arXiv subjects

Jinlin Xie

Publications and source records attributed to Jinlin Xie.

6 recordsLinked to original sources

arXiv2026

First Observation of Fishbone-Driven Zonal Flows with Fine Reversed Structure in Tokamak Plasmas

We present the first direct experimental observation of fishbone-driven zonal flows in the core of the EAST tokamak. In contrast to the global pattern predicted by previous models and simulations based on the energetic-particle-expulsion mechanism, the observed flows exhibit a fine-scale, radially reversed structure inside the q = 1 rational surface. The flow rises faster and saturates earlier than the fishbone within a single burst, indicating that a beat-driven nonlinear process dominates the early stage rather than the energetic-particle-expulsion mechanism. Global nonlinear gyrokinetic simulations quantitatively reproduce the observed radial profile and reveal that this structure arises from the cancellation of comparable but opposite contributions from thermal ions and electrons. This cancellation mechanism is not captured in previous theoretical frameworks. These findings establish that the fishbone can generate sheared flows with a distinct radial topology, offering a promising pathway for regulating turbulence and improving core confinement.

physics.plasm-ph↗

arXiv2026

A programmable stellarator-tokamak hybrid for million-scale magnetic-configuration discovery

Tokamaks and stellarators are the leading magnetic-confinement concepts for fusion, but they rely on complementary design principles. Tokamaks use simple axisymmetric coils and plasma current, whereas stellarators use externally generated three-dimensional fields for steady-state operation. Here, we propose a programmable stellarator--tokamak hybrid that uses a fixed set of simple planar coils to access a broad magnetic-configuration space. The device adds 288 dipole-field coils to a tokamak-like coil set, with only six independent coil geometries required by symmetry. By programming coil currents, the same hardware generates more than 1.66 million optimized stellarator configurations spanning quasi-axisymmetry, quasi-helical symmetry, and quasi-isodynamicity, as well as tokamak-relevant three-dimensional perturbations. Representative configurations exhibit nested magnetic surfaces, low neoclassical transport, and favorable energetic-particle confinement. This approach enables rapid magnetic-configuration discovery without hardware redesign.

physics.plasm-ph↗

arXiv2024

Attention-aware convolutional neural networks for identification of magnetic islands in the tearing mode on EAST tokamak

The tearing mode, a large-scale MHD instability in tokamak, typically disrupts the equilibrium magnetic surfaces, leads to the formation of magnetic islands, and reduces core electron temperature and density, thus resulting in significant energy losses and may even cause discharge termination. This process is unacceptable for ITER. Therefore, the accurate identification of a magnetic island in real time is crucial for the effective control of the tearing mode in ITER in the future. In this study, based on the characteristics induced by tearing modes, an attention-aware convolutional neural network (AM-CNN) is proposed to identify the presence of magnetic islands in tearing mode discharge utilizing the data from ECE diagnostics in the EAST tokamak. A total of 11 ECE channels covering the range of core is used in the tearing mode dataset, which includes 2.5*10^9 data collected from 68 shots from 2016 to 2021 years. We split the dataset into training, validation, and test sets (66.5%, 5.7%, and 27.8%), respectively. An attention mechanism is designed to couple with the convolutional neural networks to improve the capability of feature extraction of signals. During the model training process, we utilized adaptive learning rate adjustment and early stopping mechanisms to optimize performance of AM-CNN. The model results show that a classification accuracy of 91.96% is achieved in tearing mode identification. Compared to CNN without AM, the attention-aware convolutional neural networks demonstrate great performance across accuracy, recall metrics, and F1 score. By leveraging the deep learning model, which incorporates a physical understanding of the tearing process to identify tearing mode behaviors, the combination of physical mechanisms and deep learning is emphasized, significantly laying an important foundation for the future intelligent control of tearing mode dynamics.

physics.plasm-ph↗

arXiv2024

Effects of Magnetic Helicity on 3D Equilibria and Self-Organized States in KTX Reversed Field Pinch

The RFP is a toroidal magnetic configuration in which plasmas can spontaneously transform into different self-organized states. Among various states, the QSH state has a dominant component for the magnetic field and significantly improves confinement. Many theoretical and experimental efforts have investigated the transitions among different states. This paper employs the MRxMHD model to study the properties of QSH and other states. The SPEC is used to compute MHD equilibria for the KTX. The toroidal volume of KTX is partitioned into two subvolumes by an internal transport barrier. The geometry of this barrier is adjusted to achieve force balance across the interface, ensuring that the plasma in each subvolume is force-free and that magnetic helicity is conserved. By varying the parameters, we generate distinct self-organized states in KTX. Our findings highlight the crucial role of magnetic helicity in shaping these states. In states with low magnetic helicity in both subvolumes, the plasma exhibits axisymmetric behavior. With increasing core helicity, the plasma gradually transforms from an axisymmetric state to a double-axis helical state and finally to a single-helical-axis state. Elevated core magnetic helicity leads to a more pronounced dominant mode of the boundary magnetic field and a reduced core magnetic shear. This is consistent with previous experimental and numerical results in other RFP devices. We find a linear relationship between the plasma current and helicity in different self-organized states. Our findings suggest that KTX may enter the QSH state when the toroidal current reaches 0.72 MA. This study demonstrates that the stellarator equilibrium code SPEC unveils crucial RFP equilibrium properties, rendering it applicable to a broad range of RFP devices and other toroidal configurations.

physics.plasm-ph↗

arXiv2020

The theoretical study on intermittency and propagation of geodesic acoustic mode in L- mode discharge near tokamak edge

Through a systematically developed theory, we demonstrate that the motion of instanton identified in [Y. Z. Zhang, Z. Y. Liu, T. Xie, S. M. Mahajan, and J. Liu, Physics of Plasmas 24, 122304 (2017)] is highly correlated to the intermittent excitation and propagation of geodesic acoustic mode (GAM) that are observed in tokamaks. While many numerical simulations have observed the phenomena, it is the first theory that reveals the physical mechanism behind GAM intermittent excitation and propagation. The preceding work is based on the micro-turbulence associated with toroidal ion temperature gradient (ITG) mode, and slab-based phenomenological model of zonal flow. When full toroidal effect are introduced into the system, two branches of zonal flow emerge: the torus-modified low frequency zonal flow (TLFZF), and GAM, necessitating a unified exploration of GAM and TLFZF. Indeed, we observe that the transition (decay) from the caviton to instanton is triggered by a rapid zero-crossing of radial group velocity of drift wave and is found to be strongly correlated with the GAM onset. Many features peculiar to intermittent GAMs, observed in real machines, are thus identified in the numerical experiment. The results will be displayed in figures and in a movie; first for single central rational surface, and then with coupled multiple central rational surfaces. The periodic bursting first shown disappears as being replaced by irregular one, more similar to the intermittent characteristics observed in GAM experiments.

physics.plasm-ph↗

arXiv2018

Two-fluid MHD Regime of Resistive Drift-Wave Instability

Drift instabilities contribute to the formation of edge turbulence and zonal flows, and thus the anomalous transport in tokamaks. Experiments often found micro-scale tur- bulence strongly coupled with large-scale magnetohydrodynamic (MHD) processes, whereas a general framework has been lacking that can cover both regimes, in partic- ular, their coupling. In this paper, the linear resistive drift wave instability (DWI) is investigated using a full 2-fluid MHD model, as well as its numerical implementation in NIMROD code. Both analytical and numerical analyses reveal a macro-scale global drift wave eigenmode coupled with MHD dynamics and illustrate a non-monotonic dispersion relation with respect to both perpendicular and parallel wavenumbers. NIMROD results also reveal an edge-localized behavior in the radial mode structure as the azimuthal mode number increases, implying the dependence of the 2-fluid ef- fects due to the inhomogeneous density profile. The edge-localization introduces a non-trivial dependence of the effective perpendicular wavenumber to the perpendicular mode number, which may explain the quantitative difference between the global dispersion relation and its local approximation from the conventional local theory.

physics.plasm-ph↗