engines {bnRep} | R Documentation |
engines Bayesian Network
Description
A fuzzy Bayesian network risk assessment model for analyzing the causes of slow-down processes in two-stroke ship main engines.
Format
A discrete Bayesian network to assess the factors contributing to the engine's slow-down processes. The probabilities were given in the referenced paper. The vertices are:
- H1
Oil mist high density (yes, no);
- H2
Scavenge air box fire (yes, no);
- H3
Piston cooling oil non flow (yes, no);
- H4
Cylinder lube oil non flow (yes, no);
- H5
Cylinder cooling fresh water low pressure (yes, no);
- H6
Cylinder cooling fresh water high temperature (yes, no);
- H7
Main lube oil low pressure (yes, no);
- H8
Thrust pad high temperature (yes, no);
- H9
Piston cooling oil high temperature (yes, no);
- H10
Exhaust gas high temperature (yes, no);
- H11
Stern tube bearing high temperature (yes, no);
- H
(yes, no);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Bashan, V., Yucesan, M., Gul, M., & Demirel, H. (2024). A fuzzy Bayesian network risk assessment model for analyzing the causes of slow-down processes in two-stroke ship main engines. Ships and Offshore Structures, 19(5), 670-686.