INTEGRATED GENETIC‑DIFFERENTIAL EVOLUTION APPROACH FOR SIMULTANEOUS PRESSURE‑DROP REDUCTION AND EFFICIENCY ENHANCEMENT IN MULTI‑CYCLONE DUST COLLECTORS

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 L_c, vortex‑finder diameter D_v) 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.