Current Research into Applications of Tomography for Fusion Diagnostics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61389021%3A_____%2F19%3A00522775" target="_blank" >RIV/61389021:_____/19:00522775 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007%2Fs10894-018-0178-x" target="_blank" >https://link.springer.com/article/10.1007%2Fs10894-018-0178-x</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10894-018-0178-x" target="_blank" >10.1007/s10894-018-0178-x</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Current Research into Applications of Tomography for Fusion Diagnostics

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Current Research into Applications of Tomography for Fusion Diagnostics

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10305 - Fluids and plasma physics (including surface physics)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Fusion Energy

ISSN

0164-0313

e-ISSN

—

Svazek periodika

38

Číslo periodika v rámci svazku

3-4

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

13

Strana od-do

458-466

Kód UT WoS článku

000476509600015

EID výsledku v databázi Scopus

2-s2.0-85052635509