IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v144y2015icp285-295.html
   My bibliography  Save this article

Reliability modeling of safety-critical network communication in a digitalized nuclear power plant

Author

Listed:
  • Lee, Sang Hun
  • Kim, Hee Eun
  • Son, Kwang Seop
  • Shin, Sung Min
  • Lee, Seung Jun
  • Kang, Hyun Gook

Abstract

The Engineered Safety Feature-Component Control System (ESF-CCS), which uses a network communication system for the transmission of safety-critical information from group controllers (GCs) to loop controllers (LCs), was recently developed. However, the ESF-CCS has not been applied to nuclear power plants (NPPs) because the network communication failure risk in the ESF-CCS has yet to be fully quantified. Therefore, this study was performed to identify the potential hazardous states for network communication between GCs and LCs and to develop quantification schemes for various network failure causes. To estimate the risk effects of network communication failures in the ESF-CCS, a fault-tree model of an ESF-CCS signal failure in the containment spray actuation signal condition was developed for the case study. Based on a specified range of periodic inspection periods for network modules and the baseline probability of software failure, a sensitivity study was conducted to analyze the risk effect of network failure between GCs and LCs on ESF-CCS signal failure. This study is expected to provide insight into the development of a fault-tree model for network failures in digital I&C systems and the quantification of the risk effects of network failures for safety-critical information transmission in NPPs.

Suggested Citation

  • Lee, Sang Hun & Kim, Hee Eun & Son, Kwang Seop & Shin, Sung Min & Lee, Seung Jun & Kang, Hyun Gook, 2015. "Reliability modeling of safety-critical network communication in a digitalized nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 285-295.
  • Handle: RePEc:eee:reensy:v:144:y:2015:i:c:p:285-295
    DOI: 10.1016/j.ress.2015.07.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015002355
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2015.07.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kang, Hyun Gook & Jang, Seung-Cheol, 2006. "Application of condition-based HRA method for a manual actuation of the safety features in a nuclear power Plant," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 627-633.
    2. Kim, Man Cheol & Smidts, Carol S., 2015. "Three suggestions on the definition of terms for the safety and reliability analysis of digital systems," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 81-91.
    3. Koo, Seo Ryong & Seong, Poong Hyun, 2006. "Software design specification and analysis technique (SDSAT) for the development of safety-critical systems based on a programmable logic controller (PLC)," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 648-664.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shin, Sung-Min & Lee, Sang Hun & Shin, Seung Ki, 2022. "A novel approach for quantitative importance analysis of safety DI&C systems in the nuclear field," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Quintanilha, Igor M. & Elias, Vitor R.M. & da Silva, Felipe B. & Fonini, Pedro A.M. & da Silva, Eduardo A.B. & Netto, Sergio L. & Apolinário, José A. & de Campos, Marcello L.R. & Martins, Wallace A., 2021. "A fault detector/classifier for closed-ring power generators using machine learning," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    2. Yang, Jun & Zou, Bowen & Yang, Ming, 2019. "Bidirectional implementation of Markov/CCMT for dynamic reliability analysis with application to digital I&C systems," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 278-290.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:144:y:2015:i:c:p:285-295. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.