A two-phase flow is the simultaneous flow of two materials with different states or phases (i.e. gas, liquid, or solid). Particularly, two-phase flows consisting of solid particles within a liquid are ubiquitous in many engineering fields, such as mining, chemical, and oil & gas. The considerable technical and economic burden of laboratory tests is making the use of Computational Fluid Dynamics a challenging approach in recent years. Our research is devoted to the development of new computational methods for the prediction of the behavior of solid-liquid flows.
Specific topics regarding this area are:
A slurry is a solid-liquid mixture with very high solid loading (up to 50%). These flows are frequently encountered in the mining industry, where slurry pipelines are used to transport the mineral concentrate to a mining processing plant near a mine. Other applications involving these flows are the CHOPS processes in the oil&gas industry and the fluidized beds in the chemical industry. The modeling of slurry flows is particularly complex as it must account properly for the interactions between the fluid and the particles, between the particles and the solid walls, and among the particles themselves. In our research group we are working at the development of new computational models for the simulation of slurry flows and, in general, solid-liquid mixtures at different solid loading.
The erosion consists of the removal of material from a surface subjected to the impingements of solid particles dragged by a fluid. The erosion is a very serious concern in the oil&gas industry, causing damages to the plants, high repair cost, and significant loss of income. The prediction of erosion requires the knowledge of the fluid dynamic properties of the abrasive particles at the time of their impingement against the eroding surface, but the considerable computational burden of the computational models currently used for determining these properties prevents (and even precludes) the possibility to estimate erosion in case of complex flows. Our research is aimed at developing innovative computational methods for overcoming these limitations, thereby allowing erosion prediction with affordable computational cost.