Bayesian Inference of Equilibrium Magnetic Field Geometry on the MAST Experiment

Autor:	G. von Nessi
Rok vydání:	2011
Předmět:	Physics Nuclear and High Energy Physics Tokamak Bayesian probability Physical system Inference Plasma Condensed Matter Physics Bayesian inference law.invention Magnetic field Physics::Plasma Physics law Plasma diagnostics Statistical physics
Zdroj:	IEEE Transactions on Plasma Science. 39:3004-3005
ISSN:	1939-9375 0093-3813
DOI:	10.1109/tps.2011.2162967
Popis:	Inference of plasma equilibrium geometry in tokamak fusion plasmas constitutes a challenging inference problem, given intrinsic difficulties surrounding the making of direct measurements in such physical systems. Traditionally, this problem has been handled by codes that attempt to reconcile solutions of the Grad-Shafranov (GS) equation with external magnetic diagnostics. Due to this inference being an intrinsically ill-posed problem, these codes suffer from numerical difficulties that require experiment-specific algorithms to handle. Here, we present a method to directly infer plasma equilibrium structure based on Bayesian analysis, which does not require solving the GS equation nor the use of any experiment-specific numerics.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cfbfe161aa81d22824dfe444619ad24d https://doi.org/10.1109/tps.2011.2162967 Zobrazit plný text záznamu