Numerical simulation of two-phase gas and non-Newtonian shear-thinning fluid flows in pipelines

• Main Author: Jia, Ninghong
• Other Authors: Thompson, C. P.
• Language: en
• Published: Cranfield University 2015
• Online Access: http://dspace.lib.cranfield.ac.uk/handle/1826/9192

The one goal of this research is to present the adaptive mesh refinement (AMR) technique for one dimensional two-phase slug flows. Uniform fine meshes for these long devices are costly and, in general situations, the optimum space discretisation could not be determined a priori. The adaptive mesh refinement (AMR) procedure permits this problem to be remedied by refining the mesh locally, within regions where sharp discontinuities and steep gradients are present. With the appropriate algorithm and data organisation, it helps to reduce CPU time and speed up simulations of flows in long pipes, while preserving accuracy and acceptable execution times. The main objective of this research is to investigate the behaviour of the gas and non-Newtonian shear-thinning fluids in horizontal pipes. Predictions of drag reduction ratio and holdup are presented for the stratified flow of gas and non-Newtonian Ostwald-deWaele liquid. For slug flow regimes, the mechanistic slug unit model is adopted in order to estimate the pressure gradients along the slug unit. The slug unit model is rearranged and reinterpreted as inviscid Burgers’s equation for incompressible phases. For both stratified and slug flow regimes, three dimensional CFD (computational fluid dynamics) simulations were performed in order to compare the drag reduction ratio and pressure gradients. In stratified flows, CFD is also used in an attempt to evaluate the liquid wall friction factor and to compare the obtained values with those given by empirical standard correlations.The estimated pressure gradient and drag reductions are compared with experimental data. Calculations showed an excellent agreement between the simulation and experimental data. Shear thinning effects are also correctly modelled in this work.