CONCLUSIONES Y RECOMENDACIONES

Fouling prediction in RO processes have been reviewed by a number of authors (El- Manharawy 1999, Barger 1991). Barger and Carnahan (1991) described three fouling models – the gel-polarization model, resistance – in – series approach, and transport – accumulation approach. Each model takes into account a set of criteria to explain fouling, but none of them are based on comprehensive criteria. For instance, the gel- polarization model considers a layer of molecules of constant concentration, which aggregate into a gel deposit that is formed at the membrane surface. Gel concentration, in this model, depends on the morphological, physical, and chemical properties of the

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feed water, but not on feed concentration, operating pressure, membrane materials, or the hydraulic conditions in the system (Rautenbach 1989, Barger 1991). As a result, the model has reduced connection with the fluid dynamics of colloid particles, and cannot explain cake formation.

Figure 2.1 - Representation of the resistant encountered by flow through a fouled membrane.

Ho and Zydney (2001) have developed a fouling model that accounts for simultaneous pore blockage and cake formation, with the cake layer only forming over those regions of the membrane that have first been blocked by an initial deposit. This model assumed that the initial flux decline arises from pore blockage by the physical deposition of large aggregates on the membrane surface and that this is incorporated into a cake layer (Ho and Zydney, 2001). The filtrate flux through the blocked pores was evaluated using Darcy’s law assuming a resistance in series model:

J blocked = _P.μ.(Rm + Rc) (1)

where -_P is the transmembrane pressure, μ the solution viscosity, Rm the membrane resistance, and Rc the resistance of the filter acid cake that forms over the membrane surface.

The resistance-in-series model assumes that the water flux is proportional to the change in pressure. The gel concentration model uses the proportionality constant, originally developed for UF system, and is then interpreted as the system's resistance to product water flow instead of the permeation coefficient (Rautenback 1989). The model sometimes applies to the fouling potential of low (<70%) recovery RO system, which is a major limitation of the model. While the resistance-in-series model can also help with

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understanding of silica scale formation, overall it is more applicable to crystal deposit on the membrane surface and less to amorphous silica.

The individual components of these feedwaters will affect each other’s solubility, growth kinetics, and concentration polarization. These essential factors would have to be experimentally determined for each feedwater to provide any basis at all for an accurate analysis by this method. For natural CSG waters it will be difficult to apply this approach as the RO feed can slightly change over the life time of the CSG project as a result of water quality changes (Whitehouse 1995). The presence of dissolved silica species in relatively high salinity natural CSG water and practical silica solubility will be more important. Nevertheless, the model is useful for understanding the concept of silicate deposit formation on the membrane surface.

The transport – accumulation approach model is based on a numerical solution of the governing field equations for a fouling system. This equation is often simplified to:

Qw = A * (NDP)

Where Qw is the rate of water flow through the membrane, A represents a unique constant for each membrane material type, and NDP is the net driving pressure or net driving force for the mass transfer of water across the membrane. The model includes an accumulation term in the equation for the mass balance at the membrane surface. For instance, for slightly soluble salts, this term requires knowledge of the salt's solubility, crystallization growth parameters, adsorption characteristics, and particle trajectory in the flow channel (Rautenbach 1989, Semiat 1996). According to Cohen (2006), a velocity profile must be developed for the defined channel geometry and flow regime, and this is then used to solve the continuity equation. At this point, the solution scheme uses the mass of the particles formed to calculate its velocity and trajectory towards the membrane. Once a particle reaches the membrane, its mass is added to that of any existing fouling layer. The pure water flux is calculated from an updated cake resistance, and the entire scheme is checked using a new mass balance calculation. While one particle may reach the membrane surface, the model also allows for simultaneous formation, growth, and transport of other particles. This dynamic model can be credited with variable success for soluble, slightly soluble, and organic solutes,

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as well as for colloidal suspensions, when compared to related experimental results. This model seem to be supported by experimental results obtained by many (Exley 1993, Gabelish 2005, El-Manharawy 2000), especially for the batch processing of designated feedwaters and for the continuous flow of highly soluble salts such as sodium chloride.

Regardless of the model used, experimental work is necessary to verify the silica scaling conditions including the silica solubility limit in a range of water matrices, impact of salt, salt concentrations, and presence of other cations such as aluminium in particular. Any form of modelling chosen to explain fouling and/or scale formation mechanisms for a particular water matrix would depend on the completion of sufficient experimental work to define chemical precipitation fouling of RO membranes, so that some insight into the physical and chemical interactions involved could be gleaned from the experimental data.