Abstract
Liquefied natural gas (LNG) is widely used, because it provides an easy and economic solution to the transport and storage of natural gas (NG), especially on long distances or when transport by pipeline is not viable. The LNG pool fire is one major process safety accident at the LNG facilities according to the report of the U.S. Government Accountability Office. Moreover, due to the high surface emissive power of LNG compared to other hydrocarbon fuels, LNG pool fires have a high potential in causing domino effects and cascading events in process industry. Previous studies developed Computational Fluid Dynamics (CFD) models of LNG pool fires, but the mass burning rate was fixed manually as a model input, not considering that the mass burning rate is determined by the fuel’s physical properties and heat input vaporizing the fuel. In this study, a model of LNG pool fire controlled by material physical properties was developed using fire dynamics simulator (FDS), and was validated against LNG pool fire experiments carried out by Mary Kay O’Connor Process Safety Center (MKOPSC). Statistical performance measurement shows that the model is superior to the semi-empirical approaches in predicting the mass burning rate of LNG pool fire under different pool sizes. A flame geometry analysis software was developed comparing different algorithms, and the centroid method was selected. The results show that the fire model (200 kW/m3 as flame contour) can accurately predict the flame geometry observed in the experimental runs. The influence of wind velocity and dike height on the mass burning rate was also investigated. The results show that the height of the concrete dike is negatively correlated with the mass burning rate of LNG pool fire. The effect of wind velocity on LNG mass burning rate is twofold. The forced convective boundary layer at lower wind velocity promotes LNG combustion and increases the mass burning rate, while higher wind velocities reduce the mass burning rate due to the reduction of the thermal radiation feedback. The findings in this study will contribute to an accurate risk assessment of LNG pool fire accidents in the process industry.
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