Improved scaling of the scrape-off layer particle flux width by the Bayes theorem on EAST
D. C. Liu, X. Liu, L. Wang, X. F. Zheng

TL;DR
This paper introduces a Bayesian MAP estimation method to more accurately determine the scrape-off layer particle flux width on EAST, leading to improved scalings and insights into plasma behavior relevant for fusion devices like ITER.
Contribution
The study develops a Bayesian MAP approach for estimating SOL flux width, improving accuracy and updating scalings for different plasma conditions on EAST.
Findings
MAP method improves fit accuracy by ~30% over traditional methods.
Revised scalings show dependence on connection length and differences between helium and deuterium.
Extrapolated flux widths are ~6 mm for ITER L-mode and ~13 mm for H-mode.
Abstract
The scaling of scrape-off layer (SOL) power width ({\lambda}q) is essential for advancing the understanding of particle and heat transport in the SOL. Due to the sparse layout of divertor Langmuir probes (Div-LPs) and probe erosion during long-pulse, high-performance operations on EAST, estimating SOL particle flux width ({\lambda}js, used to approximate {\lambda}q) from the ion saturation current density profile (js) often incurs substantial uncertainty. This study presents a maximum a posteriori (MAP) estimation method based on Bayes' theorem, achieving approximately 30% improvement in fitting accuracy over traditional ordinary least squares. Using this method and the FreeGS equilibrium code, we updated databases from Liu et al., Nucl. Fusion 64 (2024). Revised {\lambda}js scalings for L-mode and H-mode in deuterium and helium plasmas demonstrate better regression quality and slightly…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTextile materials and evaluations
