Retrieving spatial distribution of plasma emissivity from line integrated measurements on tokamaks presents a challenging task due to ill-posedness of the tomography problem and limited number of the lines of sight. Modern methods of plasma tomography therefore implement a-priori information as well as constraints, in particular some form of penalisation of complexity. In this contribution, the current tomography methods under development (Tikhonov regularisation, Bayesian methods and neural networks) are briefly explained taking into account their potential for integration into the fusion reactor diagnostics. In particular, current development of the Minimum Fisher Regularisation method is exemplified with respect to real-time reconstruction capability, combination with spectral unfolding and other prospective tasks.

Current Research into Applications of Tomography for Fusion Diagnostics / Mlynar, Jan; Craciunescu, Teddy; Ferreira, Diogo R.; Carvalho, Pedro; Ficker, Ondrej; Grover, Ondrej; Imrisek, Martin; Svoboda, Jakub; Subba, F.. - In: JOURNAL OF FUSION ENERGY. - ISSN 0164-0313. - 38:3-4(2018), pp. 458-466. [10.1007/s10894-018-0178-x]

Current Research into Applications of Tomography for Fusion Diagnostics

Subba, F.
2018

Abstract

Retrieving spatial distribution of plasma emissivity from line integrated measurements on tokamaks presents a challenging task due to ill-posedness of the tomography problem and limited number of the lines of sight. Modern methods of plasma tomography therefore implement a-priori information as well as constraints, in particular some form of penalisation of complexity. In this contribution, the current tomography methods under development (Tikhonov regularisation, Bayesian methods and neural networks) are briefly explained taking into account their potential for integration into the fusion reactor diagnostics. In particular, current development of the Minimum Fisher Regularisation method is exemplified with respect to real-time reconstruction capability, combination with spectral unfolding and other prospective tasks.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2986794