| Autor: |
Rehman U; BIOMATH, Department of Mathematical Modelling, Statistics and Bio-Informatics, Ghent University, Coupure Links 653, Ghent 9000, Belgium E-mail: usman.rehman@ugent.be., Audenaert W; BIOMATH, Department of Mathematical Modelling, Statistics and Bio-Informatics, Ghent University, Coupure Links 653, Ghent 9000, Belgium E-mail: usman.rehman@ugent.be., Amerlinck Y; BIOMATH, Department of Mathematical Modelling, Statistics and Bio-Informatics, Ghent University, Coupure Links 653, Ghent 9000, Belgium E-mail: usman.rehman@ugent.be., Maere T; modelEAU, Département de génie civil et de génie des eaux, Université Laval, 1065 Avenue de la Médecine, Québec, QC, G1 V 0A6 Canada., Arnaldos M; BIOMATH, Department of Mathematical Modelling, Statistics and Bio-Informatics, Ghent University, Coupure Links 653, Ghent 9000, Belgium E-mail: usman.rehman@ugent.be; Acciona Agua S.A., R&D Department, Av. De les Garrigues 22, El Prat del Llobregat, Barcelona 08820, Spain., Nopens I; BIOMATH, Department of Mathematical Modelling, Statistics and Bio-Informatics, Ghent University, Coupure Links 653, Ghent 9000, Belgium E-mail: usman.rehman@ugent.be. |
| Abstrakt: |
Current water resource recovery facility (WRRF) models only consider local concentration variations caused by inadequate mixing to a very limited extent, which often leads to a need for (rigorous) calibration. The main objective of this study is to visualize local impacts of mixing by developing an integrated hydrodynamic-biokinetic model for an aeration compartment of a full-scale WRRF. Such a model is able to predict local variations in concentrations and thus allows judging their importance at a process level. In order to achieve this, full-scale hydrodynamics have been simulated using computational fluid dynamics (CFD) through a detailed description of the gas and liquid phases and validated experimentally. In a second step, full ASM1 biokinetic model was integrated with the CFD model to account for the impact of mixing at the process level. The integrated model was subsequently used to evaluate effects of changing influent and aeration flows on process performance. Regions of poor mixing resulting in non-uniform substrate distributions were observed even in areas commonly assumed to be well-mixed. The concept of concentration distribution plots was introduced to quantify and clearly present spatial variations in local process concentrations. Moreover, the results of the CFD-biokinetic model were concisely compared with a conventional tanks-in-series (TIS) approach. It was found that TIS model needs calibration and a single parameter set does not suffice to describe the system under both dry and wet weather conditions. Finally, it was concluded that local mixing conditions have significant consequences in terms of optimal sensor location, control system design and process evaluation. |
