Study of Coagulant Dosage Variation According to the Design G Value of Coagulation and Flocculation Processes in a Water Treatment Plant

2021 ◽  
pp. 533-541
Author(s):  
R. M. M. C. Dassanayake ◽  
N. S. Jayasinghe ◽  
A. P. K. Wickramage ◽  
K. B. K. D. K. Kandeyaya ◽  
W. B. M. L. I. Weerasekara ◽  
...  
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Coagulation And Flocculation ◽  
Coagulant Dosage ◽  
G Value

Application of artificial neural network to control the coagulant dosing in water treatment plant

2000 ◽  
Vol 42 (3-4) ◽  
pp. 403-408 ◽  
Author(s):  
R.-F. Yu ◽  
S.-F. Kang ◽  
S.-L. Liaw ◽  
M.-c. Chen
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Water Treatment ◽  
Regression Model ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Ann Model ◽  
Coagulant Dosage ◽  
Ann Models

Coagulant dosing is one of the major operation costs in water treatment plant, and conventional control of this process for most plants is generally determined by the jar test. However, this method can only provide periodic information and is difficult to apply to automatic control. This paper presents the feasibility of applying artificial neural network (ANN) to automatically control the coagulant dosing in water treatment plant. Five on-line monitoring variables including turbidity (NTUin), pH (pHin) and conductivity (Conin) in raw water, effluent turbidity (NTUout) of settling tank, and alum dosage (Dos) were used to build the coagulant dosing prediction model. Three methods including regression model, time series model and ANN models were used to predict alum dosage. According to the result of this study, the regression model performed a poor prediction on coagulant dosage. Both time-series and ANN models performed precise prediction results of dosage. The ANN model with ahead coagulant dosage performed the best prediction of alum dosage with a R2 of 0.97 (RMS=0.016), very low average predicted error of 0.75 mg/L of alum were also found in the ANN model. Consequently, the application of ANN model to control the coagulant dosing is feasible in water treatment.

Roughing filtration as an effective pre-treatment system for high turbidity water

2011 ◽  
Vol 64 (7) ◽  
pp. 1419-1427 ◽  
Author(s):  
Zahiruddin Khan ◽  
Rahimuddin Farooqi
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Dose Requirement ◽  
Water Turbidity ◽  
Effluent Quality ◽  
Coagulant Dosage ◽  
High Turbidity ◽  
Pre Treatment ◽  
Effective Water

Effective water treatment is the prime goal of every water treatment facility. Chakwal Water Treatment Plant in Pakistan has been treating high-turbidity surface water through crude coagulation, sedimentation and slow sand filtration since the early 1980s. The process has always been tedious in terms of high coagulant dosage, large volumes of sludge and short filter runs especially after wet spells. A laboratory-scale study was conducted to see if roughing filtration, as the pre-treatment process, would help in reducing coagulant dose and sludge volume and improving effluent quality. Results indicated that up-flow rouging filtration with media grades decreasing in the direction of flow could reduce wet weather raw water turbidity (by more than 90%) and coagulant dose. Overall, the plant could save over US $54,000 annually in terms of coagulant cost only. Longer filter runs, improved product water quality leading to lower chlorine dose requirement, would be additional benefits.

Treatment and reuse of backwash water in Taipei water treatment plant, Taiwan

2006 ◽  
Vol 6 (6) ◽  
pp. 89-98 ◽  
Author(s):  
C.B. Yang ◽  
Y.L. Cheng ◽  
J.C. Liu ◽  
D.J. Lee
Keyword(s):  
Water Treatment ◽  
Pilot Study ◽  
Sea Water ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Coagulant Dosage ◽  
Effective Removal ◽  
Recycle Ratio ◽  
Water Recycle ◽  
The Impact

A case study on the treatment and reuse of backwash water from Chang-Hsing Water Treatment Plant (CHWTP) and Swan-Sea Water Treatment Plant (SSWTP) of Taipei Water Department was conducted. Both backwash waters showed different properties. However, the characteristics of each backwash water did not vary considerably among samples taken during different time. Results from jar tests indicated that both polyaluminium chloride (PACl) and alum could result in effective removal of turbidity. Both DOC and absorbance of UV254 decreased slightly with increasing coagulant dosage. In continuous operation of backwash water recycle in pilot study in CHWTP, it was found that treated water quality was not affected by two different modes of recycle: intermittent recycle at ratio of 1:7 (backwash water:raw water) and continuous recycle at ratio of 1:42. In the pilot study in SSWTP, no impact was found on the introduction of backwash water at recycle ratio of 4, 6 and 8%, regardless of whether the backwash water was recycled directly or went through 3 min pre-sedimentation before it is recycled. Further study on the impact of typhoon on treatment and recycle of backwash water was recommended.

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