Markov models for mixing of powders in static mixers

Abstract

Mixing of powders is important in many different industries as it adds significant value to the product. The research on this operation in industry goes through simulation of continuous mixing and mixing in general. The objective of this thesis is a development of a unified model representing samples of the particulate flow in different types of static mixers operating with materials that tend to segregate. One and two dimensional models of static mixers based on the theory of Markov chains are developed and the procedure of model parameter identification is proposed. The results of simulation have shown how the value of transition probabilities and initial distribution of the components influence mixture quality. The experimental results have proved the adequacy of the developed models. It has been shown that there is an optimum number of material passages through the mixer that gives maximal mixture quality while mixing components that tend to segregate.