Portfolio optimization of safety measures for reducing risks in nuclear systems. (November 2017)
- Record Type:
- Journal Article
- Title:
- Portfolio optimization of safety measures for reducing risks in nuclear systems. (November 2017)
- Main Title:
- Portfolio optimization of safety measures for reducing risks in nuclear systems
- Authors:
- Mancuso, A.
Compare, M.
Salo, A.
Zio, E. - Abstract:
- Highlights: Risk-based optimization to select safety measures in high-risk installations. Computationally viable algorithm to identify cost-efficient portfolios. Feasibility of the approach shown by revisiting an earlier case study concerning an airlock system. Comparison of the results with the procedure on risk importance measures. Abstract: In the framework of Probabilistic Risk Assessment (PRA), we develop a method to support the selection of cost-effective portfolios of safety measures. This method provides a systemic approach to determining the optimal portfolio of safety measures that minimizes the risk of the system and thus provides an alternative to using risk importance measures for guiding the selection of safety measures. We represent combinations of events leading to system failure with Bayesian Belief Networks (BBNs) which can be derived from traditional Fault Trees (FTs) and are capable of encoding event dependencies and multi-state failure behaviours. We also develop a computationally efficient enumeration algorithm to identify which combinations (portfolios) of safety measures minimize the risk of failure at different costs of implementing the safety measures. The method is illustrated by revisiting an earlier case study concerning the airlock system of a CANDU Nuclear Power Plant (NPP). The comparison of results with those of choosing safety measures based on risk importance measures shows that our approach leads to considerably lower residual risk atHighlights: Risk-based optimization to select safety measures in high-risk installations. Computationally viable algorithm to identify cost-efficient portfolios. Feasibility of the approach shown by revisiting an earlier case study concerning an airlock system. Comparison of the results with the procedure on risk importance measures. Abstract: In the framework of Probabilistic Risk Assessment (PRA), we develop a method to support the selection of cost-effective portfolios of safety measures. This method provides a systemic approach to determining the optimal portfolio of safety measures that minimizes the risk of the system and thus provides an alternative to using risk importance measures for guiding the selection of safety measures. We represent combinations of events leading to system failure with Bayesian Belief Networks (BBNs) which can be derived from traditional Fault Trees (FTs) and are capable of encoding event dependencies and multi-state failure behaviours. We also develop a computationally efficient enumeration algorithm to identify which combinations (portfolios) of safety measures minimize the risk of failure at different costs of implementing the safety measures. The method is illustrated by revisiting an earlier case study concerning the airlock system of a CANDU Nuclear Power Plant (NPP). The comparison of results with those of choosing safety measures based on risk importance measures shows that our approach leads to considerably lower residual risk at different cost levels. … (more)
- Is Part Of:
- Reliability engineering & system safety. Volume 167(2017)
- Journal:
- Reliability engineering & system safety
- Issue:
- Volume 167(2017)
- Issue Display:
- Volume 167, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 167
- Issue:
- 2017
- Issue Sort Value:
- 2017-0167-2017-0000
- Page Start:
- 20
- Page End:
- 29
- Publication Date:
- 2017-11
- Subjects:
- Bayesian Belief Networks -- Portfolio optimization -- Risk analysis -- Safety barriers -- Risk importance measures
Reliability (Engineering) -- Periodicals
System safety -- Periodicals
Industrial safety -- Periodicals
Fiabilité -- Périodiques
Sécurité des systèmes -- Périodiques
Sécurité du travail -- Périodiques
620.00452 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09518320 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ress.2017.05.005 ↗
- Languages:
- English
- ISSNs:
- 0951-8320
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7356.422700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10739.xml