Universitat Politècnica de Catalunya. Doctorat en Polímers i Biopolímers
Universitat Politècnica de Catalunya. Departament d'Enginyeria Química
Universitat Politècnica de Catalunya. Departament de Mecànica de Fluids
Universitat Politècnica de Catalunya. eb-POLICOM - Polímers i Compòsits Ecològics i Biodegradables
Universitat Politècnica de Catalunya. CDIF - Centre de Diagnòstic Industrial i Fluidodinàmica
2024-09-03
Computational fluid dynamics (CFD) modeling has emerged as a valuable tool for investigating complex processes like microencapsulation. This paper aims to validate the ability of CFD simulations to predict particle size distribution in a polymer microencapsulation process. The CFD modeling approach employed a Eulerian multiphase framework, incorporating a discrete population balance model to track the evolution of the droplet population. A realizable k-e turbulence model and a multiple reference frame strategy were utilized to capture the system’s flow dynamics. The results reveal that while the CFD simulations align well with experimental data at higher agitation speeds (>10,000 rpm), discrepancies arise at lower speeds (<7500 rpm), indicating a challenge in accurately capturing turbulent viscous regimes. Despite these challenges, the CFD model demonstrates robust predictive capabilities for droplet formation and distribution in microencapsulation processes, validated by error margins within the acceptable limits. The validated model can be used as a reliable tool to guide experimental efforts and optimize process parameters, contributing to an enhanced understanding and control of microencapsulation processes.
Peer Reviewed
Objectius de Desenvolupament Sostenible::12 - Producció i Consum Responsables
Postprint (published version)
Article
English
Àrees temàtiques de la UPC::Enginyeria química; Àrees temàtiques de la UPC::Enginyeria dels materials; Computational fluid dynamics; Microencapsulation; Cumulative probability distribution; Population balance models; Number density
Multidisciplinary Digital Publishing Institute
https://www.mdpi.com/2076-3417/14/17/7807
http://creativecommons.org/licenses/by-nc-nd/4.0/
Open Access
Attribution-NonCommercial-NoDerivatives 4.0 International
E-prints [72986]