Abstract
Abstract The energy requirement for the separation of a given mixture via a multistage membrane cascade depends on the choice of the cascade and its operating conditions. Identifying the optimal cascade along with its optimal operating conditions is challenging, since it requires the solution of a nonconvex mathematical program. To address the challenge, we propose novel Mixed Integer Nonlinear Programs (MINLPs) that are formulated such that they can be solved using off-the-shelf global optimization solvers. We illustrate the practicality of our models with two case studies: (1) separation of p-xylene from o-xylene (2) recovery of natural gas liquid (NGL) from shale gas. Further, for NGL recovery, we determine the target selectivity and permeability that will enable membrane technology to outcompete the conventional demethanizer. These target values provide guidance for experimental groups that are developing new membrane materials for NGL recovery.
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