A NEW COMPUTATIONAL FLUID DYNAMICS STUDY OF A LIQUID-LIQUID HYDROCYCLONE IN THE TWO PHASE CASE FOR SEPARATION OF OIL DROPLETS AND WATER

Abstract

A liquid-liquid hydrocyclone, so-called de-oiling equipment, was investigated for separation of oil droplets and wastewater in an Iranian petroleum unit. To generate the geometry and the mesh of the hydrocyclone Gambit software was used. Afterwards, by taking advantage of the Euler-Lagrangian principle, the governing equations covering the motion of fluid and that of particles in the hydrocyclone were solved. Initially, it was shown that the outcomes of CFD are in agreement with experimental data, and then 15 hydrocyclones with different overflow diameters, overflow lengths and input velocities were employed for more detailed analyses. The separation process through a hydrocyclone is counted as an economical process when ther is not only a low pressure drop inside the hydrocyclone, but also a high separation efficiency. As a result, regarding the mentioned criteria, the optimum hydrocyclone, whereby the highest performance of the hydrocyclone is exploited, was obtained by applying the 15 sets of CFD data to a Neural Network (NN) and then by optimizing the function generated by the NN by means of a Genetic Algorithm (GA). The innovation of this research work is the three-phase modeling.

Keywords:
Liquid-liquid hydrocyclone; Optimization; RSM turbulent model; CFD