10.5281/zenodo.4438588
https://zenodo.org/records/4438588
oai:zenodo.org:4438588
A. Durrant
A. Durrant
University of Aberdeen / University of Lincoln
Detection and localisation of multiple in-core perturbations with neutron noise-based self-supervised domain adaptation
Zenodo
2021
2021-01-13
eng
Presentation
10.5281/zenodo.4438587
https://zenodo.org/communities/cortex
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
Problem Case
• We aim to unfold reactor transfer function to provide core diagnostics.
• Derivation of core perturbation characteristics to classify and locate its origin.
• Yet this is challenging due to the limited number of neutron detectors in
western type reactors.
• We ask, can we use machine learning to successfully approximate the reactor
transfer function?
• However, to effectively train ML algorithms large quantities of data are
required.
More details can be found in the presentation file
European Commission
10.13039/501100000780
754316
Core monitoring techniques and experimental validation and demonstration