Multi-scale turbulence simulation suggesting improvement of electron heated plasma confinement

Milestone in predicting core plasma turbulence: successful multi-channel validation of the gyrokinetic code GENE

On the basis of several recent breakthroughs in fusion research, many activities have been launched around the world to develop fusion power plants on the fastest possible time scale. In this context, high-fidelity simulations of the plasma behavior on large supercomputers provide one of the main pathways to accelerating progress by guiding crucial design decisions. When it comes to determining the energy confinement time of a magnetic confinement fusion device, which is a key quantity of interest, gyrokinetic turbulence simulations are considered the approach of choice - but the question, whether they are really able to reliably predict the plasma behavior is still open. The present study addresses this important issue by means of careful comparisons between state-of-the-art gyrokinetic turbulence simulations with the GENE code and experimental observations in the ASDEX Upgrade tokamak for an unprecedented number of simultaneous plasma observables.

Multi-fidelity information fusion for turbulent transport modeling in magnetic fusion plasma

Maintaining the high-temperature and pressure conditions required for sustained nuclear fusion is challenging due to the turbulent transport that naturally occurs in the plasma. Developing reliable models for turbulent transport is essential for progress in fusion research and development. This study proposes multi-fidelity modeling for the improved accuracy of regression models for turbulent transport in magnetic fusion plasma. Multi-fidelity modeling combines low-fidelity data, which have low accuracy but many data points, with high-fidelity data, which are highly accurate but have few data points or small parameter ranges, to enhance the overall predictive accuracy of a model. We used a multi-fidelity information fusion technique, Nonlinear AutoRegressive Gaussian Process regression (NARGP), to solve the regression problems associated with turbulent transport in plasma. We applied NARGP to (i) merge the low-resolution and high-resolution simulation results, (ii) apply regression of turbulence diffusivity to the experimental dataset using linear analyses, and (iii) adapt the quasi-linear transport model to nonlinear simulation results of a particular discharge. We demonstrated that NARGP improved the prediction accuracy of the plasma turbulent transport model. NARGP offers a robust and versatile method for integrating multi-fidelity data, and its broad applicability may contribute to optimizing fusion reactor design and operation.

Reversal of the Parallel Drift Frequency in Anomalous Transport of Impurity Ions

It is found that, in the studies of heavy ion transport with gyrokinetic simulations, the ion parallel drift frequency can reverse sign in velocity space when the amplitude variation of the electrostatic potential fluctuation is strong along the magnetic field line. As a result, the particle transport related to the parallel dynamics is strongly enhanced. It is noted that, while parallel gradient of the fluctuation amplitude can be instigated by a large magnetic shear or safety factor in a tokamak, the generic mechanism is independent of its cause, which suggests broader applications to kinetic plasma problems. Some relevant topics are briefly addressed in the end.

A simplified model to estimate nonlinear turbulent transport by linear dynamics in plasma turbulence

A simplified model to estimate nonlinear turbulent transport only by linear calculations is proposed, where the turbulent heat diffusivity in tokamak ion temperature gradient(ITG) driven turbulence is reproduced for a wide parameter range including near- and far-marginal ITG stability. The optimal nonlinear functional relation(NFR) between the turbulent diffusivity, the turbulence intensity [Formula: see text], and the zonal-flow intensity [Formula: see text] is determined by means of mathematical optimization methods. Then, an extended modeling for [Formula: see text] and [Formula: see text] to incorporate the turbulence suppression effects and the temperature gradient dependence is carried out. The simplified transport model is expressed as a modified nonlinear function composed of the linear growth rate and the linear zonal-flow decay time. Good accuracy and wide applicability of the model are demonstrated, where the regression error of [Formula: see text] indicates improvement by a factor of about 1/4 in comparison to that in the previous works.