Globally Optimal Networks for Multipressure Distillation of Homogeneous Azeotropic Mixtures

Abstract

In this article, a methodology for the globally optimal synthesis of a network of vapor–liquid equilibrium flash separators that can operate at multiple pressures and separate an azeotropic mixture is presented. The objective function minimized is the total flow entering the network flashes. The proposed synthesis methodology employs the infinite-dimensional state-space (IDEAS) conceptual framework, which is shown to be applicable to the problem under consideration. The resulting infinite linear programming (ILP) IDEAS formulation is shown to have several properties that allow its simplification. The approximate solution of this IDEAS ILP is pursued through the solution of a number of finite-dimensional linear programs (FLPs) of ever increasing size, whose optimum values form a sequence that converges to the ILP’s infimum. The proposed optimal design methodology is general in nature and can be used to separate any number of pressure-sensitive azeotropic mixtures, with or without use of an entrainer. The method is demonstrated on a first case study involving the dual-pressure separation of a methyl acetate/methanol binary mixture, which exhibits a minimum-boiling azeotrope, without using an entrainer, and a second case study involving the dual-pressure separation of a ternary mixture of water, methanol, and acetone that also exhibits a minimum-boiling azeotrope for the methanol/acetone binary mixture, again without using an entrainer. The IDEAS-generated globally optimal design is shown to be 31.54% better than an optimized, dual-pressure, traditional, two-column design for the binary mixture (case 1) and 15.15% better for the ternary mixture (case 2).