Evaluation, modelling and control of ultrafiltration membrane water treatment systems / Chew Chun Ming

Ultrafiltration (UF) membrane water treatment systems are swiftly gaining acceptance for large-scale production of potable/drinking water supply in Malaysia. In the first part of this research, extensive efforts have been taken to analyze and evaluate an industrial-scale UF membrane water treatme...

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Bibliographic Details
Main Author: Chew , Chun Ming
Format: Thesis
Published: 2017
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Online Access:http://studentsrepo.um.edu.my/8275/1/All.pdf
http://studentsrepo.um.edu.my/8275/6/chun_ming.pdf
http://studentsrepo.um.edu.my/8275/
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Institution: Universiti Malaya
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Summary:Ultrafiltration (UF) membrane water treatment systems are swiftly gaining acceptance for large-scale production of potable/drinking water supply in Malaysia. In the first part of this research, extensive efforts have been taken to analyze and evaluate an industrial-scale UF membrane water treatment plant in Malaysia through detailed case studies. Analysis of the UF membrane water treatment plant was performed to highlight the common design and operational issues with suggested solutions obtained from literature. Subsequently, evaluation and comparison between the UF membrane water treatment system and the conventional media/sand filtration water treatment system was conducted. Detailed analyses on commercial, quality and environmental aspects were examined on both water treatment systems. Capital costs of the UF system was 5.6% higher while the operational cost was more than three times than the conventional media/sand filtration water treatment system. Apparent advantages of the UF system were exhibited through its production of consistent filtrate turbidity of less than 1 Nephelometric Turbidity Units (NTU) and non-hazardous sludge as by-products. The sludge from the conventional system contains 58 mg/L of Aluminium residual originates from the Aluminium Chlorohydrate (ACH) utilized as coagulant in the process. Considerable efforts were also made to elucidate the key issues of scaling-up industrial-scale UF membrane water treatment system from data obtained through laboratory and pilot-scale experiments. Results have indicated that all three UF systems (laboratory-scale, pilot-scale and industrial-scale) have exhibited similar transmembrane pressure (TMP) profiles pattern under same operational conditions. In the second part of this research work, a pilot-scale UF system has been utilized to gather data for the process modelling. A practical hybrid model which encompassed the theoretical model of Darcy’s law and artificial neural networks (ANN) predictive model has been developed. This hybrid model utilizes data from commonly available on-line monitoring analyzers and laboratory analysis data in a typical UF membrane water treatment plant. Results have indicated close agreement between the simulated model and experimental data on feed water with turbidity of 10 NTU and 20 NTU respectively. In the final part of this research work, an UF experimental system equipped with supervisory control and data acquisition software has been commissioned to implement various on-line control systems. The predictive model developed earlier has been utilized together with ANN controllers to provide an alternative control system for the dead-end constant flux UF process. Experiments were conducted to compare the results from both the ANN and conventional set-points control systems. The ANN control system has exhibited capability to reduce water losses to 4.9 % compared to the conventional set-points control system of 9.6% while maintaining acceptable potential membrane fouling propensity for low turbidity of feed water. Main objectives of this research are to demonstrate the feasible utilization of UF membrane water treatment systems and viable suggestions to improve its operations. The major contributions of this research were highlighted through case studies evaluation of the UF membrane water treatment systems, development of hybrid model for potential membrane fouling parameters estimation and a proposed alternative ANN process control system to reduce water losses.