Combining 10 meta-heuristic algorithms, CFD, DOE, MGGP and PROMETHEE II for optimizing Stairmand cyclone separator
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- @Article{IZADI:2021:PT,
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author = "Ahad Izadi and Elham Kashani and Ali Mohebbi",
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title = "Combining 10 meta-heuristic algorithms, {CFD}, {DOE},
{MGGP} and {PROMETHEE} {II} for optimizing Stairmand
cyclone separator",
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journal = "Powder Technology",
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volume = "382",
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pages = "70--84",
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year = "2021",
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ISSN = "0032-5910",
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DOI = "doi:10.1016/j.powtec.2020.12.056",
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URL = "https://www.sciencedirect.com/science/article/pii/S0032591020312237",
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keywords = "genetic algorithms, genetic programming, Gas cyclone
separator, CFD simulation, Multi-gene genetic
programming, Multi-objective optimization, DOE,
PROMETHEE II",
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abstract = "Gas cyclone separators have been widely used in
different industries. In this study, to find the best
geometrical ratios of Stairmand cyclone separator,
computational fluid dynamics (CFD), design of
experiments (DOE), multi-gene genetic programming
(MGGP), and ten meta-heuristic algorithms were
combined. Six geometrical dimensions of the gas cyclone
separator including inlet height and width, vortex
finder length and its diameter, cylinder height and
cone-tip diameter were optimized. The obtained models
from MGGP were optimized by ten meta-heuristic
algorithms and non-dominated Pareto fronts were
analyzed using six unary and binary metrics and
PROMETHEE II as a decision making method. According to
the optimization results, multi-objective Particle
Swarm Optimization (MOPSO) showed the best performance
and generated more preferred designs than Stairmand
design compared to other algorithms. These preferred
designs increased the collection efficiency within 0.36
to 6percent and decreased the pressure drop within 3.3
to 27.5percent compared to the Stairmand",
- }
Genetic Programming entries for
Mohammad Izadi Khalegh Abadii
Elham Kashani
Ali Mohebbi
Citations