Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
We present a novel technique of neutron noise detection and experimental data interpretation developed during the EU H2020 project CORTEX aiming to improve the capabilities for identification and localization of neutron noise sources. The experimental data analysis is performed in the frequency domain by extracting the spectral power density and the phase angle using a novel spectral variance reduction technique based on per cycle based bootstrapping with replacement. This technique allows for variance reduction of measured spectral power and phase angle not only at base frequency but at higher harmonic frequency contributions as well. This allows for a more representative treatment of experimental data and validation of codes for neutron noise propagation, some of which have been developed within the project. The detector response is not necessarily linearly dependent on the oscillator movement, and the study of non-linear terms provides additional information which can improve the accuracy of neutron noise source identification and localization. Moreover those terms can be used in a Taylor series to identify a more complex dependence. The process is simplified in the sense, that these contributions are linearized in the frequency domain as higher harmonic frequency contributions and can be easily identified and extracted due to spectral peaks prominence provided by the bootstrapping with replacement method. Combined with the spectral power and phase, we present a preliminary investigation of usability of higher order terms for noise source identification and localization. In this paper, we outline the CORTEX project, the experiments and the measurement analysis methodology based on the bootstrapping with replacement along with the initial developments on the study of non-linear terms in CROCUS reactor, using several different noise source configurations at a set frequency.
Majed Chergui, Thomas Charles Henry Rossi, Malte Oppermann, Lijie Wang