Surrogate Models for Distillation Boundaries in Azeotropic Multicomponent Mixtures

Industrial & Engineering Chemistry Research, vol. 63, pp. 13723–13739

Abstract

The accurate approximation of distillation boundaries is of crucial importance for evaluating the feasibility and conceptual design of distillation-based processes for the separation of azeotropic multicomponent mixtures. The lack of an explicit mathematical model for distillation boundaries is a major limitation for the application of shortcut models in the synthesis and design of distillation-based processes. In order to overcome this limitation, this work proposes a generalized method to derive surrogate models for distillation boundaries in multicomponent systems that are applicable for flowsheet evaluation and optimization during the conceptual design of distillation processes. On the basis of an extensive screening, a Gaussian process model combined with the quasi-random Halton sequence as sampling method was found to provide the best surrogate models for the use in flowsheet optimization. The benefits of integrating these surrogate models into hybrid process models are demonstrated in two case studies that show a reduction of up to 95% in the computational cost of process optimization while maintaining the accuracy of purely mechanistic modeling approaches.

Authors 4

1. Marian Panofen Aachen Process Systems Engineering (AVT.SVT)

   TU Dortmund University · RWTH Aachen University

   Affiliation as printed

   Laboratory of Fluid Separations, Department of Biochemical and Chemical Engineering, TU Dortmund University, Emil-Figge-Str. 70, 44227 Dortmund, Germany

   Process Systems Engineering (AVT.SVT), RWTH Aachen University, Forckenbeckstr. 51, 52074 Aachen, Germany

2. Thulasi Rolland

   TU Dortmund University · Hamburg University of Technology

   Affiliation as printed

   Institute of Process Systems Engineering, Hamburg University of Technology, Am Schwarzenberg-Campus 4, 21073 Hamburg, Germany

   Laboratory of Fluid Separations, Department of Biochemical and Chemical Engineering, TU Dortmund University, Emil-Figge-Str. 70, 44227 Dortmund, Germany

3. Jerzy Pela

   TU Dortmund University

   Affiliation as printed

   Laboratory of Fluid Separations, Department of Biochemical and Chemical Engineering, TU Dortmund University, Emil-Figge-Str. 70, 44227 Dortmund, Germany

4. Mirko Skiborowski corresponding

   TU Dortmund University · Hamburg University of Technology

   Affiliation as printed

   Institute of Process Systems Engineering, Hamburg University of Technology, Am Schwarzenberg-Campus 4, 21073 Hamburg, Germany

   Laboratory of Fluid Separations, Department of Biochemical and Chemical Engineering, TU Dortmund University, Emil-Figge-Str. 70, 44227 Dortmund, Germany