Prediction of Operation Efficiency of Water Treatment Plant with the Help of Multi-criteria Decision-making

2017 ◽  
Vol 3 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Sudipa Choudhury ◽  
Apu Kumar Saha
Keyword(s):  
Decision Making ◽  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Multi Criteria Decision Making ◽  
Operation Efficiency

Location selection for Installation of Surface Water Treatment Plant by Applying a New Sinusoidal Analytical Hierarchy Process

2019 ◽  
Vol 8 (3) ◽  
pp. 20-42
Author(s):  
Sudipa Choudhury ◽  
Apu Kumar Saha
Keyword(s):  
Decision Making ◽  
Water Treatment ◽  
Surface Water ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Location Selection ◽  
Simulation And Optimization ◽  
Surface Water Treatment ◽  
Selection For ◽  
Selection Of

Water treatment plants (WTPs) are responsible for ensuring supply of healthy water to urban and rural consumers for drinking and other related purposes. But the arbitrary selection of a location for installation or relocation of WTPs often fails the purpose of the plant. Presently studies in location selection for water treatment plant are rare. Multi-criteria decision making (MCDM) methods and bagged polynomial neural networks (PNN) were found to be exemplary and easy to use tools for prediction, simulation and optimization of decision-making objectives. The present study tries to apply the advantages of MCDM and bagged PNNs in the identification of an ideal location for a surface water treatment plant. The most significant parameter is found to be WQI which represents the overall quality of water suitable for domestic use. The PNN models were developed with all the selected eight alternatives as input and output. The algorithms like GMDH, SFS, SMS, and QC were used to estimate the weight of connections in between the input and hidden; and hidden and output layers separately for each segment. The application of these two soft computation tools provides an opportunity to the decision maker in the selection of optimal location with the help of an objective and cognitive method.

Value analysis system development for water treatment plant maintenance method selection

2010 ◽  
Vol 37 (9) ◽  
pp. 1213-1223
Author(s):  
Jong-Won Seo ◽  
Pyung-Ki Jung ◽  
Min-Jae Lee
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Automated System ◽  
Value Analysis ◽  
A Value ◽  
Method Selection ◽  
Analysis System

Even though the life span of a water treatment facility is relatively long, the decision-making process related to method selection for repair and reinforcement is generally influenced by an engineer's experience. These decisions should be made systematically after considering facility use, damage features, technical features, reconstruction costs, maintenance costs, and others. The purpose of this study is to provide a value analysis system for the effective selection of repairing and (or) reinforcing methods for water treatment plant concrete structures. Analysis of the concrete structure's damage type and maintenance records allowed the development of a value analysis system for more effective and systematic decision making. Performance evaluation criteria were established using a survey of field professionals as the decision basis. Weight for each performance criterion was determined by using the field personnel survey and the analytic hierarchy process (AHP) methodology. The rank rating standard for each performance evaluation criterion was established for each maintenance method type. Finally, an automated system was developed that can give guidance on repair and reinforcement method selection by applying proposed performance indices that are related to the maintenance method selection and the value analysis of the different methods.

Multi-objective optimization of water treatment operations for disinfection byproduct control

2020 ◽  
Vol 6 (3) ◽  
pp. 702-714
Author(s):  
William J. Raseman ◽  
Joseph R. Kasprzyk ◽  
R. Scott Summers ◽  
Amanda K. Hohner ◽  
Fernando L. Rosario-Ortiz
Keyword(s):  
Decision Making ◽  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Multi Objective Optimization ◽  
Disinfection Byproduct ◽  
Multi Objective ◽  
Plant Operations ◽  
Decision Making Framework

This paper introduces a novel decision-making framework for the optimization of water treatment plant operations.

DESIGNING OF REMOTE TERMINAL UNIT (RTU) FOR MEASUREMENT OF pH IN WATER TREATMENT PLANT

2019 ◽  
Vol 10 (1) ◽  
pp. 16
Author(s):  
V. MANE-DESHMUKH PRASHANT ◽  
B. MORE ASHWINI ◽  
B. P. LADGAOKAR ◽  
S. K. TILEKAR ◽  
◽  
...  
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Terminal Unit ◽  
Remote Terminal ◽  
Remote Terminal Unit

ENHANCED COAGULATION FOR ALGAE REMOVAL IN A TYPICAL ALGERIA WATER TREATMENT PLANT

2017 ◽  
Vol 16 (10) ◽  
pp. 2303-2315 ◽  
Author(s):  
Djamel Ghernaout ◽  
Abdelmalek Badis ◽  
Ghania Braikia ◽  
Nadjet Mataam ◽  
Moussa Fekhar ◽  
...  
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Enhanced Coagulation ◽  
Algae Removal

Sadr City R3 Water Treatment Plant Baghdad, Iraq

2008 ◽  
Author(s):  
Angelina Johnston ◽  
Kevin O'Connor ◽  
Todd Criswell
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant

Water treatment to reduce internal corrosion in the drinking water distribution system in Oslo

2001 ◽  
Vol 1 (3) ◽  
pp. 91-96 ◽  
Author(s):  
L.J. Hem ◽  
E.A. Vik ◽  
A. Bjørnson-Langen
Keyword(s):  
Water Treatment ◽  
Corrosion Rate ◽  
Distribution System ◽  
Water Distribution ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Corrosion Monitoring ◽  
Copper Corrosion ◽  
Iron Corrosion ◽  
Internal Corrosion

In 1995 the new Skullerud water treatment plant was put into operation. The new water treatment includes colour removal and corrosion control with an increase of pH, alkalinity and calcium concentration in addition to the old treatment, which included straining and chlorination only. Comparative measurements of internal corrosion were conducted before and after the installation of the new treatment plant. The effect of the new water treatment on the internal corrosion was approximately a 20% reduction in iron corrosion and a 70% reduction in copper corrosion. The heavy metals content in standing water was reduced by approximately 90%. A separate internal corrosion monitoring programme was conducted, studying the effects of other water qualities on the internal corrosion rate. Corrosion coupons were exposed to the different water qualities for nine months. The results showed that the best protection of iron was achieved with water supersaturated with calcium carbonate. Neither a high content of free carbon dioxide or the use of the corrosion inhibitor sodium silicate significantly reduced the iron corrosion rate compared to the present treated water quality. The copper corrosion rate was mainly related to the pH in the water.

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