Chemical Engineering Science 64 (2009) 775--786 Contents lists available at ScienceDirect Chemical Engineering Science journal homepage: www.elsevier.com/locate/ces Experimental validation studies on a multi-dimensional and multi-scale population balance model of batch granulation Jonathan M.-H. Poon a , Rohit Ramachandran a , Constantijn F.W. Sanders b , Thomas Glaser b,c , Charles D. Immanuel a, ∗ , Francis J. Doyle III b , James D. Litster d,1 , Frantisek Stepanek a , Fu-Yang Wang d , Ian T. Cameron d a Department of Chemical Engineering, Centre for Process Systems Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK b Department of Chemical Engineering, University of California at Santa Barbara, Santa Barbara, CA 93106, USA c Institute for Systems Theory and Automatic Control, University of Stuttgart, 70550, Germany d Particle and Systems Design Centre, School of Engineering, The University of Queensland, Brisbane 4072, Australia ARTICLE INFO ABSTRACT Article history: Received 15 November 2007 Received in revised form 14 July 2008 Accepted 20 August 2008 Available online 11 October 2008 Keywords: Granulation Multi-dimensional population balance Agglomeration Nucleation Mechanistic kernels Scale-up In this study, a dynamic model is presented for the granulation process, employing a three-dimensional population balance framework. As a first attempt to account for the multi-scale character of the process, the nucleation and aggregation kernels used in the population balance model are derived using mecha- nistic representations of the underlying particle physics such as wetting kinetics and energy dissipation effects. Thus, the fundamental properties of the powder and the liquid were used as parameters in the model to predict the granulator dynamics and granule properties. The population balance model is validated against experimental data from a calcite/PVOH–H 2 O recipe obtained using a lab-scale drum granulator for granule size, fractional binder content and porosity. A reasonably good agreement between experimental and simulation results were obtained for the granule size distribution under different ex- perimental conditions. In addition, accurate model predictions were made for the evolution of the average properties (i.e., size, fractional binder content and porosity) for various operating conditions. © 2008 Elsevier Ltd. All rights reserved. 1. Introduction Granulation is a particle agglomeration process of converting fine powdery solids into larger free-flowing agglomerates with the help of a liquid binder. It finds application in a wide range of industries (e.g. pharmaceuticals, fertilisers and minerals). Granulated products often have notable improvements compared to their ungranulated form and some of these include increased bulk density, improved flow properties and uniformity in the distribution of multiple solid components. Granulation processes have been ubiquitous in the in- dustry for many years, with significant research undertaken to gain insight into the underlying phenomena occurring during the pro- cess. However, industrial granulation processes are by-and-large op- erated in a highly inefficient manner with large recycle ratios within the process (3–4:1, recycle/product) (Iveson et al., 2001; Mort et al., 2001; Wang and Cameron, 2002). This motivates the need to provide an integrated process model, which will be a crucial aid for a more ∗ Corresponding author. Fax: +44 20 7594 6606. E-mail address: c.immanuel@imperial.ac.uk (C.D. Immanuel). 1 Current address: School of Chemical Engineering, Purdue University, West Lafayette, IN 47907-2100, USA. 0009-2509/$ - see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.ces.2008.08.037 efficient operation (Litster, 2003; Bardin et al., 2004; Knight, 2004; Mort, 2005). A comprehensive model of the process will enable an analysis of the system dynamics and the formulation of a suitable control strategy, which will in turn contribute to a more efficient op- eration of the process (Litster, 2003; Knight, 2004). This model-based approach is substantiated by the fact that plant-level experiments can be labour and capital intensive, making an experiment-based approach less suitable for investigating all facets of this complex dy- namic system. With current improvements in computer technology, computer simulations are becoming more amenable and provide a greater rationale for developing models that would facilitate the de- sign of granulation processes (Drechsler et al., 2005). The granulation process is an example of a multi-scale problem and the multi-scale nature of this process is summarised in Fig. 1. Micro-scale phenomena such as the wetting kinetics and energy dissipation effects (which are reflected in binder addition and mix- ing rates) directly influence the meso-scale phenomena (nucleation, aggregation, consolidation and breakage), which in turn directly de- termine the macroscopic properties such as granule size. The micro- scale properties themselves are influenced by fundamental material properties, both of the solid and the liquid. Detailed experimentation was performed in order to verify the link between the fundamental properties and operating variables on the one hand and the end