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S C F Meijer

Publications and source records attributed to S C F Meijer.

2 recordsLinked to original sources

Modelling the start-up of a full-scale biological phosphorous and nitrogen removing WWTP.

In this paper we simulated the start-up of a full-scale biological phosphorus and nitrogen removing (BPNR) wastewater treatment plant (wwtp). For the simulation we used a metabolic phosphorus model integrated in ASM2d, referred to as the Technical University Delft Phosphorus (TUDP) model. In a previous study it was shown that under steady state conditions the model is determined by stoichiometry rather than kinetics. To evaluate the kinetics of the metabolic biological phosphorus model, we recorded and simulated the start-up of a full-scale upgraded BPNR process. The initial state of the start-up was the simulated steady state of the process prior to the start-up. We could evaluate the SRT during the start-up on the basis of the accumulation of total-phosphorus in the sludge. During the start-up, the process changed from partly nitrifying to fully nitrifying, denitrifying and phosphate removing. Growth of PAO only showed sensitive for the glycogen formation rate kGLY. Disregarding a 20% in- or decrease of the kinetic rates of biological phosphorus removal (BPR), all start-up simulations converged to comparable steady states. This underlines that BPR is determined by stoichiometry rather than kinetics. Previous simulation studies with the TUDP-model showed that glycogen accumulated to unrealistic high concentrations with an increasing sludge retention time (SRT). We modelled the glycogen kinetics with a maximum glycogen fraction, which proved an effective and straightforward method to avoid unrealistic glycogen accumulation. In the steady state simulations, the glycogen concentration was determined by the value of the maximum glycogen fraction (fGLY(max)), whereas the overall sludge composition showed insensitive towards this parameter. Temperature appeared highly sensitive and therefore should not be neglected when modelling BPR.

Bioreactors↗

Error diagnostics and data reconciliation for activated sludge modelling using mass balances.

Research on activated sludge models is mainly directed towards the reliability and estimation of model coefficients. Model calculations however, rely heavily on accurate determination of operational conditions. Accurate measurement of operational conditions and mass flows is difficult, caused by large (full-scale) process flows and the absence of reliable measurements. Therefore operational data should be verified on (gross) errors before being implemented in model studies. Calibrating a model on erroneous mass flows leads to laborious calibration procedures and moreover, unjustified adaptation of the model (kinetic and stoichiometric) parameters. Gross error detection is possible when there are more measurements than strictly required to solve a system of linear conservation relations (mass balances). A simple method for error detection is evaluating the mass balance residuals. For over determined systems data accuracy can be improved using balancing methods (i.e. minimising balance residuals). This is referred to as data reconciliation. A reconciled data set contains fewer errors and is exactly in line with the mass balances of the system. In this paper we describe a method for gross error detection and data reconciliation. It is shown how data reconciliation improves the accuracy of the data set and how the use of a balanced data set simplifies the model calibration procedure. This is demonstrated on the basis of a modelling study of a full-scale WWTP.

Calibration↗