On the quantification of safety margins

The nuclear industry has relied on the concept of Defense in Depth (DID) and traditional safety margins to deal with the uncertainties associated with the design and operation of nuclear facilities. These concepts were formulated in the early days of development of nuclear power when these uncertainties could not be quantified. The subsequent development of Probabilistic Risk Assessment (PRA) has provided the analytical tools that allow the quantification of uncertainties associated with accident initiation and progression. But, while the impact of redundancy has been explicitly modeled and quantified, the role of safety margins is still not explicitly taken into account. The present work identifies the impact of safety margins in the PRA and proposes a methodology to quantify them. Practical examples are developed and discussed in two case studies. In the first study, we analyze the passive cooling of a gas-cooled fast reactor and we use an importance sampling Monte Carlo technique to propagate the epistemic uncertainties and to calculate the overall probability of failure. A comparison with an alternative active design is considered also. The results show that the active system can have, for this particular application, better reliability than the passive one.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Nuclear Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Pagani, Lorenzo P

Advisor dc:contributor.advisor

• George E. Apostolakis.

• Nuclear Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/33642

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/33642