Pareto optimal design of square cyclone separators using a novel multi-objective optimization algorithm

In the present study, multi-objective optimization (MO) of square cyclones is performed in three steps. In the first step, the collection efficiency (η) and the pressure drop (Δp) in a set of square cyclone separators are numerically investigated using computational fluid dynamics techniques. In the...

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Bibliographic Details
Published in:Transactions of the Institute of Measurement and Control 2013-05, Vol.35 (3), p.289-300
Main Authors: Mahmoodabadi, MJ, Bagheri, A, Maafi, R Abedzadeh, Hoseini, GR
Format: Article
Language:English
Subjects:
Algorithms
Cyclones
Optimization techniques
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Summary:In the present study, multi-objective optimization (MO) of square cyclones is performed in three steps. In the first step, the collection efficiency (η) and the pressure drop (Δp) in a set of square cyclone separators are numerically investigated using computational fluid dynamics techniques. In the second step, two meta-models based on the evolved group method of data handling-type neural networks are obtained, for modelling of η and Δp with respect to geometrical design variables. Finally, a novel MO based on a combination of the particle swarm optimization, multiple-crossover and mutation operator is introduced. The proposed MO is applied to Pareto optimal design of square cyclones considering two conflicting objectives (η and Δp), based on the obtained polynomial neural networks. Furthermore, the proposed Pareto result is compared with that of Non-dominated Sorting Genetic Algorithm II.
ISSN:0142-3312
1477-0369
DOI:10.1177/0142331212444154