scholarly journals Hindered Settling Velocity & Structure Formation during Particle Settling by Direct Numerical Simulation

2015 ◽  
Vol 102 ◽  
pp. 1656-1666 ◽  
Author(s):  
Ali Abbas Zaidi ◽  
Takuya Tsuji ◽  
Toshitsugu Tanaka
2017 ◽  
Vol 110 ◽  
pp. 38-47 ◽  
Author(s):  
Elena Torfs ◽  
Sophie Balemans ◽  
Florent Locatelli ◽  
Stefan Diehl ◽  
Raimund Bürger ◽  
...  

Author(s):  
Hiroshi SATO ◽  
Karoku NODA ◽  
Kazuo OTSUKA ◽  
Toshio KAWASHIMA

1996 ◽  
Vol 33 (1) ◽  
pp. 37-51 ◽  
Author(s):  
P. Vanrolleghem ◽  
D. Van der Schueren ◽  
G. Krikilion ◽  
K. Grijspeerdt ◽  
P. Willems ◽  
...  

An on-line settlometer has been developed. Batch settling experiments lasting 40 min are performed in a model clarifier incorporated in the sensor (“In-Sensor-Experiment”). The descent of the sludge blanket interface is monitored and the settling characteristics are deduced. The hardware consists of a 10 litre Pyrex decanter, a stirring/wall-scraping mechanism, an external light source and a moving light-intensity scanner. Either stirred or non-stirred settling curves can be recorded. Processing of the raw data readily produces the zone or hindered settling velocity (Vs) and the (stirred) sludge volume ([S]SV). The latter can be combined with a sludge concentration measurement to determine SVI-values, and dSVIs if a dilution step is included. Initial results are reported on a more elaborate interpretation of the data based on sedimentation models. The Takács et al. and Cho et al. models described the settling curves equally well. However, an identifiability analysis showed that not all parameters can be given unique values on the basis of the simple batch settling experiments applied in the work. More elaborate “In-Sensor-Experiments” are required to obtain complete identification. Two years of practical experience with the device on pilot- and full-scale treatment plants revealed its robustness, low maintenance requirements and reproducible monitoring of settling curves.


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