AUTOMATED SVI MEASUREMENTS INCORPORATING SHORT-TERM

TEMPERATURE VARIATIONSWerner Rössle

Jurie TerblanchèERWAT

WISA April 2010

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CONTENT• Background• Experimental• Results

– Batch tests conventional SVI– On-line tests automated on-line SVI monitoring at full-

scale reactor – Modelling SVI combined with both MLSS

concentration and sample temperature from on-line data

• Conclusions• Project summary• Acknowledgements

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BACKGROUNDSludge Volume Index (SVI) test • Developed 1934, procedure simple, fast, widely used, data• SVI of < 100 to 150 ml/g indicates a well-settling sludge• Temperature dependency generally not considered, and

compensation methods usually not implemented

Standard methods (APHA, 1998) SVI test procedure• Sample of known MLSS concentration, 1 litre cylinder,

stirred, 30 minute settling• Settled sludge volume read off cylinder wall• SVI = settled sludge volume (ml/l) / MLSS concentration (g/l)• Sample temperature kept constant at reactor (basin)

temperature during SVI settling test – no procedure provided3

EXPERIMENTAL(1) BATCH TEST Basic sludge settling test in cylinders

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EXPERIMENTAL(2) BATCH TESTSVI test method • reactor and ambient temperatures• MLSS concentration• reactor sludge sample, remix• sludge in 1 or 2 litre cylinder(s), remix• cylinder in shade or sunshine (assess location)• sample temperature• start sludge settling test immediately• 30 minutes settling to obtain settled volume • sample temperature again (probe of thermometer in same

position inside cylinder during all measurements)• calculate SVI

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EXPERIMENTAL(3) ON-LINE METER

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• Settler• Settler

EXPERIMENTAL(4) ON-LINE METER

Automated on-line SVI meter– Mobile (220V and water supply) in an enclosure– 2 ℓ Perspex settling cylinder (84.0 mm diameter and

360.9 mm height), removable for cleaning– On-line Tr, Tc, Ta, MLSS concentration – Moving infrared light scanner – 6-line graphic recorder, data storage, retrieval– Automated sample filling, settling, draining, and washing

stages– Sludge sample transfer vacuum based, no mechanical

pumping

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RESULTS(1) BATCH TEST

Cylinder PlaceMLSS conc. [mg/l]Tr [°C]Ta [°C]

583020.530.1

587020.831.5

Average

1 ℓ ShadeSVI[ml/g] 118 107 113Tc30 [°C ] 25.3 24.4 24.9

1 ℓ SunSVI[ml/g] 89 80 85Tc30 [°C ] 26.2 27.9 27.1

2 ℓ ShadeSVI[ml/g] 130 126 128Tc30 [°C ] 24.3 23.3 23.8

2 ℓ SunSVI[ml/g] 93 82 88Tc30 [°C ] 25.6 26.6 26.1

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RESULTS(2) BATCH TEST ILLUSTRATION

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START OF SETTLING TEST 1, 15/10MLSS = 5830 mg/lTr = 20.5°CTa = 30.1°C Tc = 20.6°CSamples in sun or shade - change Tc

END OF SETTLING TEST: Sample handling:1l sun, 1l shade, 2l shade, 2l sunSample temperature Tc30

26.2, 25.3, 25.6, 24.3 4 SVI from one reactor sample:89,118, 130, 93

89 118 130 93

RESULTS(3) BATCH TEST ILLUSTRATION

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START OF SETTLING TEST 2, 16/10MLSS = 5870 mg/lTr = 20.8°CTa = 31.5°C Tc = about 22°CSamples in sun or shade - change Tc

END OF SETTLING TEST: Sample handling:2l sun, 1l sun, 2l shade, 1l shadeSample temperature Tc30

26.6, 27.9, 23.3, 24.44 SVI from one reactor sample:82, 80, 126, 107

82 80 126 107

RESULTS(4) DIURNAL ON-LINE SVI

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Graph of 44 on-line 30-minute settling curves, MLSS concentration, temperature and calculated SVI trends over a diurnal period

RESULTS(5) SETTLING CURVES & SVI

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Graph of 2 on-line 30-minute settling curves, MLSS concentration, temperature and calculated SVI trends

RESULTS(6) SVI vs. MLSS CONC.

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Data scatter, R2 = 0.47

RESULTS(7) SVI vs. TEMPERATURE

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Data scatter, R2 = 0.69

RESULTS(8) SVI vs. MLSS CONC. & TEMP.

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R2 = 0.84

RESULTS(9) BASIC MODEL• Commercial statistical software package • Basic regression model for easy use:

• R2 improvement about 0.3 with one case study• Significant parameters affecting SVI:

– MLSS concentration – Sample temperature

• 8 ml/g SVI change (average) per 1°C on-line sample temperature change with one case study

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CONCLUSIONS1. Batch settling test: substantial temperature

change– Test cylinder environment has an influence on sample

temperature and SVI

2. On-line settling test: automated diurnal trends– Short time delay between sampling and test reduces

sample temperature variations, improved SVI– Incorporates reactor temperature variations in SVI trend

3. Modelling: correlations for general and design use– Improved SVI correlations with both temperature and

MLSS concentration

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PROJECT SUMMARY• Include temperature in sludge settling analysis

– reactor, ambient, sample temperatures, or at least stabilised sample and room temperatures

• Use a consistent reference basis of experimental conditions is a basic requirement– impact of cylinder handling and temperature on results

used for plant process control or design or modelling

• Do not extrapolate any results from a case study– develop correlations for each plant or reactor

• On-line automated sludge settling monitoring – benefits relate to automated sampling and testing

methods and on-line data generation18

ACKNOWLEDGEMENTS• ERWAT provided facilities and research resources• ERWAT Research and Development Forum, Board of

Directors and Executive Management provided support

• ERWAT operational personnel assisted during batch settling tests

• Mr G. George made key contributions during the development, construction and upgrading of the on-line SVI meter

• WRC provided initial project finance on a related activated sludge settling project

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Thank you

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