Fluid flow in hydrocyclones optimized through multi-objective genetic algorithms

Chakraborti, N. ; Shekhar, A. ; Singhal, A. ; Chakraborty, S. ; Chowdhury, S. ; Sripriya, R. (2008) Fluid flow in hydrocyclones optimized through multi-objective genetic algorithms Inverse Problems in Science and Engineering, 16 (8). pp. 1023-1046. ISSN 1741-5977

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Official URL: http://www.tandfonline.com/doi/abs/10.1080/1741597...

Related URL: http://dx.doi.org/10.1080/17415970802166618


Transient swirl flow fields that exist in the hydrocyclone separators have been simulated using the CFD software FLUENT™. The outputs are treated in a multi-objective fashion using tailor-made evolutionary computing softwares developed in-house. The recently proposed ‘new multi-objective genetic algorithm’ developed at this research group is utilized for this purpose along with a multi-objective immune system algorithm. Using the simulated flow fields, attempts are made to simultaneously optimize two conflicting criteria: (i) the volume of the LZV (locus of zero vertical velocity) envelope that governs the extent of classification towards the overflow region and (ii) the overall pressure drop that drives the classification process towards the underflow. The resulting Pareto frontiers are computed and analysed.

Item Type:Article
Source:Copyright of this article belongs to Taylor and Francis.
Keywords:Flow Configuration; Hydrocyclone; NMGA; Pareto Frontiers; CFD; Genetic Algorithms; Multi-Objective Optimization
ID Code:100971
Deposited On:30 Dec 2016 11:54
Last Modified:30 Dec 2016 11:54

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