Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference & The Annual European Safety and Reliability Conference |
| Subtitle of host publication | PSAM11 ESREL 2012 |
| Pages | 2778-2785 |
| Volume | 4 |
| Publication status | Published - 2012 |
| MoE publication type | A4 Article in a conference publication |
| Event | 11th International Probabilistic Safety Assessment and Management Conference and The Annual European Safety and Reliability Conference, PSAM11 & ESREL 2012 - Helsinki, Finland Duration: 25 Jun 2012 → 29 Jun 2012 |
Conference
| Conference | 11th International Probabilistic Safety Assessment and Management Conference and The Annual European Safety and Reliability Conference, PSAM11 & ESREL 2012 |
|---|---|
| Country | Finland |
| City | Helsinki |
| Period | 25/06/12 → 29/06/12 |
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Keywords
- probabilistic risk analysis (PRA)
- passive systems
- passive containment cooling system (PCCS)
Cite this
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Passive Systems Reliability : Application of MELCOR Simulations for PCCS Case Study. / Männistö, Ilkka; Karanta, Ilkka.
Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference & The Annual European Safety and Reliability Conference: PSAM11 ESREL 2012. Vol. 4 2012. p. 2778-2785.Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Passive Systems Reliability
T2 - Application of MELCOR Simulations for PCCS Case Study
AU - Männistö, Ilkka
AU - Karanta, Ilkka
N1 - Project code: 73576
PY - 2012
Y1 - 2012
N2 - Increasing use of passive safety systems also increases the need for advanced methods of analyzing their reliability. Passive components work in a variety of ways. IAEA classifies these components and systems based on the level of passivity they exhibit. Reliability analysis of passive components relying mostly on physical phenomena require a combination of physics modeling and probabilistic methods. Challenges are to identify the mechanisms that can degrade or otherwise affect the systems stated safety function and the sources of uncertainty. Sources of uncertainty can be the geometric properties and layout of the system, material properties, design parameters and phenomenological analysis. A pilot case study of simulating a passive containment cooling system (PCCS) using MELCOR is applied within a simplified passive systems reliability framework. The aim of the framework is to explicitly state the interactions and information flow between deterministic physics modeling and probabilistic risk assessments, and the uncertainties related to them. The framework includes identification of main hazards, main sources of uncertainty both in the input data and the models, propagation of the uncertainties in physical models and finally the inclusion of the reliability assessment into the probabilistic risk analysis (PRA) model. The framework is partly based on a case study on a passive containment cooling system performed for this project. This paper includes the main results and lessons learned from the case study.
AB - Increasing use of passive safety systems also increases the need for advanced methods of analyzing their reliability. Passive components work in a variety of ways. IAEA classifies these components and systems based on the level of passivity they exhibit. Reliability analysis of passive components relying mostly on physical phenomena require a combination of physics modeling and probabilistic methods. Challenges are to identify the mechanisms that can degrade or otherwise affect the systems stated safety function and the sources of uncertainty. Sources of uncertainty can be the geometric properties and layout of the system, material properties, design parameters and phenomenological analysis. A pilot case study of simulating a passive containment cooling system (PCCS) using MELCOR is applied within a simplified passive systems reliability framework. The aim of the framework is to explicitly state the interactions and information flow between deterministic physics modeling and probabilistic risk assessments, and the uncertainties related to them. The framework includes identification of main hazards, main sources of uncertainty both in the input data and the models, propagation of the uncertainties in physical models and finally the inclusion of the reliability assessment into the probabilistic risk analysis (PRA) model. The framework is partly based on a case study on a passive containment cooling system performed for this project. This paper includes the main results and lessons learned from the case study.
KW - probabilistic risk analysis (PRA)
KW - passive systems
KW - passive containment cooling system (PCCS)
M3 - Conference article in proceedings
SN - 978-1-62276-436-5
VL - 4
SP - 2778
EP - 2785
BT - Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference & The Annual European Safety and Reliability Conference
ER -