Coupling of CFD Simulations and Population Balance Modeling to Predict Brownian Coagulation in an Emulsion Polymerization Reactor

Abstract

In this study a framework consisting of a computational fluid dynamics simulation coupled to a population balance model for the modeling of emulsion polymerizations is proposed. The combined approach is used to understand the impact of changing length and time scales, as well as mixing conditions on the particle size distribution (PSD) of a polymer latex under different conditions. It is shown that the effect of agitation rate can have a profound impact on the distribution of ionic species in the reactor, and thus on the evolution of the PSD.

Mechanisms and conditions that affect phase inversion processes: A review

“…In the past few years, several attempts have been made to deepen the understanding of break-up and coalescence phenomena by combining computational fluid dynamics (CFD) and population balance models (PBM). [126][127][128][129][130][131][132][133] In these works, the spatial dependencies of the break-up and coalescence rates are incorporated by simulating the geometry in question with a proper mesh and solving the equations with a finite elements method or similar. This methodology results in a greater physical accuracy but demands higher computational costs.…”

Combining Morphological Population Balances with Face-Specific Growth Kinetics Data to Model and Predict the Crystallization Processes for Ibuprofen

“…Furthermore, the MPB models can be used for well-mixed systems and also hydrodynamic systems having inhomogeneous property distribution in the manufacturing units via either multi-zonal modelling techniques (e.g. [23][24][25] or fully coupling methods 23,26,27 .…”

“…Furthermore, the MPB models can be used for well-mixed systems and also hydrodynamic systems having inhomogeneous property distribution in the manufacturing units via either multizonal modeling techniques (e.g., refs 23−25) or fully coupling methods. 23,26,27 In this paper, the development and application of MPB modeling methodology for pharmaceutical crystallization processes is presented as a key component of an overall process route map based upon the first-principles predictive models that can be used for the digital design and control of pharmaceutical manufacturing processes 28 and, through this, for the more effective and personalized delivery of medicines to patients. Its relevance to pharmaceutical processes is highlighted through the application to crystallization processes integrating crystal morphology and growth kinetics with population balance through the MPB.…”

“…For the dissolution process, the deaggregation, deagglomeration, and face-specific dissolution mechanisms can control the effective and accurate release of API for precision drug delivery. Furthermore, the MPB models can be used for well-mixed systems and also hydrodynamic systems having inhomogeneous property distribution in the manufacturing units via either multizonal modeling techniques (e.g., refs − ) or fully coupling methods. ,, …”