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Risk Analysis of Dust Explosion Scenarios Using Bayesian Networks

Author

Listed:
  • Zhi Yuan
  • Nima Khakzad
  • Faisal Khan
  • Paul Amyotte

Abstract

In this study, a methodology has been proposed for risk analysis of dust explosion scenarios based on Bayesian network. Our methodology also benefits from a bow‐tie diagram to better represent the logical relationships existing among contributing factors and consequences of dust explosions. In this study, the risks of dust explosion scenarios are evaluated, taking into account common cause failures and dependencies among root events and possible consequences. Using a diagnostic analysis, dust particle properties, oxygen concentration, and safety training of staff are identified as the most critical root events leading to dust explosions. The probability adaptation concept is also used for sequential updating and thus learning from past dust explosion accidents, which is of great importance in dynamic risk assessment and management. We also apply the proposed methodology to a case study to model dust explosion scenarios, to estimate the envisaged risks, and to identify the vulnerable parts of the system that need additional safety measures.

Suggested Citation

  • Zhi Yuan & Nima Khakzad & Faisal Khan & Paul Amyotte, 2015. "Risk Analysis of Dust Explosion Scenarios Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 35(2), pages 278-291, February.
    • Handle: RePEc:wly:riskan:v:35:y:2015:i:2:p:278-291
    DOI: 10.1111/risa.12283
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    References listed on IDEAS

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    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. Nima Khakzad & Faisal Khan & Paul Amyotte & Valerio Cozzani, 2013. "Domino Effect Analysis Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 292-306, February.
    3. Cai, Baoping & Liu, Yonghong & Liu, Zengkai & Tian, Xiaojie & Dong, Xin & Yu, Shilin, 2012. "Using Bayesian networks in reliability evaluation for subsea blowout preventer control system," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 32-41.
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    2. Liu, Cuiwei & Wang, Yazhen & Li, Xinhong & Li, Yuxing & Khan, Faisal & Cai, Baoping, 2021. "Quantitative assessment of leakage orifices within gas pipelines using a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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    9. Rongchen Zhu & Xin Li & Xiaofeng Hu & Deshui Hu, 2019. "Risk Analysis of Chemical Plant Explosion Accidents Based on Bayesian Network," Sustainability, MDPI, vol. 12(1), pages 1-20, December.
    10. Arman Nedjati & Mohammad Yazdi & Rouzbeh Abbassi, 2022. "A sustainable perspective of optimal site selection of giant air-purifiers in large metropolitan areas," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8747-8778, June.
    11. Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Chen, Xianqi, 2019. "Improved compression inference algorithm for reliability analysis of complex multistate satellite system based on multilevel Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 123-142.

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