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  (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) . 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.
All Science Journal Classification (ASJC) codes
- Nuclear Energy and Engineering
- Materials Science(all)
- Civil and Structural Engineering
- Mechanical Engineering
Cruz, N., Pereira, R. C., Santos, B., Fernandes, A., Sousa, J., Marocco, D., Riva, M., Centioli, C., Cecconello, M., Correia, C. M. B., Gonçalves, B., & Esposito, B. (2017). Real-time software tools for the performance analysis of the ITER Radial Neutron Camera. Fusion Engineering and Design, 123, 1001 - 1005. https://doi.org/10.1016/j.fusengdes.2017.02.071