LNG vapour cloud dispersion modelling and simulations with OpenFOAM

Growth in demand for Liquefied Natural Gas (LNG) has increased calls for further research and development on LNG production and safer methods for its transportation. This paper presents the implementation of numerical models for dispersion of evaporated LNG in the open atmosphere. The developed model incorporates in its formulation LNG spill and pool formation into a source model. It is then coupled with a Computational Fluid Dynamics (CFD) approach in OpenFOAM for dispersion calculations. Atmospheric conditions such as average wind speed and direction were used to resolve wind boundary layers. The model also accounts for the humidity effect and its influence on air-density and buoyancy change. Verifications have been conducted using the experimental results from Maplin Sands series of tests by comparing the maximum evaporated gas concentration in every arc in relation to the release point. The results show good agreements between the model’s predictions and experiments

LNG vapour cloud dispersion modelling and simulations with OpenFOAM

Growth in demand for Liquefied Natural Gas (LNG) has increased calls for further research and development on LNG production and safer methods for its transportation. This paper presents the implementation of numerical models for dispersion of evaporated LNG in the open atmosphere. The developed model incorporates in its formulation LNG spill and pool formation into a source model. It is then coupled with a Computational Fluid Dynamics (CFD) approach in OpenFOAM for dispersion calculations. Atmospheric conditions such as average wind speed and direction were used to resolve wind boundary layers. The model also accounts for the humidity effect and its influence on air-density and buoyancy change. Verifications have been conducted using the experimental results from Maplin Sands series of tests by comparing the maximum evaporated gas concentration in every arc in relation to the release point. The results show good agreements between the model’s predictions and experiments