Application of Bayesian methods and networks to ignition hazard event prediction in nuclear waste decommissioning operations
- Submitting institution
-
London South Bank University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 251676
- Type
- D - Journal article
- DOI
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10.1016/j.psep.2018.03.002
- Title of journal
- Process Safety and Environmental Protection
- Article number
- -
- First page
- 396
- Volume
- 116
- Issue
- -
- ISSN
- 0957-5820
- Open access status
- Access exception
- Month of publication
- March
- Year of publication
- 2018
- URL
-
https://www.sciencedirect.com/science/article/pii/S0957582018300521
- 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
- No
- Number of additional authors
-
4
- Research group(s)
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C - The London Centre for Energy Engineering
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Bayesian networks using original data and uncertainties were created, incorporating expert opinion from Sellafield Ltd, giving much more realistic event probabilities. This work represents a fundamental shift in the making of nuclear safety cases and, for the first time, was successfully applied at Sellafield. This helped underpin the renewal of LSBU’s partnership with Sellafield Ltd in 2019 to support their Flammable Gas Centre of Expertise (£500k).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -