Volume 22, Issue 1 (2025)
ioh 2025, 22(1): 326-346 |
Back to browse issues page
Ethics code: ندارد
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
khani Golabbas U, Panjali Z, Bayatian M. QUANTITATIVE RISK ASSESSMENT OF BUTADIENE STORAGE TANKS IN A PROCESS UNIT USING FAULT TREE ANALYSIS BY FUZZY BAYESIAN AND CONSEQUENCE MODELING. ioh 2025; 22 (1) : 19
URL: http://ioh.iums.ac.ir/article-1-3738-en.html
URL: http://ioh.iums.ac.ir/article-1-3738-en.html
Department of occupational health and work safey, TeMS.C., Islamic Azad University, Tehran, Iran , majid_bayatian@yahoo.com
Abstract: (666 Views)
ABSTRACT
BACKGROUND AND AIMS: Butadiene storage tanks in process industries pose substantial risks due to the highly flammable nature of their contents. Accurate risk assessment is essential not only for protecting personnel and equipment but also for ensuring overall process safety and safeguarding surrounding communities. This study aims to evaluate the risk levels of potentially catastrophic scenarios using Fault Tree Analysis (FTA) and to define the safety perimeter through risk contour modeling with DNV’s SAFETI v8.4 software.
METHODS: An expert panel collaborated to reduce uncertainties, and the worst-case scenario—characterized by the highest probability and severity—was selected. Experts’ opinions were applied through a fuzzy logic-based approach to estimate the probabilities of basic events in the chosen scenario. Root causes of failures were first outlined qualitatively, and then a quantitative FTA was conducted. Defuzzified data provided deterministic probabilities for each event, which were then utilized in a Bayesian Network model using GeNIe software to calculate the probability of the top event. SAFETI software was used to generate risk contours and determine safety perimeters for a catastrophic rupture.
RESULTS: FTA identified 45 basic and 17 intermediate events potentially leading to catastrophic outcomes. Bayesian analysis revealed that intentional procedural violations (probability: 0.0091622) as the most significant, while shear stress (0.00089743) was the least significant contributor. SAFETI modeling indicated maximum damage localized within the tank area, with risk diminishing at 900 meters from the explosion. The social risk was found at an unacceptable level (10⁻³), and the top event occurrence probability was 0.00020267.
CONCLUSION: FTA combined with SAFETI provides a robust framework for assessing and managing risk in hazardous process scenarios, offering practical insights for safety improvements and emergency planning.
KEYWORDS: Risk Assessment; Butadiene Tanks; Bayesian Network; Explosion; Consequence Modeling.
BACKGROUND AND AIMS: Butadiene storage tanks in process industries pose substantial risks due to the highly flammable nature of their contents. Accurate risk assessment is essential not only for protecting personnel and equipment but also for ensuring overall process safety and safeguarding surrounding communities. This study aims to evaluate the risk levels of potentially catastrophic scenarios using Fault Tree Analysis (FTA) and to define the safety perimeter through risk contour modeling with DNV’s SAFETI v8.4 software.
METHODS: An expert panel collaborated to reduce uncertainties, and the worst-case scenario—characterized by the highest probability and severity—was selected. Experts’ opinions were applied through a fuzzy logic-based approach to estimate the probabilities of basic events in the chosen scenario. Root causes of failures were first outlined qualitatively, and then a quantitative FTA was conducted. Defuzzified data provided deterministic probabilities for each event, which were then utilized in a Bayesian Network model using GeNIe software to calculate the probability of the top event. SAFETI software was used to generate risk contours and determine safety perimeters for a catastrophic rupture.
RESULTS: FTA identified 45 basic and 17 intermediate events potentially leading to catastrophic outcomes. Bayesian analysis revealed that intentional procedural violations (probability: 0.0091622) as the most significant, while shear stress (0.00089743) was the least significant contributor. SAFETI modeling indicated maximum damage localized within the tank area, with risk diminishing at 900 meters from the explosion. The social risk was found at an unacceptable level (10⁻³), and the top event occurrence probability was 0.00020267.
CONCLUSION: FTA combined with SAFETI provides a robust framework for assessing and managing risk in hazardous process scenarios, offering practical insights for safety improvements and emergency planning.
KEYWORDS: Risk Assessment; Butadiene Tanks; Bayesian Network; Explosion; Consequence Modeling.
Article number: 19
Type of Study: Research |
Subject:
Safety
Received: 2025/03/8 | Accepted: 2025/09/6 | Published: 2025/03/30
Received: 2025/03/8 | Accepted: 2025/09/6 | Published: 2025/03/30
References
1. HABIBI EA, KESHAVARZI M, YOUSEFI RHA, HASANZADEH A. Outcome analysis of major accidents and determining the safety integrity level of processes in sour water stripping unit of gas refinery using lopa technique. 2011.
2. Consequence IRSNM. Modeling of Explosion Events by PHAST Software in an Industrial Unit-A Case Study of 2 Phases of South Pars. Bulding of the Georgian National Academy of Science. 2015;9(1):26-316.
3. Aldeeb A, Rogers W, Mannan M. Evaluation of 1, 3-butadiene dimerization and secondary reactions in the presence and absence of oxygen. Journal of hazardous materials. 2004;115(1-3):51-6. [DOI:10.1016/j.jhazmat.2004.06.019] [PMID]
4. Станіславчук ОВ, Чеберячко СІ, Голінько ВІ, Забеліна ВА, Дерюгін ОВ. ANALYSIS OF REASONS OCCURRENCE OF DANGEROUS SITUATIONS DURING THE OPERATION OF GAS STATIONS. 2024.
5. Scarselli A, Corfiati M, Di Marzio D, Iavicoli S. Appraisal of levels and patterns of occupational exposure to 1, 3-butadiene. Scandinavian journal of work, environment & health. 2017:494-503. [DOI:10.5271/sjweh.3644] [PMID]
6. Yarandi MS, Karimi A, Sajedian AA, Ahmadi V. Comparative assessment of carcinogenic risk of respiratory exposure to 1, 3-Butadiene in a petrochemical industry by the US Environmental Protection Agency (USEPA) and Singapore Health Department methods. J Health Saf Work. 2019;10(3):237-50.
7. Melnick RL, Huff J. 1, 3-Butadiene: toxicity and carcinogenicity in laboratory animals and in humans. Reviews of Environmental Contamination and Toxicology: Continuation of Residue Reviews. 1992:111-44. [DOI:10.1007/978-1-4612-2864-6_5] [PMID]
8. Qiuhong W, Yilin S, Xin L, Juncheng J, Mingguang Z, Liubing W. Numerical simulation on gas dispersions and vapor cloud explosions induced by gas released from an ethylene storage tank. 爆炸与冲击. 2020;40(12):125401-1--13.
9. Wu X, Li L, Yin J, Wang B, Wang W, Lin G, et al. Studies on principle and prevention of explosion in butadiene systems. Process safety and environmental protection. 2002;80(6):305-9. [DOI:10.1205/095758202321154934]
10. AL RAZI KMH. 博士 (工学) 甲第 440 号. 2013.
11. Luong C, Zhang K. An assessment of emission event trends within the Greater Houston area during 2003-2013. Air Quality, Atmosphere & Health. 2017;10:543-54. [DOI:10.1007/s11869-016-0449-5]
12. journal Er. Butadiene leak at ExxonMobil in Baton Rouge 2025 [Available from: https://www.european-rubber-journal.com/article/2078303/butadiene-leak-at-exxonmobil-in-baton-rouge?utm_source=chatgpt.com.
13. Municipality G. 18-hour operation to neutralize the hazard of the overturned butadiene tanker. 2025.
14. Haghnazarloo H, Parvini M, Lotfollahi MN. Consequence modeling of a real rupture of toluene storage tank. Journal of loss prevention in the process industries. 2015;37:11-8. [DOI:10.1016/j.jlp.2015.06.007]
15. Mossink J, de Greef M. Inventory of socioeconomic costs of work accidents: Office for Official Publications of the European Communities Luxembourg; 2002.
16. Jallon R, Imbeau D, de Marcellis-Warin N. Development of an indirect-cost calculation model suitable for workplace use. Journal of safety research. 2011;42(3):149-64. [DOI:10.1016/j.jsr.2011.05.006] [PMID]
17. Broughton E. The Bhopal disaster and its aftermath: a review. Environmental Health. 2005;4:1-6. [DOI:10.1186/1476-069X-4-6] [PMID] []
18. Venart JES. Flixborough: the Explosion and its Aftermath. Process Safety and Environmental Protection. 2004;82(2):105-27. [DOI:10.1205/095758204322972753]
19. Anspaugh LR, Catlin RJ, Goldman M. The Global Impact of the Chernobyl Reactor Accident. Science. 1988;242(4885):1513-9. [DOI:10.1126/science.3201240] [PMID]
20. Carlson CS. Effective FMEAs: Achieving safe, reliable, and economical products and processes using failure mode and effects analysis: John Wiley & Sons; 2012. [DOI:10.1002/9781118312575]
21. Solukloei HRJ, Nematifard S, Hesami A, Mohammadi H, Kamalinia M. A fuzzy-HAZOP/ant colony system methodology to identify combined fire, explosion, and toxic release risk in the process industries. Expert Systems with Applications. 2022;192:116418. [DOI:10.1016/j.eswa.2021.116418]
22. Golfarelli M, Rizzi S, Proli A, editors. Designing what-if analysis: towards a methodology. Proceedings of the 9th ACM International Workshop on Data Warehousing and OLAP; 2006. [DOI:10.1145/1183512.1183523]
23. Zaranejad A, Ahmadi O. Fire and explosion risk assessment in a chemical company by the application of DOW fire and explosion index. Journal of Occupational Health and Epidemiology. 2015;4(3):163-75. [DOI:10.18869/acadpub.johe.4.3.163]
24. Hazop KS, ile Çalışanların ERDY. Control of Health Risk of Employees in The Chemical Industry With Hazop and Eta Risk Assessment Methods. AYDIN SAĞLIK DERGİSİ.246.
25. Jafari MJ, Pouyakian M, Hanifi SM. Reliability evaluation of fire alarm systems using dynamic Bayesian networks and fuzzy fault tree analysis. Journal of Loss Prevention in the Process Industries. 2020;67:104229. [DOI:10.1016/j.jlp.2020.104229]
26. Mohammadi H, Fazli Z, Kaleh H, Azimi HR, Moradi Hanifi S, Shafiee N. Risk analysis and reliability assessment of overhead cranes using fault tree analysis integrated with Markov chain and fuzzy Bayesian networks. Mathematical Problems in Engineering. 2021;2021(1):6530541. [DOI:10.1155/2021/6530541]
27. Keyvani Brojeni M, Kheirandish Sarabi S, Vosoughi S, Souri B, Akbarzadeh Miandoab F, Moradi Hanifi S. QUANTITATIVE RISK ASSESSMENT OF A CARBON DIOXIDE STORAGE TANK BY USING CONSEQUENCE MODELING AND FUZZY BAYESIAN NETWORKS. Iran Occupational Health. 2025;22(1):0-.
28. Abbasi Kharajou B, Ahmadi H, Rafiei M, Moradi Hanifi S. Quantitative risk estimation of CNG station by using fuzzy bayesian networks and consequence modeling. Scientific Reports. 2024;14(1):4266. [DOI:10.1038/s41598-024-54842-y] [PMID] []
29. Kwak H, Kim M, Min M, Park B, Jung S. Assessing the Quantitative Risk of Urban Hydrogen Refueling Station in Seoul, South Korea, Using SAFETI Model. Energies. 2024;17(4):867. [DOI:10.3390/en17040867]
30. Toungsetwut M. Analytical Methods for Risk Assessment and reduction of the uncertainty: University of Stavanger, Norway; 2012.
31. Chin SL, Nor SHM, Al-Shanini A, Ahmad A. OPERATIONAL RISK ANALYSIS FOR UNDESIRED POLYMERIZATION IN OVERHEAD CONDENSER OF BUTADIENE COLUMN. Jurnal Teknologi. 2016;78(8-3). [DOI:10.11113/jt.v78.9564]
32. Ramezanifar E, Gholamizadeh K, Mohammadfam I, Mirzaei Aliabadi M. Risk assessment of methanol storage tank fire accident using hybrid FTA-SPA. PLoS one. 2023;18(3):e0282657. [DOI:10.1371/journal.pone.0282657] [PMID] []
33. Pouyakian M, Azimi HR, Patriarca R, Keighobadi E, Fardafshari M, Hanifi SM. Application of Functional Resonance Analysis and fuzzy TOPSIS to identify and prioritize factors affecting newly emerging risks. Journal of Loss Prevention in the Process Industries. 2024;91:105400. [DOI:10.1016/j.jlp.2024.105400]
34. Khakzad N, Khan F, Amyotte P. Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network. Process Safety and Environmental Protection. 2013;91(1-2):46-53. [DOI:10.1016/j.psep.2012.01.005]
35. Chang Z, He X, Fan H, Guan W, He L. Leverage Bayesian network and fault tree method on risk assessment of LNG maritime transport shipping routes: Application to the China-Australia route. Journal of Marine Science and Engineering. 2023;11(9):1722. [DOI:10.3390/jmse11091722]
36. Satiarvand M, Orak N, Varshosaz K, Hassan EM, Cheraghi M. Providing a comprehensive approach to oil well blowout risk assessment. Plos one. 2023;18(12):e0296086. [DOI:10.1371/journal.pone.0296086] [PMID] []
37. Nazari S, Karami N, Moghadam H, Nasiri P. Consequence analysis of BLEVE scenario in the propane tank: ACase study at Bandar Abbas gas condensate refinery of Iran. International Journal of Scientific Engineering and Technology. 2015;4(9):472-5. [DOI:10.17950/ijset/v4s9/904]
38. Hanna S, Britter R, Leung J, Hansen O, Sykes I, Drivas P, editors. Source emissions and transport and dispersion models for toxic industrial chemicals (tics) released in cities. Eighth Symposium on the Urban Environment, Room, Italy; 2009.
39. Hanifi SM, Omidi L, Moradi G. Risk calculation and consequences simulation of natural gas leakage accident using ALOHA software. Journal of Health & Safety at Work. 2019;9(1).
40. Hanna S, Dharmavaram S, Zhang J, Sykes I, Witlox H, Khajehnajafi S, et al. Comparison of six widely‐used dense gas dispersion models for three recent chlorine railcar accidents. Process Safety Progress. 2008;27(3):248-59. [DOI:10.1002/prs.10257]
41. Mazzola T, Hanna S, Chang J, Bradley S, Meris R, Simpson S, et al. Results of comparisons of the predictions of 17 dense gas dispersion models with observations from the Jack Rabbit II chlorine field experiment. Atmospheric Environment. 2021;244:117887. [DOI:10.1016/j.atmosenv.2020.117887]
42. Pouyakian M, Ashouri M, Eidani S, Madvari RF, Laal F. A systematic review of consequence modeling studies of the process accidents in Iran from 2006 to 2022. Heliyon. 2023;9(2). [DOI:10.1016/j.heliyon.2023.e13550] [PMID] []
43. Leoni L, De Carlo F, Paltrinieri N, Sgarbossa F, BahooToroody A. On risk-based maintenance: A comprehensive review of three approaches to track the impact of consequence modelling for predicting maintenance actions. Journal of Loss Prevention in the Process Industries. 2021;72:104555. [DOI:10.1016/j.jlp.2021.104555]
44. Gonçalves B, Sá M, Azevedo R. Hazard and operability (HAZOP) study: A systematic process to identify potential hazards and operability problems. Occupational Safety and Hygiene III: CRC Press; 2015. p. 217-22. [DOI:10.1201/b18042-43]
45. Ahlert RC. Guidelines for consequence analysis of chemical releases. Center for Chemical Process Safety, American Institute of Chemical Engineers (AIChE), New York, NY,(1999,) 320 Pages,[ISBN No.: 0‐8169‐0786‐2], US. List Price: $129.00. Wiley Online Library; 2000. [DOI:10.1002/ep.670190304]
46. Topalis P, Korneliussen G, Hermanrud J, Steo Y, editors. Risk based inspection methodology and software applied to atmospheric storage tanks. Journal of Physics: conference series; 2012: IOP Publishing. [DOI:10.1088/1742-6596/364/1/012125]
47. Shahani NM, Sajid MJ, Zheng X, Jiskani IM, Brohi MA, Ali M, et al. Fault tree analysis and prevention strategies for gas explosion in underground coal mines of Pakistan. Mining of Mineral Deposits. 2019. [DOI:10.33271/mining13.04.121]
48. Lees F. Lees' Loss prevention in the process industries: Hazard identification, assessment and control: Butterworth-Heinemann; 2012.
49. Asghari B, Omidvari M. Probability assessment of chemical liquid release at floating roof storage tank in the oil refinery by fuzzy fault tree analysis. Iran Occupational Health. 2018;15(4):8-20.
50. Signoret J-P, Leroy A, Signoret J-P, Leroy A. Fault tree analysis (FTA). Reliability Assessment of Safety and Production Systems: Analysis, Modelling, Calculations and Case Studies. 2021:209-25. [DOI:10.1007/978-3-030-64708-7_16]
51. Lavasani SM, Yang Z, Finlay J, Wang J. Fuzzy risk assessment of oil and gas offshore wells. Process Safety and Environmental Protection. 2011;89(5):277-94. [DOI:10.1016/j.psep.2011.06.006]
52. Rajakarunakaran S, Kumar AM, Prabhu VA. Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station. Journal of Loss Prevention in the Process Industries. 2015;33:109-23. [DOI:10.1016/j.jlp.2014.11.016]
53. Saaty TL, Ozdemir MS. Why the magic number seven plus or minus two. Mathematical and computer modelling. 2003;38(3-4):233-44. [DOI:10.1016/S0895-7177(03)90083-5]
54. Omidvari M, Lavasani S, Mirza S. Presenting of failure probability assessment pattern by FTA in Fuzzy logic (case study: Distillation tower unit of oil refinery process). Journal of Chemical Health & Safety. 2014;21(6):14-22. [DOI:10.1016/j.jchas.2014.06.003]
55. Yazdi M, Kabir S. A fuzzy Bayesian network approach for risk analysis in process industries. Process safety and environmental protection. 2017;111:507-19. [DOI:10.1016/j.psep.2017.08.015]
56. Fazli Z, Laal F, Keighobadi E, Ebrahimi H, Medvari RF, Hanifi SM. Quantitative Risk assessment of Gasoline Storage Tank Farm Unit using by Fuzzy Set Theory and Consequence modeling. Iran Occupational Health. 2024;20(2):0-. [DOI:10.61186/ioh.20.2.18]
57. Renjith V, Madhu G, Nayagam VLG, Bhasi A. Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation. Journal of hazardous materials. 2010;183(1-3):103-10. [DOI:10.1016/j.jhazmat.2010.06.116] [PMID]
58. Hanifi SM, Laal F, Ghashghaei M, Mandali H. Providing a model to evaluate the spread of fire in a chemical warehouse using numerical simulation and Bayesian network. Process Safety and Environmental Protection. 2024;183:124-37. [DOI:10.1016/j.psep.2023.12.055]
59. Khodabakhsh Z, Omidi L, Dolatabad KM, Aleahmad M, Joveini H. Application of Bayesian networks in fire domino effects modeling in gasoline storage tanks area. Journal of Health & Safety at Work. 2024;14(3). [DOI:10.18502/jhsw.v14i3.18317]
60. Mohammadi H, Jafari MJ, Pouyakian M, Keighobadi E, Hanifi SM. Development of a new index for assessing the inherent safety level of chemical processes using a multi-criteria fuzzy decision-making approach. Journal of Loss Prevention in the Process Industries. 2024;87:105238. [DOI:10.1016/j.jlp.2023.105238]
61. Jones D, Berger S, editors. How to select appropriate quantitative safety risk criteria-applications from the center for chemical process safety (CCPS) guidelines on quantitative safety risk criteria. SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability?; 2010: SPE. [DOI:10.2118/127012-MS]
62. Das S, Roy K. A State-of-the-Art Review on FRF-Based Structural Damage Detection: Development in Last Two Decades and Way Forward. International Journal of Structural Stability and Dynamics. 2021;22. [DOI:10.1142/S0219455422300014]
63. Ouache R, Adham AAA. Reliability of Risk Assessment in Petrochemical Industries. International Journal of Industrial Management. 2015;1.
64. Jafari MJ, Zarei E, Badri N. The quantitative risk assessment of a hydrogen generation unit. international journal of hydrogen energy. 2012;37(24):19241-9. [DOI:10.1016/j.ijhydene.2012.09.082]
65. Kamaei M, Alizadeh SSA, Keshvari A, Kheyrkhah Z, Moshashaei P. Risk assessment and consequence modeling of BLEVE explosion wave phenomenon of LPG spherical tank in a refinery. Journal of Health and Safety at Work. 2016;6(2):10-24.
66. Pang M, Zhang Z, Zhou Z, Li Q. Risk Diagnosis Analysis of Ethane Storage Tank Leakage Based on Fault Tree and Fuzzy Bayesian Network. Applied Sciences (2076-3417). 2025;15(4). [DOI:10.3390/app15041754]
67. Ni X, Yang B, Xu J. Application of SAFETI in the Analysis of Natural Gas Pipeline Leakage Accident. ICPTT 2011: Sustainable Solutions For Water, Sewer, Gas, And Oil Pipelines1770. p. 1761-70. [DOI:10.1061/41202(423)186]
68. Aliabadi MM, Ramezani H, Kalatpour O. Quantitative Risk Assessment of Condensate Storage Tank, Considering Domino Effects. Journal of Health & Safety at Work. 2022;12(1).
69. Frank W, Jones D. Choosing appropriate quantitative safety risk criteria: Applications from the new CCPS guidelines. Process Safety Progress. 2010;29(4):293-8. [DOI:10.1002/prs.10404]
70. Kharajou BA, Rafiei M, Ahmadi H, Hanifi SM. Quantitative Assessment of Domino Effects of The Explosion at The North-west Station of Tehran District Six Using Consequence Modeling And GIS.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
