Kernel identification in continuous fluidized bed spray agglomeration from steady state data

Fluidized bed spray agglomeration is an important industrial particle formation process. In particular, the continuous operation mode is able to provide a constant stream of product particles with constant quality in terms of particle properties. Mathematical process modeling represents a valuable tool for a thorough analysis of the involved mechanistic processes and can further be used for process intensification and control. Sophisticated models describing the quantitative effect of process conditions on particle properties are particularly important. Therefore, in this contribution the influence of the seven most important operational parameters on the particle size distribution is modeled, including fluidization and binder properties. To this end, a population balance process model with the three-parametric Kapur kernel is fitted to experimental data. The first main result of this contribution is the quantitative description of the dependency between the agglomeration rate and the process conditions by multidimensional paraboloids. The second main result is the introduction of a general method by which this quantitative formulation is obtained. (c) 2021 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).

Automated summary

Fluidized bed spray agglomeration is a significant industrial particle formation process, and mathematical process modeling plays a crucial role in analyzing mechanistic processes, intensification, and control. This study focuses on the influence of seven operational parameters on particle size distribution and introduces a general method for obtaining a quantitative formulation of the dependency between agglomeration rate and process conditions.