International Journal on Engineering Applications (IREA) · 2018 · 16 citations · 17 references
EngineeringAerospace EngineeringComputational EngineeringComputational Fluid DynamicsDesign OptimizationFluid DynamicsComputational AerodynamicsCyclone SeparationGas-liquid SeparationGenetic AlgorithmsMultiphase Flow SimulationPressure Drop PredictionCyclone Geometry OptimizationCyclone Separator PerformanceGas-solid Flow ModelingGenetic Algorithm OptimizationPressure DropSeparator Performance ModelingTwo-phase Flow ModelingTwo-phase Flow Simulation
Several classical approaches for designing cyclone separators have been presented till today. Although these approaches have worked well in certain circumstances, they may not always lead to the best possible designs. This paper presents a robust performance optimization method for cyclone separators using genetic algorithm. The effects of seven geometrical design parameters on efficiency and pressure drop are investigated simultaneously. For calculating these performance characteristics, a gas- solid multiphase flow simulation is used to model the two-phase flow inside the cyclone. The proposed computational fluid dynamic model is employed to formulate the objective functions, which are the pre-requisite of genetic algorithm. The simultaneous optimizing of cyclone parameters reveals the profound effects of the conical height and slope, on both efficiency and pressure drop of cyclone separators. The results also show that by increasing the efficiency over 85 percent, pressure drop will be increased significantly.
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