[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Intermolecular And Surface Forces

Inactivation credit of UV radiation for viruses, bacteria and protozoan (oo)cysts in water: a review.

Characterisation of aquatic humic and non-humic matter with size-exclusion chromatography--organic carbon detection--organic nitrogen detection (LC-OCD-OND).

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Studies in Surface Science and Catalysis

Mathematical models for the crystallisation process in pellet reactors have been developed during recent decades. In this paper, these models are extended with new insights in the pellet softening process. The diffusion of the supersaturated water to the pellet surface is included in the model and the fluidisation model of the bed is modified. The new model is calibrated in a pilot plant setup. Calibration results are validated in two different full-scale plants. The validation process shows that, even under basic process operation, the model can be used to identify a malfunctioning apparatus and identify undesired process conditions. For the normal situation the model gives satisfactory results in predicting fluidised bed porosity and water quality parameters such as calcium, pH, conductivity and m-alkalinity. The validated model is used to show that pellet size control in the reactor has significant influence on performance with respect to the water quality parameters. Maintaining the pellet size in the bottom of the reactor at 0.8 mm compared with 1.4 mm reduces the supersaturation of calcium carbonate in the water after the reactor by 50%, but increases the consumption of seeding material by 550%.

Dynamic modelling for optimisation of pellet softening

Good modelling practice increases the credibility and impact of the information and insight that modelling aims to generate. It is known to be crucial for model acceptance and it is a necessity to amass a long-term, systematic thorough knowledge base for both science and decision making. This paper shows how ten steps in model development and evaluation can also be applied to numerical modelling of drinking water treatment, using models of drinking water treatment processes of the Weesperkarspel treatment plant of Waternet. The Weesperkarspel plant consists of ozonation, pellet softening, biological activated carbon filtration and slow sand filtration. For the different processes models were developed that were used for operational improvements. The modelling resulted in new insights and knowledge about the treatment processes and improved operation of the processes. From scenario studies for the pellet softening it was concluded that chemical dosing can be diminished when by-pass ratio is increased and that pellet size can be controlled by measuring the difference in pressure guaranteeing fluidisation of the pellet bed. In addition, ozone dosage can be optimised by modelling ozone exposure, bromate formation and biologically degradable natural organic matter (NOM) under varying influent water quality.

Good modelling practice in drinking water treatment, applied to Weesperkarspel plant of Waternet

Integrating biological As(III) oxidation with Fe(0) electrocoagulation for arsenic removal from groundwater.

Possibilities for reuse of treated domestic wastewater in The Netherlands

Water treatment plants are in general robust and designs are based on the performance of individual processes with pre-set boundary conditions. It is assumed that an integral approach of the entire treatment plant can lead to more efficient operation. Taking into account the developments in sensoring, automation and computation, it is a challenge to improve quality and reliability of the treatment plants and to make maximal use of the installed infrastructure, postponing new investments. At Amsterdam Water Supply (AWS), the first steps have been taken to come to an integral dynamic model of the total water treatment plant and the use of this model as an instrument for integral control. The parameters influencing the performance of the water treatment process will be incorporated in an overall model evaluating the goal factors quality (good, constant and reliable), quantity, costs, environmental impact (low residuals level), redundancy and flexibility. For several individual processes at AWS models have already been developed during the last few years, like models for the ozone process, biological activated carbon filtration and pellet softening. For the final calibration and validation pilot reactors are automated and on-line data are collected. Criteria for evaluation are developed to realise an optimal control of the individual processes in interaction with the goal factors of the total treatment process.

Luuk C. Rietveld

Papers

Dynamic modelling for optimisation of pellet softening

Good modelling practice in drinking water treatment, applied to Weesperkarspel plant of Waternet

Integrating biological As(III) oxidation with Fe(0) electrocoagulation for arsenic removal from groundwater.

Possibilities for reuse of treated domestic wastewater in The Netherlands

Integrated operation of drinking water treatment plant at Amsterdam water supply