Design of vortex-based cavitation devices/reactors: influence of aspect ratio, number of inlets and shape
Vortex-based hydrodynamic cavitation devices are being used in a wide range of applications. However, adequate information on the design of such devices is not available. In this work, we have computationally investigated the influence of key design parameters such as the aspect ratio of the vortex chamber, the number of tangential inlets and the shape of the device on resulting flow characteristics and cavitation. Experiments were carried out to validate key findings from the computational studies. These investigations revealed that the aspect ratio of the vortex chamber as six may be considered as optimum. The performance of single and multiple inlet devices was found to be comparable at the same pressure drop (that is at same energy consumption per m3 ). Scale-up with a geometric similarity led to a reduction in the extent of cavitation for same energy consumption per m3 . For facilitating scale-out option, an attempt was made to simplify the configuration of the vortex-based cavitation device. Computational results indicated that the cavitation performance of simplified configuration was not significantly inferior. A case of the formation of liquid–liquid emulsion was taken as a test case for evaluation of a modified cavitation device based on the present investigations. The droplet size distributions of emulsions generated by both the devices indicate that the proposed simplified configuration, which may facil?itate fabrication and offer integrated scale-out options, performs almost at par with a complex configuration. The presented results will be useful for optimising designs of vortex-based hydrodynamic cavitation devices/ reactors.
Factory in a Box for Personalised Products based on Emulsions [FabPRO]
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PublicationUltrasonics Sonochemistry, 2023, 101, 106695
Other Funding informationThe authors greatly acknowledge the support provided by ANSYS for CFD licence under an academic partnership programme. The authors greatly acknowledge financial support from Science Foundation Ireland (SFI Project ID: 20/FFP-A/8518) and access to LDA established under SFI Infra-structure grant (NaPRO). The authors also acknowledge the Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.
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- Bernal Institute
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