uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Real-time software tools for the performance analysis of the ITER Radial Neutron Camera
Univ Lisbon, Inst Super Tecn, Inst Plasmas & Fusao Nucl, P-1049001 Lisbon, Portugal..
Univ Lisbon, Inst Super Tecn, Inst Plasmas & Fusao Nucl, P-1049001 Lisbon, Portugal..
Univ Lisbon, Inst Super Tecn, Inst Plasmas & Fusao Nucl, P-1049001 Lisbon, Portugal..
Univ Lisbon, Inst Super Tecn, Inst Plasmas & Fusao Nucl, P-1049001 Lisbon, Portugal..
Show others and affiliations
2017 (English)In: Fusion engineering and design, ISSN 0920-3796, E-ISSN 1873-7196, Vol. 123, p. 1001-1005Article in journal (Refereed) Published
Abstract [en]

The Radial Neutron Camera (RNC) diagnostic is a neutron detection system with multiple collimators aiming at characterizing the neutron emission that will be produced by the ITER tokamak. The RNC plays a primary role for basic and advanced plasma control measurements and acts as backup for system machine protection measurements. During the RNC system level design phase the following real-time data processing algorithms were developed to assess RNC data throughput needs and measurement performances: (i) real-time data compression block (ii) real-time calculation of the neutron emissivity radial profile, based on Tikhonov regularization, starting from the line-integrated measurements, the line-of-sight geometry and using the magnetic flux information [1] (iii) real-time calculation of the neutron emissivity profile using a priori trained neural networks, the line-integrated measurements and the magnetic flux information (the best output from different neural networks being evaluated by a figure of merit that maps the neutron emissivity profile to the original line-integrated measurements) [21]. This paper presents results for the processing times of the various algorithms and their minimum control cycle for different conditions, such as number of lines of sight, number of magnetic flux surfaces and measurement error on the line integrated RNC measurements.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE SA , 2017. Vol. 123, p. 1001-1005
Keywords [en]
RNC diagnostic, ITER, Real-time processing, Neutron emissivity, Data compression
National Category
Subatomic Physics
Identifiers
URN: urn:nbn:se:uu:diva-341823DOI: 10.1016/j.fusengdes.2017.02.071ISI: 000418992000210OAI: oai:DiVA.org:uu-341823DiVA, id: diva2:1183058
Conference
29th Symposium on Fusion Technology (SOFT), SEP 05-09, 2016, Prague, CZECH REPUBLIC
Available from: 2018-02-15 Created: 2018-02-15 Last updated: 2018-02-15Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Cecconello, Marco

Search in DiVA

By author/editor
Cecconello, Marco
By organisation
Applied Nuclear Physics
In the same journal
Fusion engineering and design
Subatomic Physics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 10 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf