scholarly journals Depth Distribution of Suspended Matter in the Sand Layer of Slow Sand Filter Model Treated by Chlorination.

2000 ◽  
Vol 36 (3) ◽  
pp. 137-142
Author(s):  
MASUO YAMAMOTO ◽  
MASAKI YAMASHITA ◽  
NOBUTADA NAKAMOTO
2002 ◽  
Vol 2 (1) ◽  
pp. 305-309
Author(s):  
H.-J. Mälzer ◽  
R. Gimbel

The running time of slow sand filters in wastewater reuse is limited by the increase of pressure drop which is mainly caused by the surface filtration of suspended solids. Surface filtration mechanisms on the top of filter sand layer can be avoided e.g. by protection layers. Choosing suitable materials for protection layers a considerable extension of slow sand filter running times can be achieved.


2006 ◽  
Vol 6 (1) ◽  
pp. 105-111 ◽  
Author(s):  
H.-J. Mälzer ◽  
R. Gimbel

The running time of slow sand filters in wastewater reuse is usually limited by the increase of pressure drop which is mainly caused by surface filtration effects of suspended solids. Surface filtration mechanisms on the top of filter sand layer can be avoided e.g. by so-called protection layers. By choosing suitable materials for protection layers a considerable extension of slow sand filter running times can be achieved.


1996 ◽  
Vol 19 (12) ◽  
pp. 1009-1014
Author(s):  
Noriyasu IWASE ◽  
Yutaka KIZAKI ◽  
Kentaro NOZAKI ◽  
Masashi SAKAI ◽  
Nobutada NAKAMOTO

1997 ◽  
Vol 33 (4) ◽  
pp. 179-186 ◽  
Author(s):  
NOBUTADA NAKAMOTO ◽  
NORIYASU IWASE ◽  
KENTARO NOZAKI ◽  
MASASHI SAKAI

2009 ◽  
Vol 2 (1) ◽  
pp. 21-27 ◽  
Author(s):  
◽  
◽  
◽  
◽  

Abstract. The general objective of this study is to estimate the performance of the Horizontal Roughing Filter (HRF) by using Weglin's design criteria based on 1/3–2/3 filter theory. The main objective of the present study is to validate HRF developed in the laboratory with Slow Sand Filter (SSF) as a pretreatment unit with the help of Weglin's design criteria for HRF with respect to raw water condition and neuro-genetic model developed based on the filter dataset. The results achieved from the three different models were compared to find whether the performance of the experimental HRF with SSF output conforms to the other two models which will verify the validity of the former. According to the results, the experimental setup was coherent with the neural model but incoherent with the results from Weglin's formula as lowest mean square error was observed in case of the neuro-genetic model while comparing with the values found from the experimental SSF-HRF unit. As neural models are known to learn a problem with utmost efficiency, the model verification result was taken as positive.


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