Separation modeling in rotating packed beds using Genetic programming method

In recent years, the high efficiency of dust removal from gases by Rotating Packed Beds has attracted the attention of various industries. However the design process of this equipment using experimental methods and their computational fluid dynamics simulations, Due to the complexity of these beds and the number of parameters affecting their efficiency, using experimental methods for design will be very costly and time-consuming. This research evaluated the performance of Genetic Programming method in modelling these beds. Based on this, with 561 experimental data and using genetic programming, various equations were developed to estimate the system's efficiency. Among the created models, an equation with the least complexity and the most accuracy was selected. Results showed that the obtained equation, with a correlation coefficient of 0.9714, a mean square error of 3.79 and a maximum percentage of error of 1.51, had high accuracy for the design of these Rotating packed beds. Sensitivity analysis of the selected equation was also conducted and the results showed that particle size, rotational speed and liquid flow rate would have the most positive effect on efficiency of these beds.