Analysing the effects of liquefaction on capsizing through integrating interpretive structural modelling (ISM) and fuzzy Bayesian networks (FBN)

Abstract

The main purpose of this research is to analyse the effect of cargo liquefaction on the capsizing of bulk carriers through an integrated model. To do this, initially, an interpretive structure modelling (ISM) was carried out to construct the relationship hierarchy of risk factors while a fuzzy Bayesian networks (FBN) were conducted to quantify impact level. The results revealed that liquefaction and improper actions to upright, among 19 factors, have a significant effect on capsizing. The findings also emphasize that the factors (improper loading (29%), lack of cargo care at sea (27.4%) and insufficient knowledge (22%)) arising from human error play an important role in cargo liquefaction. Unlike experimental researches in the literature, this research analyses the liquefaction risk and the other basic causes resulting from the capsizing of bulk carriers using an integrated risk assessment method. For further researches, it is recommended to consider other risk identification and assessment models for better results.