A model for the fouling of M.S.F. plants based on data from operating units

Cooper, Katie; Hanlon, L.G.; Smart, Gerald; Talbot, R.E.

doi:10.1016/0011-9164(83)87060-x

Cited by 6 publications

(2 citation statements)

References 2 publications

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“…Various models have been developed to correlate the formation of scale on heat transfer surfaces over the last sixty years, and these models are not limited to desalination units. The earliest of these, proposed by Kern and Seaten, was based on a diffusion model in which the net rate of deposition is the difference between the rate of deposition and rate of removal at any given time, correlating an increase in fluid velocity with a reduction in fouling layer thickness [57,58]. Over the years, further modifications were incorporated into ionic diffusion models as well as kinetic models to predict the rate of scale deposition as a function of operating parameters and the use of antiscalants, including the use of computational fluid dynamics (CFD) [59][60][61][62][63][64][65].…”

Section: Modelling Approaches In Desalinationmentioning

confidence: 99%

Mathematical and optimization modelling in desalination: State-of-the-art and future direction

et al. 2019

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The growing water demand across the world necessitates the need for new and improved processes as well as for a better understanding of existing processes. This level of understanding includes predicting system performance in scenarios that cannot always be evaluated experimentally. Mathematical modelling is a crucial component of designing new and improved engineering processes. Through mathematically modelling real life systems, we gain a deeper understanding of processes while being able to predict performance more effectively. Advances in computational capacity and the ease of assessing systems allow researchers to study the feasibility of various systems. Mathematical modelling studies enable optimization performance parameters while minimizing energy requirements and, as such, have been an active area of research in desalination. In this review, the most recent developments in mathematical and optimization modelling in desalination are discussed with respect to transport phenomena, energy consumption, fouling predictions, and the integration of multiple scaling evolution on heat transfer surfaces has been reviewed. Similarly, developments in optimization of novel reverse osmosis (RO) configurations have been analyzed from an energy consumption perspective. Transport models for membranebased desalination processes, including relatively less understood processes such as nanofiltration and forward osmosis are presented, with recent modifications to allow for different solutes and solutions. Mathematical modelling of hybrid systems integrated with RO has also been reviewed. A survey of the literature shows that mathematical and optimization modelling of desalination processes is an exciting area for researchers in which future scholarship includes coupling of renewable energy systems with desalination technologies, as well as more advanced descriptions of fouling evolution other than that of cake filtration in membrane-based processes.

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Section: Modelling Approaches In Desalinationmentioning

confidence: 99%

Mathematical and optimization modelling in desalination: State-of-the-art and future direction

et al. 2019

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“…One of the early attempts to model fouling behaviour was conducted by Kern and Seaton [13]. They confirmed that the fluid velocity plays an important role in limiting the increase of the fouling thickness by considering a constant deposit rate and increasing removal rate, so that the process of fouling reaches steady state when the removal rate becomes equal to the deposition rate [14].…”

Section: Introductionmentioning

confidence: 99%

Dynamic modelling of Heat Exchanger fouling in multistage flash (MSF) desalination

Alsadaie

Mujtaba

2017

Desalination

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Fouling on heat transfer surfaces due to scale formation is the most concerned item in thermal desalination industry. Here, a dynamic fouling model is developed and incorporated into the MSF dynamic process model to predict fouling at high temperature and high velocity. The proposed dynamic model considers the attachment and removal mechanisms in the fouling phenomena with more relaxation of the assumptions such as the density of the fouling layer and salinity of the recycle brine. While calcium sulphate might precipitate at very high temperature, only the crystallization of calcium carbonate and magnesium hydroxide are considered in this work. Though the model is applied in a 24 stages brine recycle MSF plant, only the heat recovery section (21 stages) is considered under this study. The effect of flow velocity and surface temperature are investigated. By including both diffusion and reaction mechanism in the fouling model, the results of the fouling prediction model are in good agreement with most recent studies in the literature. The deposition of magnesium hydroxide increases with the increase in surface temperature and flow velocity while calcium carbonate deposition increases with the increase in the surface temperature and decreases with the increase in the flow velocity.

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An operating philosophy to optimise the output, plant life and economy of MSF plants operatin at high temperatures

Cooper¹,

Hanlon²,

Talbot³

1985

Desalination

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A model for the fouling of M.S.F. plants based on data from operating units

Cited by 6 publications

References 2 publications

Mathematical and optimization modelling in desalination: State-of-the-art and future direction

Mathematical and optimization modelling in desalination: State-of-the-art and future direction

Dynamic modelling of Heat Exchanger fouling in multistage flash (MSF) desalination

An operating philosophy to optimise the output, plant life and economy of MSF plants operatin at high temperatures

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