Measuring Floc Structural Characteristics

Jarvis, Peter; Jefferson, Bruce; Parsons, Simon A.

doi:10.1007/s11157-005-7092-1

Cited by 106 publications

(45 citation statements)

References 56 publications

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“…However, this method had problems with the reliability of signals (Jarvis et al 2005) and on-line applications (Burgess et al 2002). An on-line nephelometric turbidimeter was developed to measure the average particle/floc size during the coagulation process by calculating the standard deviation (SD) of measured turbidity data.…”

Section: Introductionmentioning

confidence: 99%

On-line evaluating the SS removals for chemical coagulation using digital image analysis and artificial neural networks

Yu¹

2014

Int. J. Environ. Sci. Technol.

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Chemical coagulation is one of the most important processes for industrial wastewater treatment plants to remove the suspended solids (SS), which depend significantly on particle characteristics. A digital image analysis system was set up in this study for the on-line measurements of particle characteristics, including particle size distribution, equivalent diameter, total area, total volume, and the fractal dimension in the both coagulation and flocculation periods in chemical coagulation. Two real industrial wastewaters, textile wastewater and landfill leachate, were used for conducting the coagulation and flocculation processes with different polyaluminum chloride dosages in a batch reactor. The artificial neural network (ANN) models were used to construct the correlations between the monitoring data acquired and the SS removal efficiencies. The experimental results indicated that the ANN models were able to precisely predict the SS removal efficiencies and effluent SS concentration after the chemical coagulation, with the correlation coefficient (R 2 ) of 0.96-0.97 for real landfill leachate and R 2 of 0.93-0.97 for real textile wastewater, which provided significant benefits for the control of chemical coagulation.

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Section: Introductionmentioning

confidence: 99%

On-line evaluating the SS removals for chemical coagulation using digital image analysis and artificial neural networks

Yu¹

2014

Int. J. Environ. Sci. Technol.

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“…This installation was based on the earlier research made by Biggs and Lant [30,31]. According to many authors it is the best approach to measure the kinetics of the aggregation process [32,33].…”

Section: Apparatusmentioning

confidence: 99%

Ultra-fine coal flocculation using dual-polymer systems of ultrasonically conditioned and unmodified flocculant

Lemanowicz

Jach

Kilian

et al. 2011

Chemical Engineering Journal

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“…Activated sludge flocs are complex three-dimensional structures and the size measured depends on the orientation of the flocs presented to the digital camera (Jarvis et al, 2005). The British Standard for quantitative microscope counting therefore suggests a minimum of 625 particles to obtain representative size distribution (BSI, 1963).…”

Section: Image Acquisitionmentioning

confidence: 99%

“…Laser particle size analysis is an alternative for floc size analysis and is also now frequently used in water laboratories to predict settlement rates and characterise particles (Jarvis et al, 2005). This paper reports on measuring floc size and characteristics by simplified image analysis and laser scattering compared with conventional settlement rate (SVI).…”

Section: Introductionmentioning

confidence: 99%

Assessing activated sludge morphology by laser and image analysis

Jun¹,

Wheatley²

2010

Proceedings of the Institution of Civil Engineers - Water Manag

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An excess of filamentous bacteria is a common settlement problem affecting the activated sludge process. In this study activated sludge morphology was monitored by image analysis and laser scattering. These were compared with the conventional sludge volume index. Good correlations between the two optical techniques for floc size were found when the small and interfering particles (< 50 ìm) were removed from the analysis (activated sludge size 100-500 ìm). A simpler image analysis procedure was developed using common software and equipment available in most laboratories. This should enable reproducible microbial morphology measurements to be used more widely routinely to predict the onset of poor settlement. The image analysis was used to determine the standard index of filamentinduced poor settlement, namely the total extended filament length. The results in common with some previously noted work did not show a simple link between either floc size or total extended filament length and sludge volume index. A new indicator of excess filaments is suggested, based on the frequency of occurrence of just the long extended filaments (> 100 ìm) which was shown to give better prediction of poor settlement (bulking).

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Measuring Floc Structural Characteristics

Cited by 106 publications

References 56 publications

On-line evaluating the SS removals for chemical coagulation using digital image analysis and artificial neural networks

On-line evaluating the SS removals for chemical coagulation using digital image analysis and artificial neural networks

Ultra-fine coal flocculation using dual-polymer systems of ultrasonically conditioned and unmodified flocculant

Assessing activated sludge morphology by laser and image analysis

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