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conference paper

Neutron noise experiments in the AKR-2 and CROCUS reactors for the European project CORTEX

Lamirand, Vincent  
•
Rais, Adolfo  
•
Huebner, Sebastian
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January 1, 2020
Advancements In Nuclear Instrumentation Measurement Methods And Their Applications (Animma 2019)
6th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications (ANIMMA)

The present article gives an overview of the first experimental campaigns carried out in the AKR-2 and CROCUS reactors within the framework of the Horizon 2020 European project CORTEX. CORTEX aims at developing innovative core monitoring techniques that allow detecting anomalies in nuclear reactors, e.g. excessive vibrations of core internals. The technique will be mainly based on using the fluctuations in neutron flux, i.e. noise analysis. The project will result in a deepened understanding of the physical processes involved. This will allow utilities to detect operational problems at a very early stage, and to take proper actions before such problems have any adverse effect on plant safety and reliability. The purpose of the experimental campaigns in the AKR-2 and CROCUS reactors is to produce noise-specific experimental data for the validation of the neutron noise computational models developed within this framework. The first campaigns at both facilities consisted in measurements at reference static states, and with the addition of mechanical perturbations. In the AKR-2 reactor, perturbations were induced by two devices: a rotating absorber and a vibrating absorber, both sets in experimental channels close to the core. In CROCUS, the project benefited from the COLIBRI experimental program: 18 periphery fuel rods were oscillated at a maximum of +/- 2 mm around their central position in the Hz range. The present article documents the experimental setups and measurements for each facility and perturbation type.

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epjconf_animma2019_04023.pdf

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http://purl.org/coar/version/c_970fb48d4fbd8a85

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openaccess

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CC BY

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1.77 MB

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80dc4d953de6ff9cab0935ce9421b3d7

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