A dynamic compartmental model of a sequencing batch reactor (SBR) for biological phosphorus removal

Author:

Daneshgar Saba12ORCID,Borzooei Sina13,Debliek Lukas4,Van Den Broeck Elias4,Cornelissen Riet4,de Langhe Piet4,Piacezzi Cesare5,Daza Miguel5,Duchi Simon5,Rehman Usman5,Nopens Ingmar12,Torfs Elena126

Affiliation:

1. a BIOMATH, Department Data Analysis and Mathematical Modelling, Ghent University, Coupure Links 653, 9000, Ghent, Belgium

2. b CAPTURE, Centre for Advanced Process Technology for Urban Resource recovery (CAPTURE), Frieda Saeysstraat 1, 9000 Ghent, Belgium

3. c Swedish Environmental Research Institute, P.O. Box 210 60, Stockholm SE-100 31, Sweden

4. d Pantarein Water Bvba, Egide Walschaertsstraat 22 L, Mechelen 2800, Belgium

5. e AM-Team, Dendermondsesteenweg 48/1, Ghent 9000, Belgium

6. f modelEAU, Département de génie civil et de génie des eaux, Université Laval, 1045, avenue de la Médecine, Québec G1V 0A6, Canada

Abstract

ABSTRACT Bioreactors are usually modelled as continuous stirred tank reactors (CSTRs) or CSTRs connected in series (Tanks-In-Series configuration). In large systems with non-ideal mixing, such approaches do not sufficiently capture the complex hydrodynamics, leading to model inaccuracies due to the lumping of spatial gradients. Highly detailed computational fluid dynamics (CFD) models provide insight into complex hydrodynamics but are computationally too expensive for flow-sheet models and digital twin applications. A compartmental model (CM) can be a middle-ground by providing a more realistic representation of the hydrodynamics and still being computationally affordable. However, the hydrodynamics of a plant can be very different under varying flow conditions. Dynamic CMs can capture these changes in an elegant way. So far, the application of CMs has been limited mostly to continuous flow systems. In this study, a dynamic CM of a sequencing batch reactor (SBR) is developed for a bio-P removal process. The SBR comes with challenges for CM development due to its distinct operational stages. The dynamic CM shows significant improvements over the CSTR model (using the same biokinetic parameters) for dissolved oxygen and phosphate predictions reducing the need for model recalibration that can lead to over-fitting and limited extrapolation capability of the model.

Publisher

IWA Publishing

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