Natural gas (NG) is considered one of the cleanest fossils and is likely to become the second most widely used fuel after coal by 2035. The annual consumption of NG reached 4.04 trillion cubic meters in 2021 as the demand for NG is increasing continuously due to stringent environmental regulations. The supply of NG under cryogenic conditions reduced the volume by 600 times and provided a viable option for storage and handling. NG under cryogenic conditions is termed Liquefied Natural Gas (LNG) which is transported and stored under highly insulated tanks to prevent heat ingress from the surroundings. Heat ingress results in LNG evaporation, termed boil-off-gas (BOG) which increases the pressure inside the storage tank, and reliquefying BOG back to LNG is highly energy-intensive. This BOG generation poses a significant risk to tank integrity and safety, necessitating effective BOG management practices.
The BOG generation is very large during LNG storage, unloading and rollover in the receiving terminal. To characterize this, a Computational Fluid Dynamics (CFD) model of LNG storage tank has been developed. The primary difficulty lies in designing the storage tank, which proves challenging due to multiple inlets and outlets positioned at various locations. A 3D model of a storage tank offers better flexibility in modeling, but its computational cost and time are very high. Consequently, a 2D tank model is developed for the analysis. The positions of all inlets and outlets are assumed to be at the center of the tank in a concentric arrangement. Moreover, the research addresses a crucial yet underexplored aspect: understanding the impact of different parameters during LNG unloading on BOG generation within the storage tank. This unloading process generates significant amounts of BOG due to flashing during unloading operations and has been insufficiently investigated in prior studies. Hence, our research aims to bridge this knowledge gap by conducting a comprehensive investigation to gain deeper insights into these unloading phenomena and their associated implications on BOG generation. Using this model, we study the effect of various parameters, namely LNG density, initial LNG level, and storage tank operating pressure, on the rate of BOG generation. Further, both top and bottom unloading operations have been investigated. Our results suggest that during top unloading, the fluctuation of the rate of BOG generation is high due to flashing phenomenon. Also, the parametric study indicates that the tank’s operating pressure is a crucial to estimate rate of BOG generation.