A neural network-based method for input parameter optimization of edge transport modeling utilizing experimental diagnostics

A neural network-based method for input parameter optimization of edge transport modeling utilizing experimental diagnostics

A neural network-based method is developed to fast optimize EMC3-EIRENE input parameters, enabling EMC3-EIRENE to produce synthetic data that closely match experimental measurements on Wendelstein 7-X. Initially, an EMC3-EIRENE simulation database covering a range of key input parameters is generate...

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Bibliographic Details
Main Authors: Y. Luo, S. Xu, Y. Liang, E. Wang, J. Cai, Y. Feng, D. Reiter, A. Knieps, S. Brezinsek, D. Harting, M. Krychowiak, D. Gradic, P. Ren, D. Zhang, Y. Gao, G. Fuchert, A. Pandey, M. Jakubowski, the W7-X Team
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Nuclear Fusion
Subjects:
machine learning
Bayesian inference
EMC3-EIRENE
Wendelstein 7-X
Online Access:https://doi.org/10.1088/1741-4326/adf75f
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https://doi.org/10.1088/1741-4326/adf75f

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