Hybrid modeling of counterion mass transfer in a membrane-supported biofilm reactor

• Published in: Biochemical engineering journal Vol. 62; pp. 22 - 33
• Main Authors: Ricardo, Ana R., Oliveira, Rui, Velizarov, Svetlozar, Reis, Maria A.M., Crespo, João G.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 15.03.2012; Elsevier
• Subjects: Biodegradation; biofilm; Biofilms; Biological and medical sciences; Bioreactors; Biotechnology; drinking water; Fundamental and applied biological sciences. Psychology; ion exchange; Ion exchange membrane; mass transfer; mechanistic models; Membrane bioreactors; Methods. Procedures. Technologies; Modeling; multivariate analysis; nitrates; perchlorates; prediction; statistical models; Various methods and equipments; Water treatment; Biodegradation; Water treatment; Ion exchange membrane; Biofilms; Membrane bioreactors; Modeling; Membrane reactor; Bioreactor; Support; Biofilm; Hybrid; Mass transfer
• ISSN: 1369-703X; 1873-295X
• DOI: 10.1016/j.bej.2011.12.010

► Counterion transport in a membrane-supported biofilm reactor was modeled. ► Model was based on combining mechanistic and multivariate techniques. ► Two hybrid modeling strategies were tested: cooperative and competitive mixture-of-experts (MOE). ► MOE structure proved to be better: combines model elements in a mediated network. ► MOE characterized the bioprocess without the need of a complex kinetic model. This paper presents a hybrid mechanistic/statistical model for predicting counterion fluxes across an ion-exchange membrane in a membrane-supported biofilm reactor. The model was calibrated with operating data for the removal of nitrate and perchlorate from a simulated contaminated drinking water stream. Two different modeling strategies were tested: a cooperative parallel hybrid model and a competitive mixture-of-experts (MOE) structure both joining a mechanistic Donnan-dialytic transport model and a multivariate projection to latent structures (PLS) model. The MOE structure proved to be a better predictive tool since it combines the two hybrid model elements in a mediated network. The PLS model was used to identify the process variables that are responsible for the mechanistic model inaccuracy. The results showed that biocompartment physicochemical data need to be considered in the modeling of the transport of counterions across the membrane, especially in situations in which the target counterion (e.g., perchlorate or nitrate) is metabolically reduced in the biocompartment. By using this strategy, the complex biofilm contribution to the transport was accounted for, without the need of developing mechanistic models built on simplified and/or inaccurate assumptions.