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Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems

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  • Groth, Katrina
  • Wang, Chengdong
  • Mosleh, Ali

Abstract

This paper introduces an integrated framework and software platform for probabilistic risk assessment (PRA) and safety monitoring of complex socio-technical systems. An overview of the three-layer hybrid causal logic (HCL) modeling approach and corresponding algorithms, implemented in the Trilith software platform, are provided. The HCL approach enhances typical PRA methods by quantitatively including the influence of soft causal factors introduced by human and organizational aspects of a system. The framework allows different modeling techniques to be used for different aspects of the socio-technical system. The HCL approach combines the power of traditional event sequence diagram (ESD)event tree (ET) and fault tree (FT) techniques for modeling deterministic causal paths, with the flexibility of Bayesian belief networks for modeling non-deterministic cause–effect relationships among system elements (suitable for modeling human and organizational influences). Trilith enables analysts to construct HCL models and perform quantitative risk assessment and management of complex systems. The risk management capabilities included are HCL-based risk importance measures, hazard identification and ranking, precursor analysis, safety indicator monitoring, and root cause analysis. This paper describes the capabilities of the Trilith platform and power of the HCL algorithm by use of example risk models for a type of aviation accident (aircraft taking off from the wrong runway).

Suggested Citation

  • Groth, Katrina & Wang, Chengdong & Mosleh, Ali, 2010. "Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1276-1285.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:12:p:1276-1285
    DOI: 10.1016/j.ress.2010.06.005
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    References listed on IDEAS

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    1. Mohaghegh, Zahra & Kazemi, Reza & Mosleh, Ali, 2009. "Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 1000-1018.
    2. Groen, Frank J. & Smidts, Carol & Mosleh, Ali, 2006. "QRAS—the quantitative risk assessment system," Reliability Engineering and System Safety, Elsevier, vol. 91(3), pages 292-304.
    3. Røed, Willy & Mosleh, Ali & Vinnem, Jan Erik & Aven, Terje, 2009. "On the use of the hybrid causal logic method in offshore risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 445-455.
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    5. Justin Pence & Zahra Mohaghegh, 2020. "A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1183-1211, June.
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    7. Farcasiu, M. & Prisecaru, I., 2014. "MMOSA – A new approach of the human and organizational factor analysis in PSA," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 91-98.
    8. Stephen Thomas & Katrina M Groth, 2023. "Toward a hybrid causal framework for autonomous vehicle safety analysis," Journal of Risk and Reliability, , vol. 237(2), pages 367-388, April.
    9. Ramos, M.A. & Thieme, Christoph A. & Utne, Ingrid B. & Mosleh, A., 2020. "Human-system concurrent task analysis for maritime autonomous surface ship operation and safety," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    10. Baoping Cai & Yonghong Liu & Zengkai Liu & Xiaojie Tian & Yanzhen Zhang & Renjie Ji, 2013. "Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1293-1311, July.
    11. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    12. Groth, Katrina M. & Swiler, Laura P., 2013. "Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 33-42.
    13. Pence, Justin & Sakurahara, Tatsuya & Zhu, Xuefeng & Mohaghegh, Zahra & Ertem, Mehmet & Ostroff, Cheri & Kee, Ernie, 2019. "Data-theoretic methodology and computational platform to quantify organizational factors in socio-technical risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 240-260.
    14. Y-F Wang & M Xie & M S Habibullah & K-M Ng, 2011. "Quantitative risk assessment through hybrid causal logic approach," Journal of Risk and Reliability, , vol. 225(3), pages 323-332, September.
    15. Zhou, Jianfeng & Reniers, Genserik & Khakzad, Nima, 2016. "Application of event sequence diagram to evaluate emergency response actions during fire-induced domino effects," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 202-209.

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