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Dynamic risk assessment of storage tank using consequence modeling and fuzzy Bayesian network
Heidar Mohammadi1, Fereydoon Laal2, Farough Mohammadian3
1Department of Occupational Health and Safety, School of Health, Larestan University of Medical Sciences, Larestan, Iran.
Heliyon
|August 18, 2023
Summary
Dynamic risk assessment of tank storage using integrated Bow Tie (BT) and Bayesian Network (BN) methods reveals unacceptable risk levels. This approach enhances objectivity in accident prevention and emergency preparedness for process industries.
Area of Science:
- Process Safety Engineering
- Risk Management
- Industrial Accident Analysis
Background:
- Process industries face significant annual losses due to accidents.
- Modern risk assessment methods are crucial for accident prevention.
- Traditional methods may lack the objectivity needed for dynamic risk assessment.
Purpose of the Study:
- To perform dynamic risk assessment of tank storage using modern methods.
- To compare modern methods with traditional risk assessment approaches.
- To enhance accident prevention strategies through objective risk evaluation.
Main Methods:
- Utilized the Bow Tie (BT) method for analyzing leakage events and consequences.
- Employed Bayesian Network (BN) method to update consequence probability rates.
- Modeled release scenarios and outcomes using ALOHA software (version 5.4).
Main Results:
- Identified 50 basic events contributing to chemical leakage.
- Pool fire was the most probable consequence of chemical leakage in both BT and BN models.
- Leakage diameter significantly impacts emission rates, with a 50mm leak showing the highest rate (80 kg/min).
Conclusions:
- The integrated BT, Fuzzy Bayesian Networks, and consequence modeling approach provides more objective risk assessment results.
- Estimated risk numbers for the analyzed scenarios fall within the unacceptable range.
- Outcome modeling results can guide accident prevention and emergency preparedness efforts in tank storage facilities.
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