The conventional water network synthesis approach greatly simplifies wastewater treatment units by using fixed recoveries, creating a gap for their applicability to industrial processes. This work describes a unifying approach combining various technologies capable of removing all the major types of contaminants through the use of more realistic models. The following improvements are made over the typical superstructure-based water network models. First, unit-specific shortcut models are developed in place of the fixed contaminant removal model to describe contaminant mass transfer in wastewater treatment units. Shortcut wastewater treatment cost functions are also incorporated into the model. In addition, uncertainty in mass load of contaminants is considered to account for the range of operating conditions. Furthermore, the superstructure is modified to accommodate realistic potential structures. We present a modified Lagrangean-based decomposition algorithm in order to solve the resulting nonconvex mixed-integer nonlinear programming (MINLP) problem efficiently. Several examples are presented to illustrate the effectiveness and limitations of the algorithm for obtaining the global optimal solutions.

The evolution of the concentration polarization layer during crossflow reverse osmosis in a slit channel has been studied. Digital Holographic Interferometry allows visualizing the polarization layer as an interference fringe pattern. An especial module with four windows has been designed to see the development of the polarization layer along the membrane channel. Several experiments with a constant transmembrane pressure of 6 bar, three different feed concentrations (3, 6 and 9 kg/m 3 ) and three different Re (13, 38 and 111) had been carried out. The process has been modelled simulating the experimental conditions. The computed results were found to be consistent with the experimental ones. All the experiments show a continuous increase of the polarization layer along the channel, regardless of the crossflow velocity, except near the outlet of the cell due to an edge effect. This increase in the polarization layer is greater at lower Re, although it does not influence very much the permeate flux. In contrast, what substantially affects the permeate flux, much more than Re number, is the feed concentration due to its osmotic pressure.

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Shale gas has emerged as a potential resource to transform the global energy market. Nevertheless, gas extraction from tight shale formations is only possible after horizontal drilling and hydraulic fracturing, which generally demand large amounts of water. Part of the ejected fracturing fluid returns to the surface as flowback water, containing a variety of pollutants. For this reason, water reuse and water recycling technologies have received further interest for enhancing overall shale gas process efficiency and sustainability. Water pretreatment systems (WPSs) can play an important role for achieving this goal. This paper introduces a new optimization model for WPS simultaneous synthesis, especially developed for flowback water from shale gas production. A multistage superstructure is proposed for the optimal WPS design, including several water pretreatment alternatives. The mathematical model is formulated via generalized disjunctive programming (GDP) and solved by re-formulation as a mixed-integer nonlinear programming (MINLP) problem, to minimize the total annualized cost. Hence, the superstructure allows identifying the optimal pretreatment sequence with minimum cost, according to inlet water composition and wastewater-desired destination (i.e., water reuse as fracking fluid or recycling). Three case studies are performed to illustrate the applicability of the proposed approach under specific composition constraints. Thus, four distinct flowback water compositions are evaluated for the different target conditions. The results highlight the ability of the developed model for the cost-effective WPS synthesis, by reaching the required water compositions for each specified destination.