Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment

A Master of Science thesis in Chemical Engineering by Rehab Ibrahim Khawaga entitled, “Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment”, submitted in December 2017. Thesis advisors are Dr. Sameer Al-Asheh and Dr. Nabil Abdel Jabber and thesis co-adv...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Khawaga, Rehab Ibrahim (author)
التنسيق: doctoralThesis
منشور في: 2017
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/9257
الوسوم: إضافة وسم
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author Khawaga, Rehab Ibrahim
author_facet Khawaga, Rehab Ibrahim
author_role author
dc.contributor.none.fl_str_mv Al-Asheh, Sameer
Abdel Jabbar, Nabil
Abouleish, Mohamed
dc.creator.none.fl_str_mv Khawaga, Rehab Ibrahim
dc.date.none.fl_str_mv 2017-12
2018-03-25T05:54:14Z
2018-03-25T05:54:14Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2017.48
http://hdl.handle.net/11073/9257
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Chlorination
Disinfection
Breakpoint chlorination
Ammonia-Nitrite system
Fuzzy logic control
Artificial neural network modelling (ANN)
Sewage
Purification
Chlorination
dc.title.none.fl_str_mv Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Chemical Engineering by Rehab Ibrahim Khawaga entitled, “Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment”, submitted in December 2017. Thesis advisors are Dr. Sameer Al-Asheh and Dr. Nabil Abdel Jabber and thesis co-advisor is Dr. Mohamed Abouleish. Soft and hard copy available.
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network_acronym_str aus
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oai_identifier_str oai:repository.aus.edu:11073/9257
publishDate 2017
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spelling Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater TreatmentKhawaga, Rehab IbrahimChlorinationDisinfectionBreakpoint chlorinationAmmonia-Nitrite systemFuzzy logic controlArtificial neural network modelling (ANN)SewagePurificationChlorinationA Master of Science thesis in Chemical Engineering by Rehab Ibrahim Khawaga entitled, “Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment”, submitted in December 2017. Thesis advisors are Dr. Sameer Al-Asheh and Dr. Nabil Abdel Jabber and thesis co-advisor is Dr. Mohamed Abouleish. Soft and hard copy available.Chlorination in wastewater treatment is regarded as a complicated process due to its ammonia and nitrite content. Chlorine added to such systems reacts with ammonia undergoing episodes of complex reactions, resulting in the chlorination breakpoint behavior. Most of the available chlorination mechanistic models are not easily applied which have restricted their practical utilization in treatment plants. In this study, a new mechanistic model for the chlorination breakpoint in an ammonia-nitrite system was developed with a user-friendly interface designed to be applicable to conditions occurring in wastewater treatment plants. The model was validated against laboratory studies reported in the literature and was also applied to forecast the chlorine residue in a wastewater treatment plant in the region. The model simulated both experimental and field data with high precision. Using the devised model, a full 43 factorial design was carried out to investigate the main effects of ammonia, nitrite, contact time, and their interactions. The outcome of the factorial designs has shown that as the ammonia proportion increases in the system, its effect prevails and diminishes that of nitrite. The carried out studies showed that this phenomenon occurs at ammonia/nitrie (A/N) ratio of 3. Artificial Neural Network modelling (ANN) was also applied to forecast the doses at which maximum and minimum total residual chlorine (TRC) of the breakpoint curve occur based on data generated using the developed model. ANN modelling was then integrated with fuzzy logic control (FLC) to optimize the chlorination process by minimizing its cost and maximizing its efficiency while operating within the plant’s budget. The developed FLC platform was applied to the Jebel Ali wastewater treatment plant and was able to improve the disinfection quality and reduce chlorine gas consumption by 18.18 %.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE)Al-Asheh, SameerAbdel Jabbar, NabilAbouleish, Mohamed2018-03-25T05:54:14Z2018-03-25T05:54:14Z2017-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2017.48http://hdl.handle.net/11073/9257en_USoai:repository.aus.edu:11073/92572025-06-26T12:31:14Z
spellingShingle Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
Khawaga, Rehab Ibrahim
Chlorination
Disinfection
Breakpoint chlorination
Ammonia-Nitrite system
Fuzzy logic control
Artificial neural network modelling (ANN)
Sewage
Purification
Chlorination
status_str publishedVersion
title Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
title_full Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
title_fullStr Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
title_full_unstemmed Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
title_short Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
title_sort Model Development, Application and Optimization of Chlorination Breakpoint in Wastewater Treatment
topic Chlorination
Disinfection
Breakpoint chlorination
Ammonia-Nitrite system
Fuzzy logic control
Artificial neural network modelling (ANN)
Sewage
Purification
Chlorination
url http://hdl.handle.net/11073/9257