutral beams and the neoclassical toroidal viscosity generated by applying three-dimensional magnetic fields. Based on a model of the momentum diffusion and torque balance, a feedback controller is designed and tested in closed-loop simulations using TRANSP, a time dependent transport analysis code, in predictive mode. Promising results for the ongoing experimental implementation of controllers are obtained.
ABSTRACT
Measuring free-surface, liquid-metal flow velocity is challenging to do in a reliable and accurate manner. This paper presents a non-invasive, easily calibrated method of measuring the surface velocities of open-channel liquid-metal flows using an IR camera. Unlike other spatially limited methods, this IR camera particle tracking technique provides full field-of-view data that can be used to better understand open-channel flows and determine surface boundary conditions. This method could be implemented and automated for a wide range of liquid-metal experiments, even if they operate at high-temperatures or within strong magnetic fields.
