Closing Thoughts on the Proposition of Improving Drift Velocity Closure Relationship for Multiphase Flow Models

The accurate prediction of drift velocity is essential in the modelling of multiphase flow in pipelines.Efforts on enhancing the applicability and predictive capabilities of drift velocity closure relationship in multiphase flow models for both low and high viscous fluids are increasing to better design and manage equipment for the production and transportation of oil resources.This work therefore present recent efforts on the developments of drift velocity models using different approaches, including Artificial Neural Network.The predictive capabilities of the developed models were evaluated by comparing with results from experimental data and existing correlations by error analysis.The outcomes demonstrate that, in overall, the difference in predictions between the developed empirical models and the ANN model is insignificant.However, both models, in most cases, outperform some of the notable drift velocity models available in open literature.