A New Mass-Based Discretized Population Balance Model for Precipitation Processes: Application to Struvite Precipitation. (15th May 2019)

• Record Type: Journal Article
• Authors: Elduayen-Echave, B.; Lizarralde, I.; Larraona, G.S.; Ayesa, E.; Grau, P.
• Is Part Of: Water research. Volume 155(2019)
• Page Start: 26
• Page End: 41
• Publication Date: 2019-05-15
• Subjects: Population Balance Model -- Struvite Precipitation -- Sensitivity Analysis -- Identifiability Analysis; Water -- Pollution -- Research -- Periodicals; 363.7394
• DOI: 10.1016/j.watres.2019.01.047
• Languages: English
• ISSNs: 0043-1354

Abstract

Abstract: Mathematical models describing precipitation processes in one step need to be upgraded. Particle size distribution is a crucial variable and its inclusion in the modelling libraries is necessary if the technology wants to be optimized through simulation. With this objective, a mass based population balance model is presented in this contribution. The model has been constructed using a stoichiometric matrix and a kinetic vector and using mass as the internal coordinate, as it is usually done in wastewater treatment modelling. Identifiability of the parameters of the model was evaluated using a sensitivity and a collinearity analysis for six simulation case studies of struvite precipitation. In addition, parameters in the model were calibrated to represent data from two batch tests in the laboratory. The results of the analysis showed that the identifiability of the parameters depends on the available experimental data and explored scenarios. Identifiability of the parameters could be the reason behind the shifting parameter values describing mechanisms of precipitation in the literature. This contribution helps to understand the possibilities and limitations that the population balance model approach offer. Graphical abstract: Image 1 Highlights: A mass based population balance model is presented. The model is described with a stoichiometric matrix and a vector of kinetics. Sensitivity and identifiability were analyzed for the parameters of the model. The analysis can explain the shifting parameter values in the literature. The model is capable to reproduce experimental pH evolution and PSD in a reactor.