6 papers
SafeDivertor: Faithful Divertor Heat Flux Reconstruction from Macroscopic Plasma State Signals via Time-Frequency Prior Exploitation
Hao Si, Zehua Chen, Qingquan Yang +8
Divertor heat-flux analysis is essential for understanding plasma-wall interactions and protecting plasma-facing components in magnetic-confinement fusion devices, while convention…
Visible-Light Imaging Diagnosis of Neutral Particle Emission Tomography in the Tokamak Divertor: An Efficient Transformer-based Surrogate Model
Xiao Wang, Hao Si, Qiang Chen +8
Nuclear fusion has made significant progress in recent years and is expected to become one of the most important pathways to addressing global energy challenges. This paper focuses…
Hierarchical Multi-to-Single-Modal Knowledge Distillation for Disruption Prediction in EAST
Qiang Chen, Xiao Wang, Hao Si +9
Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible images provide complementary…
HGTS-Former: Hierarchical HyperGraph Transformer for Multivariate Time Series Analysis
Hao Si, Xiao Wang, Fan Zhang +5
Multivariate time series analysis has long been one of the key research topics in the field of artificial intelligence. However, analyzing complex time series data remains a challe…
NESTOR: A Nested MOE-based Neural Operator for Large-Scale PDE Pre-Training
Dengdi Sun, Xiaoya Zhou, Xiao Wang +4
Neural operators have emerged as an efficient paradigm for solving PDEs, overcoming the limitations of traditional numerical methods and significantly improving computational effic…
Revisiting Heat Flux Analysis of Tungsten Monoblock Divertor on EAST using Physics-Informed Neural Network
Xiao Wang, Zikang Yan, Hao Si +5
Estimating heat flux in the nuclear fusion device EAST is a critically important task. Traditional scientific computing methods typically model this process using the Finite Elemen…