Dynamic Analysis of the Consequences of Gas Release in Process Industries Using Event Tree Technique and Bayesian Network

  • Iraj Mohammadfam
Keywords: Dynamic Analysis, Event Tree Technique, Bayesian Network


In process industries, storage tanks play an important role in the storage of a wide range of chemicals, compressed gas and other hydrocarbons. Gas release from these tanks can lead to catastrophic events with huge financial, human, and environmental consequences. In this study, a compressed gas tank was chosen as the unit of case study. Gas release as the top event was taken into consideration for quantitative and qualitative analysis of the probable consequences using the Event Tree Analysis and Bayesian network model. Analyzing the consequences of gas release from the tank by Event Tree Analysis (ETA), 6 safety barriers were detected to prevent the top event. The success and failure of these barriers could lead to 10 final consequences. Among the identified consequences, “near misses” were known to be the most probable consequence. The results of the study showed that safety barriers could significantly reduce the consequences of the occurrence of the top event. Bayesian networks can fix the static problem of quantitative risk analysis and provide the capability to determine the most probable consequences of the top event.


Lees, F., Lees' Loss prevention in the process industries: Hazard identification, assessment and control. 2012: Butterworth-Heinemann.

Azadeh A, Nouri J, Mohammad Fam I. The impacts of macroergonomics on environmental protection and human performance in power plants.Iranian J Env Health Sci Eng, 2005.2 (1): p. 60-66.

Nezhad, A.Z., et al., Identification and Safety Assessment of the Hazardous Zones (Unwanted Energy Flows) in an Construction Project at the National Petrochemical Company by Application of ET and BA Method. Journal of Applied Sciences, 2007. 7(19): p. 2769-75.

Chang, J.I. and C.-C. Lin, A study of storage tank accidents. Journal of loss prevention in the process industries, 2006. 19(1): p. 51-59.

Florea, G. and M. Popa, Safety and Security Integration in LPG Tank Farm Process Control. IFAC Proceedings Volumes, 2012. 45(6): p. 1828-1831.

Mohammadfam I, Bahrami A, Fatemi F, Golmohammadi R, Mahjub H. Evaluation of the relationship between job stress and unsafe acts with occupational accidents in a vehicle manufacturing plant. Avicenna Journal of Clinical Medicine. 2008. 15(3):P. 60-6.

Pallotta, N., et al., Ultrasonographic detection and assessment of the severity of Crohn's disease recurrence after ileal resection. BMC gastroenterology, 2010. 10(1): p. 69.

Azadeh A, Fam IM, Azadeh MA. Integrated HSEE management systems for industry: A case study in gas refinary. Journal of the Chinese Institute of Engineers. 2009.32(2):P.235-41.

Smith, L., M. Smith, and P. Ashcroft, Analysis of environmental and economic damages from British Petroleum’s Deepwater Horizon oil spill. 2011.

Taveau, J., Explosion of fixed roof atmospheric storage tanks, Part 1: Background and review of case histories. Process Safety Progress, 2011. 30(4): p. 381-392.

Hyatt, N., Guidelines for process hazards analysis (PHA, HAZOP), hazards identification, and risk analysis. 2003: CRC press.

Marhavilas, P.K. and D. Koulouriotis, A risk-estimation methodological framework using quantitative assessment techniques and real accidents’ data: Application in an aluminum extrusion industry. Journal of Loss Prevention in the Process Industries, 2008. 21(6): p. 596-603.

Mohammadfam I, Kamalinia M, Momeni M, Golmohammadi R, Hamidi Y, Soltanian A. Developing an integrated decision making approach to assess and promote the effectiveness of occupational health and safety management systems. Journal of Cleaner Production. 2016. 127:P. 119-33.

Park, K., et al., Incident analysis of Bucheon LPG filling station pool fire and BLEVE. Journal of hazardous materials, 2006. 137(1): p. 62-67.

Abimbola, M., F. Khan, and N. Khakzad, Dynamic safety risk analysis of offshore drilling. Journal of Loss Prevention in the Process Industries, 2014. 30: p. 74-85.

Yang, X. and M.S. Mannan, The development and application of dynamic operational risk assessment in oil/gas and chemical process industry. Reliability Engineering & System Safety, 2010. 95(7): p. 806-815.

Mohammadfam I, Ghasemi F, Kalatpour O, Moghimbeigi A. Constructing a Bayesian network model for improving safety behavior of employees at workplaces. Applied ergonomics. 2017. 58:P. 35-47.

Khakzad, N., F. Khan, and P. Amyotte, Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network. Process Safety and Environmental Protection, 2013. 91(1): p. 46-53.

Zhang, G. and V.V. Thai, Addressing the epistemic uncertainty in maritime accidents modelling using Bayesian network with interval probabilities. Safety science, 2018. 102: p. 211-225.

Ghasemi F, Kalatpour O, Moghimbeigi A, Mohammadfam I. Selecting strategies to reduce high-risk unsafe work behaviors using the safety behavior sampling technique and Bayesian network analysis. Journal of research in health sciences. 2017.17(1):P.1-6.

Aiyou, W., et al., City fire risk analysis based on coupling fault tree method and triangle fuzzy theory. Procedia Engineering, 2014. 84: p. 204-212.

Zulqarnain, M. and M. Tyagi. Quantification of Risks Associated With a Representative Production Well in the Gulf of Mexico. in ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. 2015. American Society of Mechanical Engineers.

Andrews, J.D. and S.J. Dunnett, Event-tree analysis using binary decision diagrams. IEEE Transactions on Reliability, 2000. 49(2): p. 230-238.


Cai, B., et al., Application of Bayesian networks in quantitative risk assessment of subsea blowout preventer operations. Risk Analysis, 2013. 33(7): p. 1293-1311.

Abimbola, M., et al., Safety and risk analysis of managed pressure drilling operation using Bayesian network. Safety science, 2015. 76: p. 133-144.

Hong, E.-S., et al., Quantitative risk evaluation based on event tree analysis technique: Application to the design of shield TBM. Tunnelling and Underground Space Technology, 2009. 24(3): p. 269-277.

Khakzad, N., F. Khan, and P. Amyotte, Quantitative risk analysis of offshore drilling operations: a Bayesian approach. Safety science, 2013. 57: p. 108-117.

Kabir, S., M. Walker, and Y. Papadopoulos, Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks. Safety science, 2018. 105: p. 55-70.

Leu, S.-S. and C.-M. Chang, Bayesian-network-based safety risk assessment for steel construction projects. Accident Analysis & Prevention, 2013. 54: p. 122-133.

Sule, I., et al., Kick control reliability analysis of managed pressure drilling operation. Journal of Loss Prevention in the Process Industries, 2018.

Yuan, Z., et al., Risk analysis of dust explosion scenarios using Bayesian networks. Risk analysis, 2015. 35(2): p. 278-291.

How to Cite
Mohammadfam I. Dynamic Analysis of the Consequences of Gas Release in Process Industries Using Event Tree Technique and Bayesian Network. Int J Occup Hyg. 10(3).
Original Article(s)