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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/14626
Title: A review of the artificial neural network based modelling and simulation approaches applied to optimize reverse osmosis desalination techniques
Authors: Mahadeva R.
Manik G.
Goel A.
Dhakal N.
Published in: Desalination and Water Treatment
Abstract: The current global issue of water scarcity has demanded for over-abstraction of conventional freshwater resources. The states of water scarcity are anticipated to worsen, as by 2050 the population is estimated to reach 9 billion worldwide. Desalination is considered a solution to solve the water scarcity issues, as it is considered a drought-proof water source, which does not depend on climate change, river flows or reservoir levels. Moreover, membrane fouling is still the main “Achilles heel” for the effective operation of desalination systems. This makes the technology chemically, energetically and operationally intensive and requires a considerable infusion of capital. The application of an artificial neural network (ANN), the computing model inspired by the human brain, and its variants, have been developed that can optimize the operation of membrane-based desalination system through analyzing the complex experimental and real-time data. This review paper presents the recent trends and developments focussed primarily on the modelling and simulation of reverse osmosis (RO) plant using ANN to solve the challenging problem in membrane-based desalination systems. The literature review suggested that ANN has a potential application in predicting linear, nonlinear, complicated complex systems with high accuracy and with better control, prediction of membrane fouling, cost analysis. Therefore, ANN considered a strong basis to attract and motivate the researchers to work in this field in the future. © 2019 Desalination Publications. All rights reserved.
Citation: Desalination and Water Treatment (2019), 156(): 245-256
URI: https://doi.org/10.5004/dwt.2019.23999
http://repository.iitr.ac.in/handle/123456789/14626
Issue Date: 2019
Publisher: Desalination Publications
Keywords: Artificial neural network
Desalination
Modelling and simulation
Reverse osmosis
ISSN: 19443994
Author Scopus IDs: 57204158068
56595314900
57210524796
36187965200
Author Affiliations: Mahadeva, R., Department of Polymer and Process Engineering, Indian Institute of Technology, Roorkee, 247667, India
Manik, G., Department of Polymer and Process Engineering, Indian Institute of Technology, Roorkee, 247667, India
Goel, A., Department of Polymer and Process Engineering, Indian Institute of Technology, Roorkee, 247667, India
Dhakal, N., Environmental Engineering and Water Technology Department, IHE-Delft Institute for Water Education, Delft, AX 2611, Netherlands
Corresponding Author: Manik, G.; Department of Polymer and Process Engineering, Indian Institute of TechnologyIndia; email: manikfpt@iitr.ac.in
Appears in Collections:Journal Publications [PE]

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