Structural damage assessment of a 500-cbm LNG bunkering ship under jet fire release: a consequence modeling approach

Liquefied Natural Gas (LNG) is widely used because of its availability, however its cryogenic and flammable nature poses significant safety risks during transport, storage, and bunkering. Accidental releases can lead to jet fires, threatening personnel and structural integrity. This study investigates the effects of a jet fire on an LNG bunkering ship in a port environment using an integrated Computational Fluid Dynamics (CFD) and Finite Element (FE) approach. CFD simulations using OpenFOAM solver predict fire-induced temperature distributions within the vessel structure. The resulting heat flux data are mapped as thermal load profiles for FE structural analysis using a Random Forest machine learning model for structural assessment. A 3D-heat dose profile is developed to estimate injury probabilities in surrounding areas. The proposed framework integrates CFD, machine learning–based thermal load mapping, structural analysis, and personnel risk assessment, providing a comprehensive methodology to support safer LNG bunkering operations.