INTEGRATED GENETIC‑DIFFERENTIAL EVOLUTION APPROACH FOR SIMULTANEOUS PRESSURE‑DROP REDUCTION AND EFFICIENCY ENHANCEMENT IN MULTI‑CYCLONE DUST COLLECTORS
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Abstract
This study shows how to “hit two targets with one math arrow”, trimming pressure drop (ΔP) down while cranking collection efficiency (η) up in industrial multi cyclone (MSC) dust collectors. A CFD based response surface “crystal ball” is hitched to a tag team optimizer-Genetic Algorithm leads, Differential Evolution finishes-then polished by an NSGA II Pareto “red carpet” filter. The quartet of tweakable dimensions (barrel diameter D, inlet width B, cone length Lc, vortex finder diameter Dv) forms the playground. The GA→DE relay squeezes the composite score from J=1.00 to J=0.17, slicing ΔP by 32% and boosting η by 9%. For a medium sized plant the makeover shaves roughly 14 MWh year⁻¹ of fan energy-about 11 t CO₂ that never see daylight-proving that a little mathematical wizardry can make cyclones spin greener and leaner.
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