18 citations · 21 across the 6 of their papers we have counts for
6 papers
Extraction of n = 0 pick-up by locked mode detectors based on neural networks in J-TEXT
Chengshuo Shen, Jianchao Li, Yonghua Ding +10
Measurement of locked mode (LM) is important for the physical research of Magnetohydrodynamic (MHD) instabilities and plasma disruption. The n = 0 pick-up need to be extracted and…
A weighted matching scheme of magnetic coil design for FRC shaping control
Zitong Qu, Ping Zhu, Zhipeng Chen +2
The two-dimentional (2D) separatrix shaping plays a crucial role in the confinement of the Field Reversed Configuration (FRC), and the magnetic coils serve as an effective means fo…
Don't Make Your LLM an Evaluation Benchmark Cheater
Kun Zhou, Yutao Zhu, Zhipeng Chen +6
Large language models~(LLMs) have greatly advanced the frontiers of artificial intelligence, attaining remarkable improvement in model capacity. To assess the model performance, a…
Electrical Characteristics of the GEC Reference Cell with Impedance Matching: A Two-Dimensional PIC/MCC Modeling Study
Zili Chen, Hongyu Wang, Shimin Yu +5
In this paper, the electrical characteristics of the Gaseous Electronics Conference (GEC) reference cell with impedance matching are investigated through a two-dimensional electros…
Critical roles of edge turbulent transport in the formation of high-field-side high-density front and density limit disruption in J-TEXT tokamak
Peng Shi, Yuhan Wang, Li Gao +16
This article presents an in-depth study of the sequence of events leading to density limit disruption in J-TEXT tokamak plasmas, with an emphasis on boudary turbulent transport and…
Transferable Cross-Tokamak Disruption Prediction with Deep Hybrid Neural Network Feature Extractor
Wei Zheng, Fengming Xue, Ming Zhang +12
Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption disc…