A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals

Alaa Husaeen Wadie

doi:doi:10.11648/j.ijema.20130105.15

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A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals

Alaa Husaeen Wadie

Published in International Journal of Environmental Monitoring and Analysis (Volume 1, Issue 5)

Received: Accepted: Published: 20 October 2013

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Abstract

In water treatment processes, the individual unit operations are complex, non-linear and poorly understood. Whilst many models have been developed to improve process understanding, these are rarely in a form easily exploited by the control engineer. Attempts to improve the performance of water treatment works through the application of improved control and measurement have had variable success. This paper discusses investigations into the application of feed forward control on the clarification process of a small-scale pilot plant. The application aimed towards maximizing the efficiency of the chemical coagulation process. To achieve this, a simple computer program written in Visual Basic version 6 models to a chief the process operating conditions. Mathematical models based on historical plant data covering 18 months analyzed by stepwise multiple regression analysis. The following parameters were important determinants of coagulant dose and pH control reagents: river turbidity, pH, temperature, total dissolved solids, and plant flowrate. A predictive equation developed from the data, of the form: Al2(SO4)3 (mg/L) = a*Q + b*Turb + c*TDS + d*pH + e*Temp + f. The aim of this model is to provide water treatment operators with a tool that enables prediction of chemical reagents and treatment conditions for selected removal of turbidity, based on raw water quality data. While for adjusting pH, whether lime or soda ash are added, the pretreatment of water supplies involves the use to decrease the acidity, to soften, and to clear drinking water, calcium oxide (CaO), commonly known as quicklime or burnt lime. The addition of lime is with the form: CaO (mg/L) = j + k *pH. And for soda ash sodium percarbonateNa2CO3 the addition form is: Na2CO3 (mg/L) = m + n*pH. The advantages of software program are significant in the operation of water treatment plant. The program designed as an aid, so the user can still customize and optimize the computer suggested design. Users are able to move forward in adjusting or optimizing the design in minutes, which is difficult for manual system. This system was an initial system, many new features and functions have to be added to the program to enhance the functions and make it commercially robust. It concluded that this system is very powerful tool in improving compliance of treated water quality to reduce labor and chemicals and to facilitate the organizations and individuals with better understanding on how their actions can have a direct impact on the treatment.

Published in	International Journal of Environmental Monitoring and Analysis (Volume 1, Issue 5)
DOI	10.11648/j.ijema.20130105.15
Page(s)	194-202
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Coagulation, Feed Forward Control, Model Definition, Turbidity, PH, Temperature, Total Dissolved Solids, Plant Flowrate

References

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[2]	Babylon Water Directorate, 2012.
[3]	Bernazeau, F., Pierrone, P., and. Duguet, J.P, 1992,"Interest in using a streamline current detector for automatic coagulant dose control, Journal of Water Supply.
[4]	Chang, M., 2002,"Forest Hydrology: An Introduction to Water and Forests", CRC Press, Boca Raton, Florida.
[5]	Cox, C.S. and Graham, J., 1994,"Steps towards automatic clarification control", IEE Colloq. Advances in control in the process industries: Computing and control division, London, UK, March.
[6]	Dentel, K.S, 1995,"Use of streaming current detector in coagulation monitoring and control", Journal of Water Sciences Research and Technologies – Aqua. 44 .
[7]	Evans, J., Enoch, C., Johnson M.,and Williams, P., 1998,"Intelligent based autocoagulation control applied to a water treatment works, in: Proceedings of International Conference on Control.
[8]	Fu-Yi Cui, Yuan-zhen, 1999, "Water Supply and Sewerage Project Instrumentation and Control. Beijing: China Building Industry Press.
[9]	Grimm, J. W., and Lynch, J. A., 2004,"Enhanced wet deposition estimates using modeled precipitation inputs", Environmental Monitoring and Assessment, vol. 90, No. 1-3.
[10]	Kenichi Kurotfanim, et al., 1995, "Advanced control of coagulation process applying floc sensor", In: IWSA. Specialized Conference on Advanced Treatment and Intergrated Water System Management into the 21st Century.
[11]	Lind, C., 1994,"Coagulation Control and Optimization", Part One and Part Two, Public Works (October).
[12]	Mirsepassi, A., Cathers B., and Dharmappa, H.B., 1995,"Application of Artificial Neural Networks to the Real Time Operation of Water Treatment Plants, in: Proceedings of the International Conference on Neural Networks, (Vol. 1), Perth, Australia.
[13]	Prakash, A., 2004,"Water Resources Engineering", ASCE Press, New York.
[14]	Song Qi-min, Lumin Gang, Yi Yong, et al, 1999, "Automatic control of the amount of coagulant filling new method. China Water & Wastewater.
[15]	Yang people, 2000, "Display type flocculation control system (FCD) in the water treatment plant applications", China Water & Wastewater.
[16]	Zhang Weiguo, 2000, "Introduction of advanced control theory and methods", Xi'an: Northwest Industry University Press,. Reposted elsewhere in the Research PapersDownloadhttp://www.hi138.com
[17]	Zhang, W. L., Wu, S. X. and Ji, H. J., 2007,"Estimation of agricultural non-point source pollution in China and the alleviating strategies", Scientia Agricultura Sinica, vol. 37, no 7.
[18]	Zhong Chun-chang, et al., 1989, "Mathematical model plus alum automation technologies. China Water Supply and Drainage.

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Alaa Husaeen Wadie. (2013). A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals. International Journal of Environmental Monitoring and Analysis, 1(5), 194-202. https://doi.org/10.11648/j.ijema.20130105.15

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ACS Style

Alaa Husaeen Wadie. A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals. Int. J. Environ. Monit. Anal. 2013, 1(5), 194-202. doi: 10.11648/j.ijema.20130105.15

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AMA Style

Alaa Husaeen Wadie. A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals. Int J Environ Monit Anal. 2013;1(5):194-202. doi: 10.11648/j.ijema.20130105.15

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@article{10.11648/j.ijema.20130105.15,
  author = {Alaa Husaeen Wadie},
  title = {A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {1},
  number = {5},
  pages = {194-202},
  doi = {10.11648/j.ijema.20130105.15},
  url = {https://doi.org/10.11648/j.ijema.20130105.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20130105.15},
  abstract = {In water treatment processes, the individual unit operations are complex, non-linear and poorly understood. Whilst many models have been developed to improve process understanding, these are rarely in a form easily exploited by the control engineer. Attempts to improve the performance of water treatment works through the application of improved control and measurement have had variable success. This paper discusses investigations into the application of feed forward control on the clarification process of a small-scale pilot plant. The application aimed towards maximizing the efficiency of the chemical coagulation process. To achieve this, a simple computer program written in Visual Basic version 6 models to a chief the process operating conditions. Mathematical models based on historical plant data covering 18 months analyzed by stepwise multiple regression analysis. The following parameters were important determinants of coagulant dose and pH control reagents: river turbidity, pH, temperature, total dissolved solids, and plant flowrate. A predictive equation developed from the data, of the form: Al2(SO4)3 (mg/L) = a*Q + b*Turb + c*TDS + d*pH + e*Temp + f. The aim of this model is to provide water treatment operators with a tool that enables prediction of chemical reagents and treatment conditions for selected removal of turbidity, based on raw water quality data. While for adjusting pH, whether lime or soda ash are added, the pretreatment of water supplies involves the use to decrease the acidity, to soften, and to clear drinking water, calcium oxide (CaO), commonly known as quicklime or burnt lime. The addition of lime is with the form: CaO (mg/L) = j + k *pH. And for soda ash sodium percarbonateNa2CO3 the addition form is: Na2CO3 (mg/L) = m + n*pH. The advantages of software program are significant in the operation of water treatment plant. The program designed as an aid, so the user can still customize and optimize the computer suggested design. Users are able to move forward in adjusting or optimizing the design in minutes, which is difficult for manual system. This system was an initial system, many new features and functions have to be added to the program to enhance the functions and make it commercially robust. It concluded that this system is very powerful tool in improving compliance of treated water quality to reduce labor and chemicals and to facilitate the organizations and individuals with better understanding on how their actions can have a direct impact on the treatment.},
 year = {2013}
}

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TY - JOUR
T1 - A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals
AU - Alaa Husaeen Wadie
Y1 - 2013/10/20
PY - 2013
N1 - https://doi.org/10.11648/j.ijema.20130105.15
DO - 10.11648/j.ijema.20130105.15
T2 - International Journal of Environmental Monitoring and Analysis
JF - International Journal of Environmental Monitoring and Analysis
JO - International Journal of Environmental Monitoring and Analysis
SP - 194
EP - 202
PB - Science Publishing Group
SN - 2328-7667
UR - https://doi.org/10.11648/j.ijema.20130105.15
AB - In water treatment processes, the individual unit operations are complex, non-linear and poorly understood. Whilst many models have been developed to improve process understanding, these are rarely in a form easily exploited by the control engineer. Attempts to improve the performance of water treatment works through the application of improved control and measurement have had variable success. This paper discusses investigations into the application of feed forward control on the clarification process of a small-scale pilot plant. The application aimed towards maximizing the efficiency of the chemical coagulation process. To achieve this, a simple computer program written in Visual Basic version 6 models to a chief the process operating conditions. Mathematical models based on historical plant data covering 18 months analyzed by stepwise multiple regression analysis. The following parameters were important determinants of coagulant dose and pH control reagents: river turbidity, pH, temperature, total dissolved solids, and plant flowrate. A predictive equation developed from the data, of the form: Al2(SO4)3 (mg/L) = a*Q + b*Turb + c*TDS + d*pH + e*Temp + f. The aim of this model is to provide water treatment operators with a tool that enables prediction of chemical reagents and treatment conditions for selected removal of turbidity, based on raw water quality data. While for adjusting pH, whether lime or soda ash are added, the pretreatment of water supplies involves the use to decrease the acidity, to soften, and to clear drinking water, calcium oxide (CaO), commonly known as quicklime or burnt lime. The addition of lime is with the form: CaO (mg/L) = j + k *pH. And for soda ash sodium percarbonateNa2CO3 the addition form is: Na2CO3 (mg/L) = m + n*pH. The advantages of software program are significant in the operation of water treatment plant. The program designed as an aid, so the user can still customize and optimize the computer suggested design. Users are able to move forward in adjusting or optimizing the design in minutes, which is difficult for manual system. This system was an initial system, many new features and functions have to be added to the program to enhance the functions and make it commercially robust. It concluded that this system is very powerful tool in improving compliance of treated water quality to reduce labor and chemicals and to facilitate the organizations and individuals with better understanding on how their actions can have a direct impact on the treatment.
VL - 1
IS - 5
ER -

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Author Information

Alaa Husaeen Wadie

Head of Environmental Eng. Dept. /College of Eng. /Babylon University

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APA Style

Alaa Husaeen Wadie. (2013). A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals. International Journal of Environmental Monitoring and Analysis, 1(5), 194-202. https://doi.org/10.11648/j.ijema.20130105.15

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ACS Style

Alaa Husaeen Wadie. A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals. Int. J. Environ. Monit. Anal. 2013, 1(5), 194-202. doi: 10.11648/j.ijema.20130105.15

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AMA Style

Alaa Husaeen Wadie. A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals. Int J Environ Monit Anal. 2013;1(5):194-202. doi: 10.11648/j.ijema.20130105.15

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@article{10.11648/j.ijema.20130105.15,
  author = {Alaa Husaeen Wadie},
  title = {A Modeling Approach towards Improving Compliance of Treated Water Quality to Reduce Manpower and Chemicals},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {1},
  number = {5},
  pages = {194-202},
  doi = {10.11648/j.ijema.20130105.15},
  url = {https://doi.org/10.11648/j.ijema.20130105.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20130105.15},
  abstract = {In water treatment processes, the individual unit operations are complex, non-linear and poorly understood. Whilst many models have been developed to improve process understanding, these are rarely in a form easily exploited by the control engineer. Attempts to improve the performance of water treatment works through the application of improved control and measurement have had variable success. This paper discusses investigations into the application of feed forward control on the clarification process of a small-scale pilot plant. The application aimed towards maximizing the efficiency of the chemical coagulation process. To achieve this, a simple computer program written in Visual Basic version 6 models to a chief the process operating conditions. Mathematical models based on historical plant data covering 18 months analyzed by stepwise multiple regression analysis. The following parameters were important determinants of coagulant dose and pH control reagents: river turbidity, pH, temperature, total dissolved solids, and plant flowrate. A predictive equation developed from the data, of the form: Al2(SO4)3 (mg/L) = a*Q + b*Turb + c*TDS + d*pH + e*Temp + f. The aim of this model is to provide water treatment operators with a tool that enables prediction of chemical reagents and treatment conditions for selected removal of turbidity, based on raw water quality data. While for adjusting pH, whether lime or soda ash are added, the pretreatment of water supplies involves the use to decrease the acidity, to soften, and to clear drinking water, calcium oxide (CaO), commonly known as quicklime or burnt lime. The addition of lime is with the form: CaO (mg/L) = j + k *pH. And for soda ash sodium percarbonateNa2CO3 the addition form is: Na2CO3 (mg/L) = m + n*pH. The advantages of software program are significant in the operation of water treatment plant. The program designed as an aid, so the user can still customize and optimize the computer suggested design. Users are able to move forward in adjusting or optimizing the design in minutes, which is difficult for manual system. This system was an initial system, many new features and functions have to be added to the program to enhance the functions and make it commercially robust. It concluded that this system is very powerful tool in improving compliance of treated water quality to reduce labor and chemicals and to facilitate the organizations and individuals with better understanding on how their actions can have a direct impact on the treatment.},
 year = {2013}
}

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