Search

Among the various methods for the solution of population balances (PB) equations, the moments based methods are some of the most successful and popular. Moment based methods have demonstrated advantages such as reduced computational effort especially for applications that couple population balance (PB) simulation with computational fluid dynamics (CFD). The methods, however, suffers from two main drawbacks: the inability to yield the number density directly and limitation to system models that only consider size independent growth expression and certain breakage and aggregation kernels. This article presents an extension to the standard MOM (SMOM), the extended method of moment (EMOM), which not only allows the prediction of the number density directly in most cases, but also makes it applicable to systems with size dependent growth and any particle aggregation and breakage kernels. The method is illustrated and tested by reference to case studies that were well studied systems in the literature.

Crystallization modelling is limited by the availability of methods to reliably predict mixing, temperature and concentration distributions, supersaturation, nucleation and growth kinetics for crystallization systems of industrial size. A new software environment for modelling batch cooling crystallization has been developed integrating crystallization and fluid dynamics. The mathematical model can reliably predict mixing in stirred vessels of a given geometry and its effect on the crystallization kinetics and crystal product properties thus reducing the cost and time required for the design and scale-up of industrial crystallizers. The paper describes the development and application of crystSim for modelling industrial crystallization in stirred tanks. The software is developed in Visual C# making full use of Object Oriented Programming (OOP) and multithreading.