Plasma Confinement State Classification in Fusion Power Plants: Profile Reflectometer and Ensemble Diagnostics

Fuente: arXiv

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Bibliographic Details
Main Authors:	Clark, Randall, Glukhov, Vacslav, Subbotin, Georgy, Nurgaliev, Maxim, Kachkin, Aleksandr, Zeng, Lei, Orlov, Dmitri M.
Format:	Preprint
Published:	2026
Subjects:	Plasma Physics
Online Access:	Acceder al recurso
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_version_	1866908807878148096
author	Clark, Randall Glukhov, Vacslav Subbotin, Georgy Nurgaliev, Maxim Kachkin, Aleksandr Zeng, Lei Orlov, Dmitri M.
author_facet	Clark, Randall Glukhov, Vacslav Subbotin, Georgy Nurgaliev, Maxim Kachkin, Aleksandr Zeng, Lei Orlov, Dmitri M.
contents	As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97\% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99\% test accuracy.
format	Preprint
id	arxiv_https___arxiv_org_abs_2602_02812
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	Plasma Confinement State Classification in Fusion Power Plants: Profile Reflectometer and Ensemble Diagnostics Clark, Randall Glukhov, Vacslav Subbotin, Georgy Nurgaliev, Maxim Kachkin, Aleksandr Zeng, Lei Orlov, Dmitri M. Plasma Physics As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97\% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99\% test accuracy.
title	Plasma Confinement State Classification in Fusion Power Plants: Profile Reflectometer and Ensemble Diagnostics
topic	Plasma Physics
url	https://arxiv.org/abs/2602.02812