Multi-Objective Optimization of Cyclone Separators Based on Geometrical Parameters for Performance Enhancement

Abstract

The present study focuses on performing multi-objective optimization of the cyclone separator geometry to lower the pressure losses and enhance the collection efficiency. For this, six geometrical entities, such as the main body diameter of the cyclone, the vortex finder diameter and its insertion length, the cone tip diameter, and the height of the cylindrical and conical segment, have been accounted for optimization, and the Muschelknautz method of modeling has been used as an objective function for genetic algorithms. To date, this is one of the most popular mathematical models that accurately predicts the cyclone performance, such as the pressure drop and cut-off particle size. Three cases have been selected from the Pareto fronts, and the cyclone performance is calculated using advanced closure large-eddy simulation—the results are then compared to the baseline model to evaluate the relative improvement. It has been observed that in one of the models, with merely a 2% reduction in the collection efficiency and an increase of 12% in the cut-off particle size, more than a 43% reduction in pressure drop value was obtained (an energy-efficient model). In another model, a nearly 25% increment in the collection efficiency and a reduction of 42% in the cut-off particle size with a nearly 36% increase in pressure drop value were observed (a high-efficiency model).

Keywords

• cyclone separators
• genetic algorithms (GAs)
• large-eddy simulation (LES)
• Muschelknautz method of modeling (MM)