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Other literature type . 2021
License: CC BY
Data sources: ZENODO
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Presentation . 2021
License: CC BY
Data sources: Datacite
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Detection and localisation of multiple in-core perturbations with neutron noise-based self-supervised domain adaptation

Authors: A. Durrant;

Detection and localisation of multiple in-core perturbations with neutron noise-based self-supervised domain adaptation

Abstract

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

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Funded by
EC| CORTEX
Project
CORTEX
Core monitoring techniques and experimental validation and demonstration
  • Funder: European Commission (EC)
  • Project Code: 754316
  • Funding stream: H2020 | RIA
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