The retrofit design of a network of processes over several time periods is addressed in this paper. A strategy is proposed that consists of a high level to analyze the entire network, and a low level to analyze a specific process flowsheet in detail. A methodology is presented for the high level to model process flowsheets and retrofit modifications using a multiperiod generalized disjunctive programming (GDP) model. This problem is reformulated as a mixed-integer linear program (MILP) using the convex hull formulation. Two examples that illustrate the proposed model are presented. The results show that the proposed GDP model provides a significant benefit over the existing network without retrofit, and provides a clear advantage over intuitively choosing modifications based on heuristics. To illustrate the performance benefits of using the convex hull formulation, the problem is also modeled as an MILP with big-M constraints.

The reactor network synthesis problem involves determining the type, size, and interconnections of the reactor units, optimal concentration and temperature profiles, and the heat load requirements of the process. A general framework is presented for the synthesis of optimal chemical reactor networks via an optimization approach. The possible design alternatives are represented via a process superstructure which includes continuous stirred tank reactors and cross flow reactors along with mixers and splitters that connect the units. The superstructure is mathematically modeled using differential and algebraic constraints and the resulting problem is formulated as an optimal control problem. The solution methodology for addressing the optimal control formulation involves the application of a control parameterization approach where the selected control variables are discretized in terms of time invariant parameters. The dynamic system is decoupled from the optimization and solved as a func...

We propose several linear programming (LP) models for attainable region (AR) analysis by considering a rate vector field in concentration space with an arbitrarily large number of points. One model provides a method to construct candidate ARs using a fully connected network of CSTRs of arbitrary volume.