arXiv subjects

Youjun Hu

Publications and source records attributed to Youjun Hu.

7 recordsLinked to original sources

arXiv2026

Linear and nonlinear benchmark of gyrokinetic simulation of energetic particle driven toroidal Alfven eigenmodes in ITPA TAE benchmark case

A new gyrokinetic code, TEK, was benchmarked in simulating energetic particle (EP) driven toroidal Alfven eigenmodes (TAEs) in the simple tokamak configuration chosen by the ITPA-EP group for code benchmarking purpose. Linear benchmark has been well established by other codes, whereas nonlinear benchmark for this case is lacking. This paper presents, besides the linear benchmark, nonlinear results for both single-n and multiple-n simulations (n is the toroidal mode number). The nonlinear results are in good agreement with an analytical theory on zonal field beat-driven by Alfven eigenmodes, partially verifying correctness of the nonlinear simulations. The saturation level and the resulting EP transport are examined. This provides data for future inter-code nonlinear benchmarking. In TEK, all species (electrons, thermal ions, EPs) are treated on the same footing using the gyrokinetic model (with electrons in the zero Larmor radius limit). The electromagnetic cancellation problem is mitigated by using the mixed-variable pullback method. Numerical details related to electromagnetic gyrokinetic simulation are discussed.

physics.plasm-ph↗

arXiv2025

EFIT-mini: An Embedded, Multi-task Neural Network-driven Equilibrium Inversion Algorithm

Equilibrium reconstruction, which infers internal magnetic fields, plasmas current, and pressure distributions in tokamaks using diagnostic and coil current data, is crucial for controlled magnetic confinement nuclear fusion research. However, traditional numerical methods often fall short of real-time control needs due to time-consuming computations or iteration convergence issues. This paper introduces EFIT-mini, a novel algorithm blending machine learning with numerical simulation. It employs a multi-task neural network to replace complex steps in numerical equilibrium inversion, such as magnetic surface boundary identification, combining the strengths of both approaches while mitigating their individual drawbacks. The neural network processes coil currents and magnetic measurements to directly output plasmas parameters, including polynomial coefficients for $p'$ and $ff'$, providing high-precision initial values for subsequent Picard iterations. Compared to existing AI-driven methods, EFIT-mini incorporates more physical priors (e.g., least squares constraints) to enhance inversion accuracy. Validated on EXL-50U tokamak discharge data, EFIT-mini achieves over 98% overlap in the last closed flux surface area with traditional methods. Besides, EFIT-mini's neural network and full algorithm compute single time slices in just 0.11ms and 0.36ms at 129$\times$129 resolution, respectively, representing a three-order-of-magnitude speedup. This innovative approach leverages machine learning's speed and numerical algorithms' explainability, offering a robust solution for real-time plasmas shape control and potential extension to kinetic equilibrium reconstruction. Its efficiency and versatility position EFIT-mini as a promising tool for tokamak real-time monitoring and control, as well as for providing key inputs to other real-time inversion algorithms.

physics.plasm-ph↗

arXiv2023

Fast equilibrium reconstruction by deep learning on EAST tokamak

A deep neural network is developed and trained on magnetic measurements (input) and EFIT poloidal magnetic flux (output) on the EAST tokamak. In optimizing the network architecture, we use automatic optimization in searching for the best hyperparameters, which helps the model generalize better. We compare the inner magnetic surfaces and last-closed-flux surfaces (LCFSs) with those from EFIT. We also calculated the normalized internal inductance, which is completely determined by the poloidal magnetic flux and can further reflect the accuracy of the prediction. The time evolution of the internal inductance in full discharges is compared with that provided by EFIT. All of the comparisons show good agreement, demonstrating the accuracy of the machine learning model, which has the high spatial resolution as the off-line EFIT while still meets the time constraint of real-time control.

physics.plasm-ph↗

arXiv2022

Simulation of neutral beam current drive on EAST tokamak

Neutral beam current drive (NBCD) on the EAST tokamak is studied by using Monte-Carlo test particle code TGCO. Phase-space structure of the steady-state fast ion distribution is examined and visualized. We find that trapped ions carry co-current current near the edge and counter-current current near the core. However, the magnitude of the trapped ion current is one order smaller than that of the passing ions. Therefore their contribution to the fast ion current is negligible (1% of the fast ion current). We examine the dependence of the fast ion current on two basic plasma parameters: the plasma current I_p and plasma density n_e. The results indicate that the dependence of fast ion current on I_p is not monotonic: with I_p increasing, the fast ion current first increases and then decreases. This dependence can be explained by the change of trapped fraction and drift-orbit width with I_p. The fast ion current decreases with the increase of plasma density n_e. This dependence is related to the variation of the slowing-down time with n_e, which is already well known and is confirmed in our specific situation. The electron shielding effect to the fast ion current is taken into account by using a fitting formula applicable to general tokamak equilibria and arbitrary collisionality regime. The dependence of the net current on the plasma current and density follows the same trend as that of the fast ion current.

physics.plasm-ph↗

arXiv2021

Effects of resonant magnetic perturbations on neutral beam heating in a tokamak

Effects of resonant magnetic perturbations (RMPs) on tangential neutral beam heating in the EAST tokamak are studied numerically. RMPs with linear resistive magnetohydrodynamics response are used in the modeling. A variety of representing configurations of RMP coil currents are examined and their effects on the NBI heating efficiency are compared, in order to find a parameter window where deleterious effects of RMPs on NBI heating efficiency are minimized. It is found that the internal redistribution of fast ions by RMPs induces local accumulation of fast ions, resulting in higher local fast ion pressure than the case without RMPs. It is also found that the toroidal phasing of the RMP with respect to the fast ion source has slight effects on the steady-state radial profile of fast ions. The dependence of fast ion loss fraction on the RMP up-down phase difference shows similar behavior as the dependence of the radial width of chaotic magnetic field on the phase difference. A statistical method of identifying resonances between RMPs and lost fast ions is proposed and the results indicate that some resonances between RMPs and lost passing particles may be of non-integer fractional order, rather than the usual integer order.

physics.plasm-ph↗

arXiv2019

Numerical study of transition between even and odd toroidal Alfv\'en eigenmodes on EAST

Linear simulations of toriodal Alfv\'en eigenmodes (TAEs) driven by energetic particles (EPs) on EAST (Experimental Advanced Superconducting Tokamak) are performed using the hybrid-kinetic MHD (HK-MHD) model implemented in NIMROD code. The EAST equilibrium is reconstructed using the EFIT code based on experimental measurement. The "slowing down" distribution is adopted for modeling the equilibrium distribution of the energetic ions from the deuterium neutral beam injection on EAST. The frequency, the dominant poloidal mode number, the radial location and the detailed 2D mode structure of the TAE/RSAE/EPM modes are consistent between the eigenvalue analysis and the NIMROD simulation. As the $\beta$ fraction of EP increases, a transition between even and odd TAEs occurs, along with that between the ballooning and anti-ballooning mode structures. When the $\beta$ fraction of EP is close to the transition threshold, both types of TAEs coexist.

physics.plasm-ph↗

arXiv2016

Observation of Toroidal Alfven Eigenmodes during Minor Disruptions in Ohmic Plasmas

Toroidal Alfven eigenmodes (TAEs) excited in purely ohmically heated plasmas without any auxiliary heating have been identified for the first time in the SUNIST spherical tokamak. The TAE modes are observed during minor disruptions and have a frequency range of 150-500 kHz. The mode structure analysis indicates the existence of both m/n=-3/-1 and -4/-1 harmonics, propagating in the electron diamagnetic direction in the laboratory frame of reference. These TAEs appear simultaneously with the generation of runaway electrons in the current quench phase, accompanying with the density sweeping during the minor disruption. Possible driving mechanisms and potential applications of these TAEs are discussed.

physics.plasm-ph↗