dustexplosion {bnRep} | R Documentation |
dustexplosion Bayesian Network
Description
Scenario derivation and consequence evaluation of dust explosion accident based on dynamic Bayesian network.
Format
A discrete Bayesian network for the accurate solution of scenario state probability. Probabilities were given within the referenced paper. The vertices are:
- AccidentDoNotOccur
(True, False);
- AccidentUnderControl
(True, False);
- BlastWavesThroughPipes
(True, False);
- BuildingDamage
(I, II, III, IV);
- Casualties
(I, II, III, IV);
- CombustibleDustAccumulates
(True, False);
- DirectEconomicLosses
(I, II, III, IV);
- DustAccumulationUnderControl
(True, False);
- DustCloudDisappearance
(True, False);
- DustExplosionIntensityCoefficient
(I, II, III, IV, V);
- EndOfRescue
(True, False);
- EnvironmentalImpact
(I, II, III, IV);
- EquipmentDamage
(I, II, III, IV);
- ExplosionPreventionMeasures
(True, False);
- ExtinctionOfSpark
(True, False);
- IgnitingTheDustCloud
(True, False);
- InitiateEmergencyResponse
(True, False);
- Misoperation
(True, False);
- NoExplosionControlMeasures
(True, False);
- OpenFireExtinguished
(True, False);
- PreventFurtherExpansion
(True, False);
- RestrictedSpace
(True, False);
- SparkDetectorExtinguishSparks
(True, False);
- SparkOccurence
(True, False);
- StrengthenDustControl
(True, False);
- TriggerSecondaryExplosion
(True, False);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Pang, L., Zhang, M., Yang, K., & Sun, S. (2023). Scenario derivation and consequence evaluation of dust explosion accident based on dynamic Bayesian network. Journal of Loss Prevention in the Process Industries, 83, 105055.