The ASCOT Fusion Source Integrator (AFSI) has been used to calculate neutron production rates and spectra corresponding to the JET 19-channel neutron camera (KN3) and the time-of-flight spectrometer (TOFOR) as ideal diagnostics, without detector-related effects. AFSI calculates fusion product distributions in 4D, based on Monte Carlo integration from arbitrary reactant distribution functions. The distribution functions were calculated by the ASCOT Monte Carlo particle orbit following code for thermal, NBI and ICRH particle reactions. Fusion cross-sections were defined based on the Bosch-Hale model and both DD and DT reactions have been included.Neutrons generated by AFSI-ASCOT simulations have already been applied as a neutron source of the Serpent neutron transport code in ITER studies. Additionally, AFSI has been selected to be a main tool as the fusion product generator in the complete analysis calculation chain: ASCOT AFSI - SERPENT (neutron and gamma transport Monte Carlo code) - APROS (system and power plant modelling code), which encompasses the plasma as an energy source, heat deposition in plant structures as well as cooling and balance-of-plant in DEMO applications and other reactor relevant analyses.This conference paper presents the first results and validation of the AFSI DD fusion model for different auxiliary heating scenarios (NBI, ICRH) with very different fast particle distribution functions. Both calculated quantities (production rates and spectra) have been compared with experimental data from KN3 and synthetic spectrometer data from ControlRoom code. No unexplained differences have been observed. In future work, AFSI will be extended for synthetic gamma diagnostics and additionally, AFSI will be used as part of the neutron transport calculation chain to model real diagnostics instead of ideal synthetic diagnostics for quantitative benchmarking.

Synthetic neutron camera and spectrometer in JET based on AFSI-ASCOT simulations / Sirén, P.; Varje, J.; Weisen, H.; Koskela, T.; Subba, F.; Contributors, Jet. - In: JOURNAL OF INSTRUMENTATION. - ISSN 1748-0221. - 12:09(2017). [10.1088/1748-0221/12/09/c09010]

Synthetic neutron camera and spectrometer in JET based on AFSI-ASCOT simulations

Subba, F.;
2017

Abstract

The ASCOT Fusion Source Integrator (AFSI) has been used to calculate neutron production rates and spectra corresponding to the JET 19-channel neutron camera (KN3) and the time-of-flight spectrometer (TOFOR) as ideal diagnostics, without detector-related effects. AFSI calculates fusion product distributions in 4D, based on Monte Carlo integration from arbitrary reactant distribution functions. The distribution functions were calculated by the ASCOT Monte Carlo particle orbit following code for thermal, NBI and ICRH particle reactions. Fusion cross-sections were defined based on the Bosch-Hale model and both DD and DT reactions have been included.Neutrons generated by AFSI-ASCOT simulations have already been applied as a neutron source of the Serpent neutron transport code in ITER studies. Additionally, AFSI has been selected to be a main tool as the fusion product generator in the complete analysis calculation chain: ASCOT AFSI - SERPENT (neutron and gamma transport Monte Carlo code) - APROS (system and power plant modelling code), which encompasses the plasma as an energy source, heat deposition in plant structures as well as cooling and balance-of-plant in DEMO applications and other reactor relevant analyses.This conference paper presents the first results and validation of the AFSI DD fusion model for different auxiliary heating scenarios (NBI, ICRH) with very different fast particle distribution functions. Both calculated quantities (production rates and spectra) have been compared with experimental data from KN3 and synthetic spectrometer data from ControlRoom code. No unexplained differences have been observed. In future work, AFSI will be extended for synthetic gamma diagnostics and additionally, AFSI will be used as part of the neutron transport calculation chain to model real diagnostics instead of ideal synthetic diagnostics for quantitative benchmarking.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2986904