Calibration of neutron detectors at ASDEX Upgrade, measurement and model
Introduction
Research fusion facilities mostly operate with deuterium (D-D) fuel which produces neutrons of 2.45 MeV energy. In neutral beam injection (NBI) heated discharges, the fast ions reacting with the bulk plasma (beam-target reactions) dominate the neutron rate (NR). Thus, the NR is an imprint of the fast particles, which can drive instabilities and damage the plasma facing components (PFC) [1], [2]. Accurate neutron measurements and a reasonable agreement between experiment and theoretical calculations are therefore essential to understanding the fast ion dynamics.
Over the course of NR investigations at ASDEX Upgrade (AUG), comparisons between the experimental and the NR predicted by the TRANSP code [3] show systematic deviations between calibration campaigns, which may point to potential calibration errors in the neutron detectors. The calibration has been found accurate to about 40 [2]. In comparison, the statistical uncertainty in 1 ms binning, which is roughly 4, and could be minimized with the choice of binning, is negligible. The usual way to calibrate involved the probing of a few discrete source positions inside the machine which did not have high statistics and were hard to reproduce precisely over the years. This has prompted us to carry out an ab initio absolute calibration with more reproducible geometry, better count statistics and the utilization of a comprehensive Monte Carlo simulation [4], [5], [6] for neutron transport and detection using the Serpent code [7].
Section snippets
Calibration set-up for neutron measurements at AUG
Complex geometries like tokamaks and stellarators are organized in sectors and consist of various materials and components. Moreover, plasma heating systems and diagnostics add up to the packed surrounding in the reactor hall. This plays a significant role in neutron measurements mainly due to the strong scattering of neutrons. Further, neutron interactions depend on material composition and thickness. To capture these effects, a toy train carrying a radioactive source (Pu/B) was
Simulation of the n-rate in AUG with the Serpent code
Neutron transport models rely on statistical methods that track the particle paths and calculate probabilities for numerous events. Monte Carlo transport codes are one example of such approach that simulates histories of particles traversing modelled geometries.
The most convenient way to incorporate a detailed ASDEX Upgrade model inside Serpent is using stereolithography (STL) files. For that purpose the whole machine was decomposed into smaller parts using the CAD software CATIA [9] and
Comparison between measurement and Serpent simulation
In this section we present the results from three calibration measurements - two inside the vacuum vessel and one outside. Measurements with the toy train were carried out for a total of one weekend (one day one radial position). The recorded data acquisition exceeds 130k seconds. The smoothed neutron rate from the outer railway track for 5000 s and the corresponding average NR are shown in Fig. 4.
The average period of a full toroidal turn is 280 s. The displayed background noise is roughly
Summary and conclusions
Three sets of calibration measurements of the He thermal neutron detector were performed at ASDEX Upgrade and simulated using the Monte Carlo transport code Serpent. A detailed geometry of AUG was decomposed, converted to STL files and implemented in the code. Comparisons between the experimental NR and the simulation outside the vacuum vessel resulted in a varying factor (between 5 and 15) with respect to the radial source position. The paper proves that the difference likely depends on the
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training program 2014–2018 and 2019–2020 under grant agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission.
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