30 citations · 86 across the 7 of their papers we have counts for
7 papers · 1 filter
Plasma GraphRAG: Physics-Grounded Parameter Selection for Gyrokinetic Simulations
Ruichen Zhang, Feda AlMuhisen, Chenguang Wan +6
Accurate parameter selection is fundamental to gyrokinetic plasma simulations, yet current practices rely heavily on manual literature reviews, leading to inefficiencies and incons…
Reconstructing High-fidelity Plasma Turbulence with Data-driven Tuning of Diffusion in Low Resolution Grids
Kunpeng Li, Youngwoo Cho, Xavier Garbet +6
Developing physically consistent closure models is a longstanding challenge in simulating plasma turbulence, even in minimal systems such as the two-field Hasegawa-Wakatani (HW) mo…
A high-fidelity surrogate model for the ion temperature gradient (ITG) instability using a small expensive simulation dataset
Chenguang Wan, Youngwoo Cho, Zhisong Qu +7
One of the main challenges in building high-fidelity surrogate models of tokamak turbulence is the substantial demand for high-quality data. Typically, producing high-quality data…
A machine-learning-based tool for last closed-flux surface reconstruction on tokamaks
Chenguang Wan, Zhi Yu, Alessandro Pau +2
Nuclear fusion represents one of the best alternatives for a sustainable source of clean energy. Tokamaks allow to confine fusion plasma with magnetic fields and one of the main ch…
A data management system for machine learning research of tokamak
Chenguang Wan, Zhi Yu, Xiaojuan Liu +3
In recent years, machine learning (ML) research methods have received increasing attention in the tokamak community. The conventional database (i.e., MDSplus for tokamak) of experi…
EAST discharge prediction without integrating simulation results
Chenguang Wan, Zhi Yu, Alessandro Pau +2
In this work, a purely data-driven discharge prediction model was developed and tested without integrating any data or results from simulations. The model was developed based on th…
Experiment data-driven modeling of tokamak discharge in EAST
Chenguang Wan, Jiangang Li, Zhi Yu +1
A model for tokamak discharge through deep learning has been done on a superconducting long-pulse tokamak (EAST). This model can use the control signals (i.e. Neutral Beam Injectio…