Simultaneous synthesis and design of reaction–separation–recycle processes using rigorous models

Yingjie Ma, Zekun Yang, Aline El-Khoruy, Nan Zhang, Jie Li*, Bingjian Zhang, Li Sun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
11 Downloads (Pure)

Abstract

Simultaneous synthesis and design of reaction–separation–recycle processes using rigorous models is highly desirable to improve process efficiency. However, it often leads to a large-scale highly challenging optimization problem. In this work, we propose a computationally efficient optimization framework for the challenging problem. The reactor and separator networks are modeled using the generalized disjunctive programming, which are reformulated into a highly nonconvex mixed-integer nonlinear programming (MINLP) formulation using the convex-hull method. To solve the complex MINLP model, a systematic solution approach is proposed in which an initialization strategy is first proposed to generate a feasible solution for a partially relaxed synthesis problem using the hybrid steady-state and time-relaxation optimization algorithm. A successive relaxed MINLP solution strategy is then adopted to solve the original model to local optimality. The computational results demonstrate that the proposed framework obtains better solutions with less computational effort, by ∼1 order of magnitude, than the existing algorithms.
Original languageEnglish
Pages (from-to)7275-7290
Number of pages16
JournalIndustrial & Engineering Chemistry Research
Volume60
Issue number19
Early online date29 Apr 2021
DOIs
Publication statusPublished - 19 May 2021

Keywords

  • algorithms
  • optimization
  • separation science
  • distillation
  • superstructures

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