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Hilal Al-Hinai

Bio: Hilal Al-Hinai is an academic researcher from Sultan Qaboos University. The author has contributed to research in topics: Desalination & Seawater greenhouse. The author has an hindex of 19, co-authored 34 publications receiving 1783 citations.

Papers
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TL;DR: In this paper, the authors reviewed the literature on the fouling phenomena in reverse osmosis (RO) membrane systems, the analytical techniques used to quantify fouling, preventive methods, and membrane cleaning strategies and made specific recommendations on how scientists, engineers, and technical staff can assist in improving the performance of these systems through fundamental and applied research.
Abstract: Desalination by using reverse osmosis (RO) membranes has become very popular for producing freshwater from brackish water and seawater. Membrane lifetime and permeate flux, however, are primarily affected by the phenomena of concentration polarization and fouling at the membrane surface. The scope of the current paper was to critically review the literature on the fouling phenomena in RO and ultrafiltration (UF) membrane systems, the analytical techniques used to quantify fouling, preventive methods, and membrane cleaning strategies. The paper also makes specific recommendations on how scientists, engineers, and technical staff can assist in improving the performance of these systems through fundamental and applied research.

468 citations

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TL;DR: In this paper, a novel approach using an artificial neural network was used to develop a model for analyzing the relationship between the Global Radiation (GR) and climatological variables, and to predict GR for locations not covered by the model's training data.

242 citations

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TL;DR: In this article, the authors used a mathematical model to predict the productivity of a simple solar still under different climatic, design and operational parameters in Oman, and found that the average annual solar still yield of 4.15 kg/m 2

219 citations

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TL;DR: In this article, the thermodynamic efficiency of single-basin and multiple-effect solar water desalination systems was critically reviewed with special emphasis on humidification-dehumidification processes.

143 citations

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TL;DR: In this paper, a single-basin solar still with the entering brine flowing between a double glass glazing is investigated, which resulted in improved performance represented by a faster rate of evaporation from the basin.

123 citations


Cited by
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Journal ArticleDOI
TL;DR: The most commonly used desalination technologies are reverse osmosis (RO) and thermal processes such as multi-stage flash (MSF) and multi-effect distillation (MED) as mentioned in this paper.

1,708 citations

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TL;DR: It is shown that single-layer porous graphene can be used as a desalination membrane using an oxygen plasma etching process and exhibits a salt rejection rate of nearly 100% and rapid water transport.
Abstract: An oxygen plasma etching process can be used to create a nanoporous graphene layer that can efficiently desalinate water.

1,353 citations

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TL;DR: In this article, the authors present various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use.
Abstract: Artificial neural networks are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems and, once trained, can perform prediction and generalisation at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimisation, signal processing and social/psychological sciences. They are particularly useful in system modelling such as in implementing complex mappings and system identification. This paper presents various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order. Artificial neural networks have been used by the author in the field of solar energy; for modelling and design of a solar steam generating plant, for the estimation of a parabolic trough collector intercept factor and local concentration ratio and for the modelling and performance prediction of solar water heating systems. They have also been used for the estimation of heating loads of buildings, for the prediction of air flow in a naturally ventilated test room and for the prediction of the energy consumption of a passive solar building. In all those models a multiple hidden layer architecture has been used. Errors reported in these models are well within acceptable limits, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use. The work of other researchers in the field of renewable energy and other energy systems is also reported. This includes the use of artificial neural networks in solar radiation and wind speed prediction, photovoltaic systems, building services systems and load forecasting and prediction.

1,016 citations

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TL;DR: In this article, the authors present a review of various systems that use renewable energy sources for desalination, including solar collectors, photovoltaics, solar ponds and geothermal energy.

949 citations

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TL;DR: An overview of the parabolic-trough collectors that have been built and marketed during the past century, as well as the prototypes currently under development can be found in this paper.
Abstract: This paper presents an overview of the parabolic-trough collectors that have been built and marketed during the past century, as well as the prototypes currently under development. It also presents a survey of systems which could incorporate this type of concentrating solar system to supply thermal energy up to 400 °C, especially steam power cycles for electricity generation, including examples of each application.

915 citations