Abstract Details
Abstracts
Author: Xishuo Wei
Requested Type: Poster
Submitted: 2023-04-01 13:29:36
Co-authors: Shuying Sun, William Tang, Zhihong Lin, Hongfei Du, Ge Dong
Contact Info:
UC Irvine
4170 Frederick Reines Hall
Irvine, CA 92697
United States
Abstract Text:
The motional Stark effect (MSE) diagnostic has been a standard measurement for the magnetic field line pitch angle in tokamaks that are equipped with neutral beams. However, the MSE data are not always available due to experimental constraints, especially in future devices without neutral beams. Here we develop a deep-learning based model (SGTC-QR) that can reconstruct the safety factor profile without the MSE diagnostic to mimic the traditional equilibrium reconstruction with the MSE constraint. The model demonstrates promising performance, and the sub-millisecond inference time is compatible with the real-time plasma control system.
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