Slug flow is one of the most common flow patterns in multiphase oil/gas transport in pipelines. Due to its complexity, it poses numerous challenges to model development. Industrial slug flow models are one-dimensional and can give poor predictions in situations where the associated closures and simplifications are no longer valid. Computational Fluid Dynamics (CFD) facilitates high-resolution studies of slug flow dynamics by implementing multi-dimensional models. Understanding the physics of slug flow would help identify the main flow mechanisms to be modelled and enable the development of mechanistic slug flow models for commercial software.
In this thesis, a computational approach is developed. The front tracking method (FTM) (Tryggvason et al. 2001) and the phase field method (PFM) (Ding et al. 2007) are used to model long bubbles in slug flows. Results of the validation study show good agreement with DeBisschop et al. (2002), who performed simulations of long bubbles in two-dimensional channels in the creeping-flow limit. Their work is extended here to moderate Archimedes numbers (10 < Ar < 200). The effects of inertia, surface tension, viscosity and inclination angle on the terminal velocity and the shape of a long bubble in different flow conditions are investigated. Furthermore, the FTM is coupled with a discrete bubble tracking method (DBTM), which has resulted in a robust hybrid method to model small and large bubbles simultaneously in an Eulerian-Lagrangian fashion. The method allows the study of the interaction of the small bubbles with a long bubble. The work is extended further to three dimensions using the PFM. The validation study shows good agreement with the present two-dimensional numerical work. The geometry is converted from a square channel to a pipe to facilitate a more realistic simulation of slug flow in pipelines. This work will provide a rigorous basis for developing simplified models.