Robust on-line diagnosis tool for the early accident detection in nuclear power plants
- Submitting institution
-
University of Portsmouth
- Unit of assessment
- 12 - Engineering
- Output identifier
- 14093209
- Type
- D - Journal article
- DOI
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10.1016/j.ress.2019.02.015
- Title of journal
- Reliability Engineering and System Safety
- Article number
- 0
- First page
- 110
- Volume
- 186
- Issue
- -
- ISSN
- 0951-8320
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
6
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work is the result of an international collaboration involving the universities of Portsmouth, Liverpool and Leeds-Beckett (UK), and the Bhabha Atomic Research Centre (India). The work presents novel, accurate and robust approaches for the detection and characterisation of loss of coolant faults in nuclear reactors. The methods and models presented in this article have been used by the Bhabha Atomic Research Centre (BARC) in India as part of their nuclear reactor diagnostics programme. This claim can be verified by contacting Gopika Vinod vgopika@barc.gov.in. This work was part of EPSRC funded project EP/M018709/1 "Smart on-line monitoring for nuclear power plants”.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -