Abstract
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.
Highlights
Hydrocyclone as a two-phase separator has a widespread application in the oil and mining industry (Samaelli et al, 2017)
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 by optimizing the function generated by the NN by means of a Genetic Algorithm (GA)
To find the pressure and velocity field inside the hydrocyclone, the Semi-Implicit pressure Linked Equations (SIMPLE) method associated to the Fluent 15 (ANSYS, 2017) solver was used for simulation
Summary
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. It was shown that the outcomes of CFD are in agreement with experimental data, and 15 hydrocyclones with different overflow diameters, overflow lengths and input velocities were employed for more detailed analyses. 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 by optimizing the function generated by the NN by means of a Genetic Algorithm (GA).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
