Optimal Groundwater Remediation Network Design Using Selective Membranes

Abstract

This work deals with the optimal synthesis of groundwater remediation networks for the valorization of anionic pollutants by means of emulsion pertraction technology using hollow fiber modules (HFM). Superstructures that incorporate all possible design alternatives are proposed. The aim of this work is to obtain a minimum cost groundwater remediation network that allows treatment of groundwater to required levels, and also, a contaminant rich solution that can be used for further processing. The optimization of the superstructure is initially formulated as a nonconvex nonlinear programming (NLP) problem. This rigorous NLP model is simplified using some assumptions to get a simplified model which is globally optimized using a Lagrangean decomposition algorithm. This globally optimal solution is used as an initialization point for optimizing the rigorous NLP problem. Three cases involving different numbers of HFM are studied to determine a cost optimized network with an optimal number of modules.

Optimization of Water Network Synthesis for Single-Site and Continuous Processes: Milestones, Challenges, and Future Directions

“…Recent work in process synthesis have increasingly involved rigorous optimization-based models particularly for the separation section, [109][110][111][112] but a relatively small number of work has been conducted that incorporate detailed mechanistic or phenomenological models on the subsystems of a water network. [113][114] While there is an appreciably rich literature on rigorous design models for wastewater treatment technologies (e.g., for reverse osmosis), 41,[115][116][117][118][119][120] there is a gap in the water network synthesis literature on papers that simultaneously optimizes their interactions with multiple water-using units by adopting such detailed models. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 approach is that a superstructure generated may not consider innovative alternatives previously unexplored or not discovered; (2) the combinatorial synthesis technique generates a superstructure by considering all possible interconnections involving all relevant materials (states) and operations (tasks), and hence may overcome the drawback of the foregoing approach.…”

“…Although regeneration technologies are inherently nonlinear, to the best of our knowledge, there have been few works to date that consider a detailed nonlinear regeneration model for water network synthesis. Recent works in process synthesis have increasingly involved rigorous optimization-based models particularly for the separation section, − but a relatively small numbers of works have been conducted that incorporate detailed mechanistic or phenomenological models on the subsystems of a water network. , While there is an appreciably rich literature on rigorous design models for wastewater treatment technologies (e.g., for reverse osmosis), ,− there is a gap in the water network synthesis literature on papers that simultaneously optimizes their interactions with multiple water-using units by adopting such detailed models.…”

A superstructure optimization approach for water network synthesis with membrane separation-based regenerators

“…Most optimization models that are tailored for membrane separation-based water treatment technology in the literature are nonlinear (Saif et al, 2008b;2008a;Bringas et al, 2007;San Roman et al, 2007;Galan and Grossmann, 1998). Hence at the outset, these models are relatively more computationally challenging to handle compared to our linear formulation.…”

A Superstructure Optimization Approach for Membrane Separation-Based Water Regeneration Network Synthesis with Detailed Nonlinear Mechanistic Reverse Osmosis Model

“…In general, there are two major approaches for addressing the water network synthesis problem, namely the insights-based and mathematical optimization techniques. The former typically involves water pinch analysis techniques, which offer good insights with low computational burden for process designers in network synthesis but often at the expense of requiring significant problem simplification. − On the other hand, optimization allows rigorous treatment of large-scale complex systems by considering representative cost functions, multiple contaminants, and various topological constraints, but it frequently suffers from the high computational expense required to achieve optimality. − Recent work in this area has increasingly witnessed the development of mathematical models of greater rigor and complexity that employ a framework driven by optimization-based approaches, primarily mathematical programming − as well as soft optimization methods such as fuzzy programming − and artificial intelligence-based metaheuristic algorithms. , Optimization-based techniques for reuse/recycle and regeneration networks also have been developed by numerous researchers using property-integration framework. − In several work, the overall optimization framework is coupled with physical insights derived from water pinch analysis. ,− The approach typically involves the construction of a superstructure-based network representation of design alternatives for the water system, in which the corresponding optimization model formulation embeds the following two parts. First is the structural optimization problem that selects the optimal water network structure from numerous feasible alternatives, as represented by 0–1 decision variables.…”