MINIMAL CUT SETS IDENTIFICATION OF NUCLEAR SYSTEMS BY EVOLUTIONARY ALGORITHMS

Abstract : Fault Trees (FTs) for the Probabilistic Safety Analysis (PSA) of real systems suffer from the combinatorial explosion of failure sets. Then, minimal cut sets (mcs) identification is not a trivial technical issue. In this work, we transform the search of the event sets leading to system failure and the identification of the mcs into an optimization problem. We do so by hierarchically looking for the minimum combination of cut sets that can guarantee the best coverage of all the minterms that make the system fail. A multiple-population, parallel search policy based on a Differential Evolution (DE) algorithm is developed and shown to be efficient for mcs identification, on a case study considering the Airlock System (AS) of CANDU reactor.
Document type :
Conference papers
Complete list of metadatas

Cited literature [19 references]  Display  Hide  Download

https://hal-supelec.archives-ouvertes.fr/hal-00930230
Contributor : Yanfu Li <>
Submitted on : Tuesday, January 14, 2014 - 2:51:01 PM
Last modification on : Tuesday, August 13, 2019 - 11:10:04 AM
Long-term archiving on : Tuesday, April 15, 2014 - 4:25:02 PM

Files

2013_02_04_Minimal_Cut_Sets_Id...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00930230, version 1

Citation

Francesco Di Maio, Samuele Baronchelli, Enrico Zio. MINIMAL CUT SETS IDENTIFICATION OF NUCLEAR SYSTEMS BY EVOLUTIONARY ALGORITHMS. International Topical Meeting on Probabilistic Safety Assessment and Analysis, Sep 2013, Columbia, United States. ⟨hal-00930230⟩

Share

Metrics

Record views

465

Files downloads

258