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.
| Mualliflar | Djurayev, Sherzod |
|---|---|
| Jurnal | Наманган муҳандисликтехнология институти илмийтехника журнали |
| Nashr sanasi | 2025-09-30 |
| Jild | 10 |
| Son | 3 |
| Betlar | 292-296 |
| Til | Ingliz |
| DOI | 10.61151/stjniet.v10i3.886 |
DOI: 10.61151/stjniet.v10i3.886 · Maqolaning asl sahifasi
Multi-cyclone, multi-objective optimisation, genetic algorithm, differential evolution, CFD–RSM, pressure drop, collection efficiency, Pareto front
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