The IFMIF-DONES Diagnostics and Control Systems: Current Design Status, Integration Issues and Future Perspectives Embedding Artificial Intelligence Tools

被引:0
作者
Cappelli, M. [1 ]
Torregrosa-Martin, C. [2 ]
Diaz, J. [3 ]
Ibarra, A. [2 ]
机构
[1] ENEA, Frascati Res Ctr, Frascati, Italy
[2] Consorcio IFMIF DONES Espana, Granada, Spain
[3] Univ Granada, Granada, Spain
关键词
Control systems; AI; IFMIF-DONES; Diagnostics; I&C;
D O I
10.1007/s10894-024-00414-x
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
As an integral part of the European strategy for advancing fusion-generated electricity, IFMIF-DONES represents a high-intensity neutron irradiation plant with the main purpose of assessing the suitability of materials for fusion reactor applications. Its primary mission is to examine how materials respond to irradiation within a neutron flux that mimics the conditions expected in the first wall of the proposed DEMO reactor, which is intended to succeed ITER. Consequently, IFMIF-DONES, whose construction is slated to commence shortly, plays a pivotal role in aiding the development, approval, and safe operation of DEMO, as well as future fusion power plants. This paper provides a quick overview of the current development of the IFMIF-DONES neutron source with a particular snapshot of the present engineering design status for what concerns the instrumentation and control systems together with its complex diagnostics, that guarantees the safe monitoring, supervision and regulation of all operations. The current status of design, after the completion of the preliminary design phase is presented, as well as the existing and future plans for their integration also using some of the new capabilities offered by Artificial Intelligence tools.
引用
收藏
页数:12
相关论文
共 42 条
  • [1] Machine learning for beam dynamics studies at the CERN Large Hadron Collider
    Arpaia, P.
    Azzopardi, G.
    Blanc, F.
    Bregliozzi, G.
    Buffat, X.
    Coyle, L.
    Fol, E.
    Giordano, F.
    Giovannozzi, M.
    Pieloni, T.
    Prevete, R.
    Redaelli, S.
    Salvachua, B.
    Salvant, B.
    Schenk, M.
    Camillocci, M. Solfaroli
    Tomas, R.
    Valentino, G.
    Van der Veken, F. F.
    Wenninger, J.
    [J]. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2021, 985
  • [2] Cappelli M., 2019, Proceedings of ICALEPCS2019
  • [3] Cappelli M., 2023, Instrumentation and Control Systems for Nuclear Power Plants
  • [4] Recent advances of the IFMIF-DONES central instrumentation and control systems engineering design
    Cappelli, Mauro
    Ambi, Francesca
    Bagnasco, Andrea
    Botta, Enrico
    Chen, Zhe
    Diaz, Javier
    Gutierrez, Victor
    Goryl, Piotr
    Sousa, Jorge
    Ibarra, Angel
    [J]. FUSION ENGINEERING AND DESIGN, 2023, 194
  • [5] Status of the engineering design of the IFMIF-DONES Central Instrumentation and Control Systems
    Cappelli, Mauro
    Bagnasco, Andrea
    Diaz, Javier
    Sousa, Jorge
    Ambi, Francesca
    Campedrer, Alessio
    Liuzza, Davide
    Carvalho, Bernardo
    Ibarra, Angel
    [J]. FUSION ENGINEERING AND DESIGN, 2021, 170
  • [6] IFMIF-DONES Central instrumentation and control systems: General overview
    Cappelli, Mauro
    Centioli, Cristina
    Neri, Carlo
    Monti, Chiara
    Ibarra, Angel
    [J]. FUSION ENGINEERING AND DESIGN, 2019, 146 : 2682 - 2686
  • [7] Donne T., 2018, eurofusion programme management unit
  • [8] Neural Networks for Modeling and Control of Particle Accelerators
    Edelen, A. L.
    Biedron, S. G.
    Chase, B. E.
    Edstrom, D., Jr.
    Milton, S. V.
    Stabile, P.
    [J]. IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 2016, 63 (02) : 878 - 897
  • [9] Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems
    Edelen, Auralee
    Neveu, Nicole
    Frey, Matthias
    Huber, Yannick
    Mayes, Christopher
    Adelmann, Andreas
    [J]. PHYSICAL REVIEW ACCELERATORS AND BEAMS, 2020, 23 (04)
  • [10] Ehrlich K., 1994, KfK Report 5296