IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v210y2021ics095183202100079x.html
   My bibliography  Save this article

nSIL Evaluation and Sensitivity Study of Diverse Redundant Structure

Author

Listed:
  • Fu, Jianmin
  • Li, Honghao
  • Chi, Yajuan
  • Zhen, Jia
  • Xu, Xiangfeng

Abstract

In order to evaluate the safety integrity level (SIL) of safety instrumented systems (SIS) with diverse redundancy structures including more realistic assumptions, the average probability of failure on demand (PFDavg) models for the common diverse redundancy structures (1oo2, 2oo2, and 2oo3) have been established based on the fault tree analysis (FTA) method. These models take into account the common cause failures (CCF) and diagnostic coverage (DC) parameters with the correction coefficient. The model is applied to the SIL assessment of the emergency shutdown system (ESD) with diverse redundancy in gas storage and gathering. The proof test interval T is used as an indicator to compare and verify the sensitivity of both the new model and the previous models. The results can be concluded as follows: 1) The new model achieves higher consistency than the previous models; 2) The proposed model considers that different redundancy structures have CCF, which are more realistic and have higher applicability to be used to solve practical engineering problems.

Suggested Citation

  • Fu, Jianmin & Li, Honghao & Chi, Yajuan & Zhen, Jia & Xu, Xiangfeng, 2021. "nSIL Evaluation and Sensitivity Study of Diverse Redundant Structure," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    • Handle: RePEc:eee:reensy:v:210:y:2021:i:c:s095183202100079x
    DOI: 10.1016/j.ress.2021.107518
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202100079X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2021.107518?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. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2009. "Design optimization of a safety-instrumented system based on RAMS+C addressing IEC 61508 requirements and diverse redundancy," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 162-179.
    2. Lundteigen, Mary Ann & Rausand, Marvin, 2008. "Spurious activation of safety instrumented systems in the oil and gas industry: Basic concepts and formulas," Reliability Engineering and System Safety, Elsevier, vol. 93(8), pages 1208-1217.
    3. Ding, Long & Wang, Hong & Jiang, Jin & Xu, Aidong, 2017. "SIL verification for SRS with diverse redundancy based on system degradation using reliability block diagram," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 170-187.
    4. Lu, Lixuan & Lewis, Gregory, 2008. "Configuration determination for k-out-of-n partially redundant systems," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1594-1604.
    5. Guo, Haitao & Watson, Simon & Tavner, Peter & Xiang, Jiangping, 2009. "Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1057-1063.
    6. Jigar, Abraham Almaw & Liu, Yiliu & Lundteigen, Mary Ann, 2016. "Spurious activation analysis of safety-instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 15-23.
    Full references (including those not matched with items on IDEAS)

    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. Qi, Meng & Kan, Yufeng & Li, Xun & Wang, Xiaoying & Zhao, Dongfeng & Moon, Il, 2020. "Spurious activation and operational integrity evaluation of redundant safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    2. Meng, Huixing & Kloul, Leïla & Rauzy, Antoine, 2018. "Modeling patterns for reliability assessment of safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 111-123.
    3. Wu, Shengnan & Zhang, Laibin & Zheng, Wenpei & Liu, Yiliu & Lundteigen, Mary Ann, 2019. "Reliability modeling of subsea SISs partial testing subject to delayed restoration," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Gabriel, Angelito & Ozansoy, Cagil & Shi, Juan, 2018. "Developments in SIL determination and calculation," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 148-161.
    5. Cai, Baoping & Li, Wenchao & Liu, Yiliu & Shao, Xiaoyan & Zhang, Yanping & Zhao, Yi & Liu, Zengkai & Ji, Renjie & Liu, Yonghong, 2021. "Modeling for evaluation of safety instrumented systems with heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2011. "Modeling safety instrumented systems with MooN voting architectures addressing system reconfiguration for testing," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 545-563.
    7. Redutskiy, Yury & Camitz-Leidland, Cecilie M. & Vysochyna, Anastasiia & Anderson, Kristanna T. & Balycheva, Marina, 2021. "Safety systems for the oil and gas industrial facilities: Design, maintenance policy choice, and crew scheduling," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    8. Khalil, Y.F., 2019. "New statistical formulations for determination of qualification test plans of safety instrumented systems (SIS) subject to low/high operational demands," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 196-209.
    9. Li, Yan-Fu & Zio, Enrico, 2012. "A multi-state model for the reliability assessment of a distributed generation system via universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 28-36.
    10. Zhang, Cai Wen & Zhang, Tieling & Chen, Nan & Jin, Tongdan, 2013. "Reliability modeling and analysis for a novel design of modular converter system of wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 86-94.
    11. Lundteigen, Mary Ann & Rausand, Marvin, 2009. "Architectural constraints in IEC 61508: Do they have the intended effect?," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 520-525.
    12. Shafiee, Mahmood, 2015. "Maintenance logistics organization for offshore wind energy: Current progress and future perspectives," Renewable Energy, Elsevier, vol. 77(C), pages 182-193.
    13. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    14. Hu, Jinxing & Li, Hongru, 2022. "A transfer learning-based scenario generation method for stochastic optimal scheduling of microgrid with newly-built wind farm," Renewable Energy, Elsevier, vol. 185(C), pages 1139-1151.
    15. Peng, Yizhen & Wang, Yu & Zi, YanYang & Tsui, Kwok-Leung & Zhang, Chuhua, 2017. "Dynamic reliability assessment and prediction for repairable systems with interval-censored data," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 301-309.
    16. Li, Shenghu, 2013. "Reliability models for DFIGs considering topology change under different control strategies and components data change under adverse operation environments," Renewable Energy, Elsevier, vol. 57(C), pages 144-150.
    17. Lundteigen, Mary Ann & Rausand, Marvin & Utne, Ingrid Bouwer, 2009. "Integrating RAMS engineering and management with the safety life cycle of IEC 61508," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1894-1903.
    18. Chang, Yang & Fang, Huajing, 2019. "A hybrid prognostic method for system degradation based on particle filter and relevance vector machine," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 51-63.
    19. Peng, Hao & van Houtum, Geert-Jan, 2016. "Joint optimization of condition-based maintenance and production lot-sizing," European Journal of Operational Research, Elsevier, vol. 253(1), pages 94-107.
    20. Longhi, Antonio Eduardo Bier & Pessoa, Artur Alves & Garcia, Pauli Adriano de Almada, 2015. "Multiobjective optimization of strategies for operation and testing of low-demand safety instrumented systems using a genetic algorithm and fault trees," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 525-538.

    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:210:y:2021:i:c:s095183202100079x. 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.