Consequence modeling and root cause analysis (RCA) of the real explosion of a methane pressure vessel in a gas refinery

The present study aimed to consequence modeling and root cause analysis of the real explosion of a methane pressure vessel in separation unit of a gas refinery in Iran. ology: This study was performed in a gas refinery in the south of Iran. The studied scenario was the actual scenario that occurred...

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Veröffentlicht in:Heliyon 2023-04, Vol.9 (4), p.e14628-e14628, Article e14628
Hauptverfasser: Khodadadi-Mousiri, Ahmad, Yaghoot-Nezhada, Ali, Sadeghi-Yarandi, Mohsen, Soltanzadeh, Ahmad
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Sprache:eng
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Zusammenfassung:The present study aimed to consequence modeling and root cause analysis of the real explosion of a methane pressure vessel in separation unit of a gas refinery in Iran. ology: This study was performed in a gas refinery in the south of Iran. The studied scenario was the actual scenario that occurred in the studied pressure vessel. Modeling of possible consequences was performed using PHAST 7.2 software. Also, the root causes analysis of the accident was performed using experts' brainstorming. At radii of 15 and 45 m, the radiation level reaches 12.5 and 4 kW/m2, respectively. In the late explosion worst-case, the vapor cloud explodes after reaching a distance of 20 m from the pressure vessel. At radii of 20 m, 25 m, and 150 m from the center of the explosion, the pressure reaches 0.2068, 0.1379, and 0.02068 bar, respectively. In the Early Explosion Overpressure, the acceptable pressure is obtained at a distance of 193 m. Moreover, in the Early Explosion Overpressure radiation, at radii of 28 m, 38 m, and 193 m, the pressure reaches 0.2068, 0.1379, and 0.02068 bar, respectively. The findings revealed that creating an appropriate risk management algorithm with a focus on consequence modeling can be an effective step towards reducing losses in the process industry. This results can create a novel insight in comparing the two reactive and proactive approaches and also reveal the effectiveness of consequence modeling in reducing the severity of risks. [Display omitted]
ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2023.e14628