arXiv subjects

Youwen Sun

Publications and source records attributed to Youwen Sun.

10 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↗

arXiv2026

DKEKAN: A single-parameterized KAN surrogate for Drift Kinetic Equation Toward Fast Neoclassical Toroidal Viscosity Torque Modeling in Tokamaks

The neoclassical toroidal viscosity (NTV) torque is a critical driver of toroidal rotation in tokamaks, profoundly influencing plasma stability and performance. Consequently, incorporating NTV effects is essential for modern integrated modeling frameworks that aim to self-consistently unify multiple physical processes. However, the high computational cost of NTV modeling precludes its self-consistent integration within such frameworks. This bottleneck arises because NTV calculation requires solving its governing equation--the drift kinetic equation (DKE)--in high-dimensional phase space. To address this issue, this study develops DKEKAN, a single-parameterized Kolmogorov-Arnold Network (SKAN) surrogate for solving DKE, to realize fast NTV modeling in tokamaks. The research process consists of the following steps: Firstly, a large dataset mapping DKE equation parameters to solutions is generated based on first-principle simulations under plasma parameters of the Experimental Advanced Superconducting Tokamak (EAST); Secondly, a surrogate model for solving DKE is developed based on the SKAN framework, which also incorporates a modular expert network design; Finally, the DKEKAN surrogate model is integrated with the NTV modeling framework to realize fast NTV calculation. With its physics-grouped expert layer and SKAN backbone, DKEKAN outperforms the tested MLP, KAN, and neural-operator baselines in overall prediction accuracy, while reducing the standalone DKE-solving time from 35.85s to 3.74s, corresponding to a speedup of approximately 9.6x, and reducing the total coupled NTVTOK runtime from 38.24s to 5.58s, corresponding to an overall speedup of approximately 6.9x. This work effectively overcomes the computational bottleneck in NTV simulations, thus supporting further integrated modeling that incorporates NTV effects.

physics.plasm-ph↗

arXiv2026

A Data-Free, Physics-Informed Surrogate Solver for Drift Kinetic Equation: Enabling Fast Neoclassical Toroidal Viscosity Torque Modeling in Tokamaks

Toroidal rotation is crucial for maintaining stable and high performance plasmas in tokamak fusion reactors. Among its driving mechanisms, the neoclassical toroidal viscosity (NTV) torque--induced by three-dimensional magnetic perturbations--is particularly significant due to its strong impact and controllability, especially for reactor-scale devices like ITER where conventional momentum injection method becomes less effective. However, traditional first-principle NTV modeling is computationally expensive, as it requires solving the drift kinetic equation (DKE) in high-dimensional phase space, therefore precluding any real-time applications such as active control or nonlinear integrated modeling of tokamak plasma. Although surrogate solver shows promising ability for accelerating scientific computations, obtaining the data required to train such model is still very challenging. In this work, we present a novel, data-free approach for developing fast surrogate solver of DKE, by training neural network solely based on physical constraints. Such physical constraints are implemented in two ways: First, the loss function is defined based on physical governing equations; Second, the boundary condition is hard-coded into the predicting model. The proposed model is validated against the dataset generated by first-principle numerical solver, which is found to achieve accurate DKE solution with significantly reduced time consuming. In particular, physics-driven surrogate shows higher physical consistency than data-driven surrogate. In general, our study provides a new idea for developing surrogate solvers in data-scarce scenarios, and demonstrates the potential of purely physics-driven neural networks to accelerate demanding scientific computations.

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↗

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↗

arXiv2021

MHD analysis on the physical designs of CFETR and HFRC

The China Fusion Engineering Test Reactor (CFETR) and the Huazhong Field Reversed Configuration (HFRC), currently both under intensive physical and engineering designs in China, are the two major projects representative of the low-density steady-state and high-density pulsed pathways to fusion. One of the primary tasks of the physics designs for both CFETR and HFRC is the assessment and analysis of the magnetohydrodynamic (MHD) stability of the proposed design schemes. Comprehensive efforts on the assessment of MHD stability of CFETR and HFRC baseline scenarios have led to preliminary progresses that may further benefit engineering designs.

physics.plasm-ph↗

arXiv2021

Plasma response to resonant magnetic perturbations near rotation zero-crossing in low torque plasmas

Plasma response to resonant magnetic perturbations (RMPs) near the pedestal top is crucial for accessing edge localized modes (ELMs) suppression in tokamaks. Since radial location of rotation zero-crossing plays a key role in determining the threshold for field penetration of RMP, plasma response may be different in low input torque plasmas. In this work, the linear MHD code MARS-F is applied to reveal the dependence of plasma response to RMP on rotation zero-crossing by a scan of rotation profiles based on an EAST equilibrium. It is shown that the plasma response is enhanced when zero-crossing occurs near rational surfaces. The dependence of plasma response on the location of rotation zero-crossing is well fitted by a double Gaussian, indicating two effects in this enhancement. One is induced by rotation screening effect shown as a wide base (with a width around 10-20 krad/s), and the other is related to resistive singular layer effect characterized by a localized peak (with a width around 3-4 krad/s). The width of the peak scales with the resistive singular layer width. The plasma displacement suggests the response is tearing like when zero-crossing is within the singular layer, while it is kink like when zero-crossing is far from the layer. The enhancement of magnetic islands width at the peak is only around a factor of two, when the absolute value of local rotation is not larger than 10-20 krad/s. It is further confirmed in a modeling of plasma response in an EAST ELM suppression discharge. Though there is a zero-crossing in $E\times B$ rotation but not in electron perpendicular rotation, no significant difference in plasma response is obtained using these two rotation profiles. This suggests that the rotation near pedestal top should not be far away from zero but may not be necessary to have zero-crossing for accessing ELM suppression.

physics.plasm-ph↗

arXiv2017

Neoclassical toroidal viscosity torque in tokamak edge pedestal induced by external resonant magnetic perturbation

The characteristic profile and magnitude are predicted in theory for the neoclassical toroidal viscosity (NTV) torque induced by plasma response to the resonant magnetic perturbation (RMP) in a tokamak with an edge pedestal. For a low-$β$ equilibrium, the NTV torque is dominated by the toroidal component with the same dominant toroidal mode number of RMP. The NTV torque profile is found to be localized, whose peak location is determined by profiles of both the equilibrium temperature (pressure) and the plasma response. In general, the peak of NTV torque profile is found to track the pedestal position. The magnitude of NTV torque strongly depends on the $β$ value of pedestal, which suggests a more significant role of NTV torque in higher plasma $β$ regimes. For a fixed plasma $β$, decreasing density hence increasing temperature can also enhance the amplitude of NTV torque due to the reduced collisionality in the $1/ν$ regime. Based on those findings, we identify the tokamak operation regimes where the significance of NTV torque in edge pedestal induced by RMP can approach those from other momentum sources such as the neutral beam injections.

physics.plasm-ph↗

arXiv2016

ELM control with RMP: plasma response models and the role of edge peeling response

Resonant magnetic perturbations (RMP) have extensively been demonstrated as a plausible technique for mitigating or suppressing large edge localized modes (ELMs). Associated with this is a substantial amount of theory and modelling efforts during recent years. Various models describing the plasma response to the RMP fields have been proposed in the literature, and are briefly reviewed in this work. Despite their simplicity, linear response models can provide alternative criteria, than the vacuum field based criteria, for guiding the choice of the coil configurations to achieve the best control of ELMs. The role of the edge peeling response to the RMP fields is illustrated as a key indicator for the ELM mitigation in low collisionality plasmas, in various tokamak devices.

physics.plasm-ph↗

arXiv2013

Toroidal modeling of interaction between resistive wall mode and plasma flow

The non-linear interplay between the resistive wall mode (RWM) and the toroidal plasma flow is numerically investigated in a full toroidal geometry, by simultaneously solving the initial value problems for the n=1 RWM and the n=0 toroidal force balance equation. Here n is the toroidal mode number. The neoclassical toroidal viscous torque is identified as the major momentum sink that brakes the toroidal plasma flow during the non-linear evolution of the RWM. This holds for a mode that is initially either unstable or stable. For an initially stable RWM, the braking of the flow, and hence the eventual growth of the mode, depends critically on the initial perturbation amplitude.

physics.plasm-ph↗