Macroscale Modelling of Pressure Drop for a Moulded Cylindrical Filter within a Vacuum Pump to Predict Aerosol Loading

Nausheen Mehboob Basha, Lloyd Cochrane, Faik Hamad

Research output: Contribution to journalArticlepeer-review

Abstract

Computational Fluid Dynamics (CFD) is used as a tool to predict the oil aerosol loading on filters moulded through ARTm® and are used in an oil-injected vacuum pump. These filters are essential for reducing exhaust emissions, which, when suspended can cause great harm to the environment, climate, equipment life and public health. However, flow characteristics in a coalescing filter are quite complex to solve using limited computational power. Therefore, an economically viable model is developed in ANSYS FLUENT with a customised algorithm to determine pressure drop and loading profile across a filter. Oil droplets entering the filter are treated as Rosin-Rammler distribution and are solved through Euler-Lagrangian approach. The developed algorithm is capable of predicting pressure drop with a lower discrepancy of 15% when compared with experimental data for two different flow rates. This model is then used to understand effect of flow characteristics on aerosol loading with resulting velocity ratio of 0.2 that will lead to even aerosol loading on filter media.
Original languageEnglish
Number of pages14
JournalAsia-Pacific Journal of Chemical Engineering
Publication statusAccepted/In press - 2020

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