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Coupling a simple and generic membrane fouling model with biological dynamics: application to the modeling of an Anaerobic Membrane BioReactor (AnMBR)

Authors :
Benyahia, B
Charfi, Asma
Heran, Marc
Cherki, B.
Kalboussi, N
Harmand, Jérome
Laboratoire d'Automatique de Tlemcen (LAT)
Université Aboubekr Belkaid - University of Belkaïd Abou Bekr [Tlemcen]
Laboratoire de Modélisation Mathématique et Numérique dans les Sciences de l'Ingénieur [Tunis] (LR-LAMSIN-ENIT)
Ecole Nationale d'Ingénieurs de Tunis (ENIT)
Université de Tunis El Manar (UTM)-Université de Tunis El Manar (UTM)
Institut Européen des membranes (IEM)
Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut de Chimie du CNRS (INC)-Université de Montpellier (UM)
Laboratoire de Biotechnologie de l'Environnement [Narbonne] (LBE)
Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Publication Year :
2020
Publisher :
HAL CCSD, 2020.

Abstract

A simple model is developed for membrane fouling, taking into account two main fouling phenomena: cake formation, due to attached solids onto the membrane surface and pores clogging, due to retained compounds inside the pores. The model is coupled with a simple anaerobic digestion model for describing the dynamics of an Anaerobic Membrane BioReactor (AnMBR). In simulations, we investigate its qualitative behavior: it is shown that the model exhibits satisfying properties in terms of flux decrease due to membrane fouling. Comparing simulation and experimental data, the model is shown to predict quite well the dynamics of an AnMBR. The simulated flux best fits the experimental flux with a correlation coefficient r^2 = 0.968 for the calibration data set and r^2 = 0.938 for the validation data set. General discussions are given on possible control strategies to limit fouling and optimize the flux production. We show in simulations that these strategies allow one to increase the mean production flux to 33 L/(h.m^2), whereas without control it was 18 L/(h.m^2).

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.dedup.wf.001..43a300cc36709f9c0738418184673b94