Published April 2017 | Version v1
Miscellaneous

Study of accident sequences using refined plant damage states in level 2 PSA

  • 1. Hitachi-GE Nuclear Energy, Ltd., Hitachi, Ibaraki (Japan)

Description

Probabilistic Safety Assessment (PSA) is a methodology to evaluate an inherent risk at a nuclear power plant caused by potential Initiating Events (IEs) which can result in Fission Products releases to the environment. Three levels of PSA are classified as following. Level 1 PSA: The assessment of plant failures leading to core damage. Level 2 PSA: The assessment of containment release consequences with the results of Level 1 PSA. Level 3 PSA: The assessment of the off-site consequences with the results of Level 2 PSA. PSA should treat the accident sequences in detail sufficient to address characteristics of a initiating event, accident progression, success criteria, plant operation procedure and so on. Since the development of all accident sequences is not realistic due to its amounts, similar accident sequences are grouped as into the Accident Classes which are used to group Level 1 PSA and the Plant Damage States (PDSs) for Level 2 PSA. In this process, it is important to reflect the characteristic in accident sequences. In this paper, it is discussed how the interface between Accident Class and PDS impacts on the results of Level 2 PSA for Advanced Boiling Water Reactor (ABWR). This refinement enables detailed analysis of accident sequence and source term. (author)

Part of:
Proceedings of 2017 international congress on advances in nuclear power plants (ICAPP2017)

Additional details

Publishing Information

Imprint Title
Proceedings of 2017 international congress on advances in nuclear power plants (ICAPP2017)
Imprint Pagination
2573 p.
Journal Page Range
5 p.

Conference

Title
2017 international congress on advances in nuclear power plants
Acronym
ICAPP2017
Dates
24-25 Apr 2017; 26-28 Apr 2017
Place
Fukui (Japan); Kyoto (Japan)

Optional Information

Notes
Available as CD-ROM Data in PDF format. Folder Name: pdf; Paper ID: 17151.pdf; 3 refs., 2 figs., 1 tab.