Joint optimization of safety barriers for enhancing business continuity of nuclear power plants against steam generator tube ruptures accidents
| Autor: | Zhiguo Zeng, Jinduo Xing, Enrico Zio |
|---|---|
| Přispěvatelé: | Centre de recherche sur les Risques et les Crises (CRC), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL) |
| Rok vydání: | 2020 |
| Předmět: |
Event tree
Business continuity management (BCM) Mixed-integer genetic algorithm (MIGA) Computer science 0211 other engineering and technologies Safety barrier 02 engineering and technology Industrial and Manufacturing Engineering [SPI]Engineering Sciences [physics] Business continuity Event tree (ET) [SHS.GEST-RISQ]Humanities and Social Sciences/domain_shs.gest-risq Nuclear power plant (NPP) Safety Risk Reliability and Quality ComputingMilieux_MISCELLANEOUS 021110 strategic defence & security studies 021103 operations research business.industry Boiler (power generation) Steam generator tube rupture (SGTR) Nuclear power Joint optimization Prevention barriers Reliability engineering business |
| Zdroj: | Reliability Engineering and System Safety Reliability Engineering and System Safety, Elsevier, 2020, 202, pp.107067. ⟨10.1016/j.ress.2020.107067⟩ |
| ISSN: | 0951-8320 1879-0836 |
| DOI: | 10.1016/j.ress.2020.107067 |
| Popis: | In nuclear power plants (NPPs), different types of safety barriers are designed to ensure the safe and continuous operation of the NPP against disruptive events. These safety barriers, although designed to operate in different phases of the accidents evolution, are often optimized separately, without considering their collective effects on preventing disruptions and quickly recovering from the disruptions. This paper develops a joint optimization model for synthetically optimizing safety barriers of different natures, including prevention, mitigation, emergency and recovery barriers to enhance the business continuity of the NPP, considering the threat of steam generator tube rupture (SGTR) accidents. The joint optimization is guided by a business continuity metric called expected business continuity value (EBCV). A physics-of-failure model is developed to describe the crack growth process of the steam generator tube and to model the effect of the prevention barriers, i.e., periodical inspection of the crack length. An event tree model is developed to describe the evolution of the SGTR-initiated accident and to model the effect of the mitigation and emergency barriers. Recovery measures are also considered via a widely-used logarithmic function model. A mixed-integer genetic algorithm (MIGA) is used to obtain optimal solutions of the joint optimization model. The results show that the developed joint optimization model can achieve better performance in terms of business continuity, compared to the conventional methods that optimize the safety barriers separately. |
| Databáze: | OpenAIRE |
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