Integrating activated sludge floc size information in MBR fouling modeling.

Although studied extensively, modeling fouling phenomena in membrane bioreactors (MBRs) remains challenging. It has been well established that cake layer formation and pore blocking have a strong impact on the filtration performance but how to capture that in comprehensive models is not fully defined yet. Since it has been shown that bioflocculation characteristics of activated sludge have a clear link with (the extent of) membrane fouling, this study integrates activated sludge floc size (i.e., particle size distribution) information in the model for pore blocking and cake layer formation with a focus on constant flux operated MBRs. Based on these floc size distributions, a three-dimensional modeling and visualization of the cake layer is envisaged which can then provide the required input information (e.g., the porosity of the cake layer) for the fouling model. The model is calibrated and validated on the basis of experimental data from Hwang et al. (2012) in 'Membrane bioreactor: TMP rise and characterization of biocake structure using CLSM-image analysis' (see J. Membr. Sci. 419-420, 33-41).

Towards a low complexity carbon removal model for the optimal design of compact decentralised wastewater treatment systems.

On-site decentralised wastewater treatment systems can provide a financially attractive alternative to a sewer connection in locations far from existing sewer networks. Operational problems and shortcomings in the design of these systems still occur frequently. The aim of this paper is to provide a low complexity (i.e. easy to calibrate) but still accurate mathematical model that can be used to optimise the operational design of compact individual wastewater treatment systems. An integrated hydraulic and biological carbon removal model of a biofilm-based compact decentralised treatment system is developed. The procedure for drafting the model is generic and can be used for similar types of wastewater treatment systems since (i) the hydraulic model is based on an N-tanks-in-series model inferred from tracer test experiments and (ii) (biofilm) respirometry experiments are exploited to determine the biodegradation kinetics of the biomass. Based on the preliminary validation results of the integrated model, the carbon removal in the system can be predicted quite accurately. While some adjustments could further improve the modelling strategy, the here presented results can already assist the manufacturers of compact treatment systems in efficiently (re)designing their systems.

Use of image analysis for sludge characterisation: studying the relation between floc shape and sludge settleability.

This paper starts by presenting a fully automatic image analysis procedure for characterisation of flocs and filaments in activated sludge images. Thereafter the attention is directed towards the results of four lab-scale experiments, in which image information is related to sludge settleability in terms of sludge volume index. This relation is statistically confirmed by applying a principal component analysis to the data. In addition, the redundancy in the data sets is studied with regard to floc shape descriptors and the monitoring potential of image analysis is demonstrated by means of a multiple linear regression exercise.

Activated sludge image analysis system: monitoring settleability and effluent clarity.

A fully automized image analysis procedure is presented for fast and reliable characterization of the activated sludge composition. In previous research, relations between filament abundance and floc shape on the one hand, and the Sludge Volume Index on the other hand were sought. This work aims at demonstrating the use of the image analysis information as an indication for the amount of suspended solids in the effluent.

Monitoring activated sludge settling properties using image analysis.

The goal of this study is to develop a monitoring system for activated sludge properties, as this is an essential tool in the battle against filamentous bulking. A fully automatic image analysis procedure for recognising and characterising flocs and filaments in activated sludge images has been optimised and subsequently used to monitor activated sludge properties in a lab-scale installation. The results of two experiments indicate that the image information correlates well with the Sludge Volume Index. It is shown that, at the onset of filamentous bulking, there is an increase in total filament length on the one hand, and a change in floc shape on the other hand.

Predicting the onset of filamentous bulking in biological wastewater treatment systems by exploiting image analysis information.

The performance of the activated sludge process is limited by the ability of the sedimentation tank (1) to separate the activated sludge from the treated effluent and (2) to concentrate it. Apart from bad operating strategies or poorly designed clarifiers, settling failures can mainly be attributed to filamentous bulking. Image analysis is a promising technique that can be used for early detection of filamentous bulking. The aim of this paper is therefore twofold. Foremost, correlations are sought between image analysis information (i.e., the total filament length per image, the mean form factor, the mean equivalent floc diameter, the mean floc roundness and the mean floc reduced radius of gyration) and classical measurements (i.e., the Sludge Volume Index (SVI)). Secondly, this information is both explored and exploited in order to identify dynamic ARX and state space-type models. Their performance is compared based on two criteria.