Adaptive mesh refinement for two-phase slug flows with an a priori indicator

The purpose of this paper is to present a novel adaptive mesh refinement AMR technique for computing unstable one dimensional two-phase flows in pipelines. In multiphase flows, the prediction and localisation of inter-facial waves, slugs and instabilities related to flow conditions under study require high levels of accuracy. This is more apparent in systems at industrial scales, where flow lines possess highly distorted regions and irregular topologies. m fine meshes for these long devices are costly and in general situations the optimum space discretisation could not be determined a priori. ve mesh refinement AMR procedure provides a remedy to this problem by refining the mesh locally, allowing to capture regions where sharp discontinuities and steep gradients are present. With appropriate algorithm and data organisation, AMR helps to reduce CPU time and speeds up simulations of flows in long pipes. The effectiveness of AMR methods relies on estimators that determine where refinement is required. We show in this work that for transient flows combining gradient-based error estimator with Kelvin–Helmholtz stability condition can improve the acceleration of computation and locate regions where refinements are required. The Kelvin–Helmholtz is a local condition and is an a priori indicator for the refinement.