Multi-object optimization study on the performance of gas cyclones based on heterogeneous condensation and turbulent agglomeration

Improving the separation efficiency of fine particles becomes more and more critical as environmental pollution aggravates. This study aims to investigate the effects of four key parameters on the performance of gas cyclones, including cyclone body height, particle concentration, initial supersaturation degree, and inlet temperature. Then, the two-way coupling numerical model, in which is the process of heterogeneous condensation and agglomeration for insoluble fine particles, was achieved by user defined function. On this basis, the response surface analysis method and multi-objective genetic algorithm were adopted to optimize the cyclone. The results show that when the particle concentration is less than 1000 mg/m³, the separation efficiency can reach above 95%. The initial supersaturation degree has the greatest effect on the separation efficiency and vapour consumption rate, while the cyclone body height is the most critical factor on the pressure drop. As the particle concentration increases, the separation efficiency decreases at first and then keeps almost stable. With the increase of inlet temperature, the separation efficiency is enhanced, and the pressure drop reduces. These research results can provide important guidance for the optimization and engineering application of this technology.