We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The optimal synthesis of complex distillation columns is a non-trivial problem due to the discrete nature of the tray-by-tray column model, and also because of the high degree of non-linearity and non-convexity of the underlying MESH equations

No abstract

In this work, we analyse the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

No abstract

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.

No abstract

We present a systematic approach to optimize the thermal insulation of a building.  The optimization reduces simultaneously the cost and several environmental impacts.  We resort to an objective reduction method to simplify the problem resolution.  We built a surrogate model to expedite the search for Pareto optimal solutions.  Significant improvements compared to the base case (no insulation) are achieved.

Synthesis gas (syngas) is a mixture of H 2 , CO and occasionally CO 2 , whose main application is as a building block of chemical compounds. The desired product dictates the syngas characteristics, which are also affected by the employed syngas synthesis technology. In this work, we study the process of producing syngas under desired specifications while consuming CO 2 in the synthesis. We propose a superstructure that includes seven reforming technologies for the syngas production, as well as a variety of auxiliary units to control the final composition of the syngas. Each potential solution is assessed, in terms of the economic and environmental performance, by the Total Annualized Cost (TAC) and the Global Warming Potential (GWP) indicator. As the problem statement involves discrete decision, we use disjunctions to model the system. The resulting MINLP multi-objective problem is solved by the epsilon constraint method. Results show that at low syngas H 2 /CO ratios and pressures, dry methane reforming (DMR) is capable of net consuming CO 2 . Partial Oxidation (POX) is the technology that exhibits the minimum TAC, although shows the maximum value for the GWP.Synergistic combination of two processes allows reducing the cost and CO 2 -equivalent emissions through the pairing of DMR and bi-reforming (BR) and BR with steam methane reforming (SMR). Furthermore, increasing the CO 2 content in the syngas at a fixed (H 2 -CO 2 )/(CO + CO 2 ) ratio proves that TAC and GWP decrease as the CO 2 /CO ratio increases.