Quantitative risk estimation of CNG station by using fuzzy bayesian networks and consequence modeling.
An object of class bn.fit. Refer to the documentation of bnlearn for details.
A discrete Bayesian network for risk assessment in compressed natural gas (CNG) stations. The probabilities were given within the referenced paper. The vertices are:
Not up-to-date technology (T, F);
Lack of maintenance (T, F);
Unsafe equipment (T, F);
Type of ignition material (T, F);
The nature of the chemical substance (T, F);
Inspection defect in wear detection (T, F);
Improper use of the equipment (T, F);
Leakage (T, F);
High temperature (T, F);
Low temperature (T, F);
Horizontal wind speed (T, F);
Vertical wind speed (T, F);
Environmental stability and instability (T, F);
Sunny hours (T, F);
Relative humidity and evaporation rate (T, F);
Lighting (T, F);
Landslide (T, F);
Flood (T, F);
Earthquake (T, F);
Land settlement (T, F);
Deliberate vandalism (T, F);
Incidents related to the missile site (T, F);
Military attack (T, F);
Explosion of other equipment (T, F);
Deliberate error in the execution of the recipe (T, F);
Accidental collision valves (T, F);
Failure to issue a work permit (T, F);
Artificial lighting (T, F);
Natural lighting (T, F);
Lack of cost (T, F);
Requirements for conducting training classes by managers (T, F);
Fatigue (T, F);
Shift work (T, F);
Stress - internal causes) (T, F);
Stress - external causes (T, F);
Not having enough experience and skills (T, F);
Hearing loss - non-occupational causes (T, F);
Hearing loss - occupational causes (T, F);
Failure to notify the control room in time (T, F);
Fear of explosion and fire by operator (T, F);
Operator performance - temperature and humidity (T, F);
Chemical pollutants - particles (T, F);
Chemical pollutants - gas and steam (T, F);
Solid waste (T, F);
Liquid waste (T, F);
Adjacent commercial use (T, F);
Adjacent residential use (T, F);
Adjacent industrial use (T, F);
Land uses changes (T, F);
Room metering - measurement of changes (T, F);
Room metering - operator error (T, F);
Lack of standard dryer quality (T, F);
Disturbance in the electricity flow of the dryer (T, F);
Fire dryer heaters (T, F);
Leakage of tank (T, F);
Adjacent tanks (T, F);
Dispenser leakage and damage (T, F);
Disregarding dispenser safety signs (T, F);
Dispenser malfunction (T, F);
Improper management performance (T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
(T, F);
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(T, F);
Abbasi Kharajou, B., Ahmadi, H., Rafiei, M., & Moradi Hanifi, S. (2024). Quantitative risk estimation of CNG station by using fuzzy bayesian networks and consequence modeling. Scientific Reports, 14(1), 4266.