Application of particulate models for industrial processes

Abstract

Abstract Two approaches for modeling and simulating gas phase processes with varying degrees of detail and computational effort are presented. The first example involves a single reactor used in the production of nonoscale particles, the second example deals with an entire spray granulation process producing particles in the millimeter range. In both cases particle size is an important measure for product quality. The aim of the work is to predict particle size distribution (PSD) and flows as a function of process and operation parameters. The reactor is simulated by means of computational fluid dynamics (CFD). Hereby, the computed flow and chemical species fields are used as input for a simulation of particle inception, growth and aggregation. Due to the complexity of the system quantitative results are prone to errors. However, the method is robust and the results for the particle field help understanding and explaining different aspects of the reactor and the aggregate particles produced. In spray granulation processes the PSD depends, very often in a complex manner, on process and/or material parameters. Moreover, process dynamics can also play an important role. Furthermore, the interaction and interconnection of different unit operations (granulators, mills, classifiers) is in the scope of interest, when the application of sophisticated models (as in the first case) is restricted or impossible due to computational limits. In this second example, a literature model for growth and abrasion (Heinrich et al. (2002)) is extended to breakage and implemented into Aspen Custom Modeler. In order to ensure a high flexibility of the model, the process is divided into several unit operations which can be arbitrarily combined within a flowsheet. The model is parameterized using plant measurements combined with suitable estimates and applied to industrial granulation processes. It can be utilized for process conception as well as for process optimization.