scholarly journals Erratum for “Hindered Settling Velocity in Particle-Fluid Mixture: A Theoretical Study Using the Entropy Concept” by Manotosh Kumbhakar, Snehasis Kundu, and Koeli Ghoshal

2021 ◽  
Vol 147 (11) ◽  
pp. 08221002
Author(s):  
Manotosh Kumbhakar ◽  
Snehasis Kundu ◽  
Koeli Ghoshal
Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 55 ◽  
Author(s):  
Zhongfan Zhu ◽  
Hongrui Wang ◽  
Dingzhi Peng ◽  
Jie Dou

The settling velocity of a sediment particle is an important parameter needed for modelling the vertical flux in rivers, estuaries, deltas and the marine environment. It has been observed that a particle settles more slowly in the presence of other particles in the fluid than in a clear fluid, and this phenomenon has been termed ‘hindered settling’. The Richardson and Zaki equation has been a widely used expression for relating the hindered settling velocity of a particle with that in a clear fluid in terms of a concentration function and the power of the concentration function, and the power index is known as the exponent of reduction of the settling velocity. This study attempts to formulate the model for the exponent of reduction of the settling velocity by using the probability method based on the Tsallis entropy theory. The derived expression is a function of the volumetric concentration of the suspended particle, the relative mass density of the particle and the particle’s Reynolds number. This model is tested against experimental data collected from the literature and against five existing deterministic models, and this model shows good agreement with the experimental data and gives better prediction accuracy than the other deterministic models. The derived Tsallis entropy-based model is also compared with the existing Shannon entropy-based model for experimental data, and the Tsallis entropy-based model is comparable to the Shannon entropy-based model for predicting the hindered settling velocity of a falling particle in a particle-fluid mixture. This study shows the potential of using the Tsallis entropy together with the principle of maximum entropy to predict the hindered settling velocity of a falling particle in a particle-fluid mixture.


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.


2008 ◽  
Vol 55 (12) ◽  
pp. 1197-1208 ◽  
Author(s):  
Alan Cuthbertson ◽  
Ping Dong ◽  
Stuart King ◽  
Peter Davies

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