The dynamics of burning plasmas in tokamaks are crucial for advancing controlled thermonuclear fusion. This study applies the NeuralPlasmaODE, a multi-region multi-timescale transport model, to simulate the complex energy transfer processes in ITER deuterium-tritium (D-T) plasmas. Our model captures the interactions between energetic alpha particles, electrons, and ions, which are vital for understanding phenomena such as thermal runaway instability. We employ neural ordinary differential equations (Neural ODEs) for the numerical derivation of diffusivity parameters, enabling precise modeling of energy interactions between different plasma regions. By leveraging transfer learning, we utilize model parameters derived from DIII-D experimental data, enhancing the efficiency and accuracy of our simulations without training from scratch. Applying this model to ITER's inductive and non-inductive operational scenarios, our results demonstrate that radiation and transport processes effectively remove excess heat from the core plasma, preventing thermal runaway instability. This study underscores the potential of machine learning in advancing our understanding and control of burning plasma dynamics in fusion reactors.
The traditional Thomson scattering diagnostic is based on measurement of the wavelength spectrum of scattered light, where electron temperature measurements are inferred from thermal broadening of the scattered laser light. At sufficiently high temperatures, especially those predicted for ITER and other burning plasmas, relativistic effects cause a change in the polarization state of the scattered photons. The resulting depolarization of the scattered light is temperature dependent and has been proposed elsewhere as a potential alternative to the traditional spectral decomposition technique. F…
Dynamics of ion temperature gradient modes in burning plasma conditions in the presence of energetic particles
Laboratoire de Physique des Plasmas, CNRS, Université Paris Saclay, Ecole Polytechnique, Sorbonne Université, Observatoire de Paris（等离子体物理实验室，法国国家科学研究中心，巴黎萨克雷大学，巴黎综合理工学院，索邦大学，巴黎天文台）；De Vinci Higher Education, De Vinci Research Center（德文奇高等教育，德文奇研究中心）；Max Planck Institut für Plasmaphysik（马克斯·普朗克等离子体物理研究所）
A perturbative hybrid ideal-MHD/drift-kinetic approach to assess the stability of alpha-particle-driven Alfven eigenmodes in burning plasmas is used to show that certain foreseen ITER scenarios, namely the Ip = 15 MA baseline scenario with very low and broad core magnetic shear, are sensitive to small changes in the background magnetic equilibrium. Slight variations (of the order of 1%) of the safety-factor value on axis are seen to cause large changes in the growth rate, toroidal mode number, and radial location of the most unstable eigenmodes found. The observed sensitivity is shown to proce…
Gyrokinetic turbulent transport simulations on steady burning condition in D-T-He plasmas
National Institute for Fusion Science, National Institutes of Natural Sciences（国立研究开发法人 国立科学研究所 核聚变科学研究所）；The Graduate University for Advanced Studies（高等研究院）；PRESTO, Japan Science and Technology Agency（日本科学技术振兴机构 PRESTO项目）；Graduate School of Engineering, Kyoto University（京都大学 工学研究科）
Plasma Science and Fusion Center, Massachusetts Institute of Technology（麻省理工学院等离子体科学与聚变中心）；Institute of Plasma Physics, Chinese Academy of Sciences（中国科学院等离子体物理研究所）；General Atomics（通用原子公司）
Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its low performance (LP) data is key to success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the…
Over the past decade, dust particulate contamination has increasingly become an area of concern within the fusion research community. In a burning plasma machine design like the International Thermonuclear Experimental Reactor (ITER), dust contamination presents problems for diagnostic integration and may contribute to tritium safety issues. Additionally due to ITER design, such dust contamination problems are projected to become of even greater concern due to dust/wall interactions and possible instabilities created within the plasma by such particulates. Since the dynamics of such dust can i…
Understanding and predicting divertor heat-load width $λ_q$ is a critically important problem for an easier and more robust operation of ITER with high fusion gain. Previous predictive simulation data for $λ_q$ using the extreme-scale edge gyrokinetic code XGC1 in the electrostatic limit under attached divertor plasma conditions in three major US tokamaks [C.S. Chang et al., Nucl. Fusion 57, 116023 (2017)] reproduced the Eich and Goldston attached-divertor formula results [formula #14 in T. Eich et al., Nucl. Fusion 53, 093031 (2013); R.J. Goldston, Nucl. Fusion 52, 013009 (2012)], and further…
Machine-learning surrogate models for nonlinear energetic-particle transport predictions in ITER
Oak Ridge National Laboratory（橡树岭国家实验室）；Institute for Fusion Studies, The University of Texas at Austin（德克萨斯大学奥斯汀分校聚变研究所）；Universidad Carlos III de Madrid（马德里卡洛斯三世大学）
We report on a theoretical discovery of new regimes of Alfvén eigenmode (AE) induced fast ion transport in tokamak plasmas, where microturbulence plays the role of a mediator of fast ion relaxation. Coulomb collisional scattering alone leads to small AE amplitudes and does not reproduce the steady state regimes observed in experiments. We show that in nonlinear regimes the effective pitch angle scattering due to microturbulence can lead to steady state AE amplitude evolution. This indicates a new route for fast ion losses, which is beyond the scenarios described in "Energetic ion transport by …
FAST (Fusion Advanced Studies Torus), the Italian proposal of a Satellite Facility to ITER, is a compact tokamak (R$_0$ = 1.82 m, a = 0.64 m, triangularity $δ$ = 0.4) able to investigate non-linear dynamics effects of $α$-particle behavior in burning plasmas and to test technical solutions for the first wall/divertor directly relevant for ITER and DEMO. Currently, ENEA is investigating the feasibility of a superconducting solution for the magnet system. This paper focuses on the analysis of the CS (Central Solenoid) magnet thermal behavior. In particular, considering a superconducting solution…
The lower hybrid wave trapping in a tokamak edge transport barrier is predicted. This effect makes possible excitation of the low-power-threshold absolute parametric decay instability leading to side-scattering of the ordinary microwave pump in the electron cyclotron resonance heating experiments. The instability can result in broadening of the power deposition profile both in present day machines and in ITER.
Two analytical models for the ordinary mode propagating through inhomogeneous edge plasma layer are developed. Simple analytical expressions for diffusion-like angular and spatial beam width variation are obtained and compared to time-averaged results coming from 2D Maxwell's equations solver for different turbulence k-spectra and plasma conditions. The strong spatial broadening of microwave beam is predicted by the two approaches at realistic turbulent edge parameters for ECRH experiments at ITER.
