
Wastewater Treatment by Reverse Osmosis Process
Description
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* Highlights different types of physico-chemical and biological wastewater treatment methods including hybrid systems
* Provides an overview of membrane processes, focuses on different types of membrane processes for water treatment and explains characteristics of membrane modules
* Introduces the importance and challenges of process modelling for simulation, design, and optimization and offers examples across various industries
*Describes the concept of different types of genetic algorithms for process optimisation and provides the state-of-the art of the GA method in terms of its application in water desalination and wastewater treatment
*Emphasizes economic aspects of RO processes for wastewater treatment
With its focus on the challenges posed by an increasing demand for fresh water and the urgent need to recycle wastewater at minimum cost, this work is an invaluable resource for engineers and scientists working within the field of wastewater treatment.
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Persons
Chakib Kara-Zaitri is a Senior Lecturer in Risk and Reliability in the Chemical Engineering Division of the School of Engineering, Faculty of Engineering and Informatics at the University of Bradford (UK). He obtained his BEng in Electrical and Electronic Engineering and PhD in Probabilistic Risk Assessment from the University of Bradford in 1983 and 1994 respectively. He has 30 years lecturing and research experience. His research interests are around the development of software systems for optimised reliability, risk, safety and maintenance engineering. His work over the last few years has focused on the development, optimisation and validation of mathematical models for faster, better and cheaper methods for removing harmful compounds from seawater and brackish water using spiral-wound reverse osmosis processes. He has published more than 36 technical papers and has delivered more than 40 conference papers around the world. He has supervised 12 PhD students to completion and is currently supervising 4 PhD students.
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