TY - CHAP
T1 - Simultaneous Synthesis and Design of Integrated Reaction-Separation Systems Using Rigorous Models
AU - Ma, Yingjie
AU - El-Khoruy, Aline
AU - Yang, Zekun
AU - Sun, Li
AU - Zhang, Nan
AU - Li, Jie
AU - Xiao, Xin
PY - 2019
Y1 - 2019
N2 - Simultaneous synthesis and design of integrated reaction-separation processes using rigorous models is highly desirable to improve process performance. However, it often leads to a large-scale highly nonlinear nonconvex mixed-integer nonlinear programming model, which is difficult to solve. In this work, we propose a computationally-efficient optimization framework for simultaneous synthesis and design using rigorous models. The reactor and separation network are modelled using generalized disjunctive programming (GDP), which is reformulated into a mixed-integer nonlinear programming model using the convex-hull method. The activeness and inactiveness of a tray in a distillation column is modelled using the bypass efficiency method without introduction of integer variables, leading to significant reduction in the number of integer variables. To solve the model to local optimality, a systematic solution approach is proposed in which the pseudo-transient continuation model is used to generate a good starting point for optimization. The complementary conditions are added step by step to avoid infeasibility and ensure bypass efficiency variables be 0 or 1 only. An example from literature is solved to illustrate the capacity of the proposed optimization framework. The computational results demonstrate that the proposed optimization framework generates the local optimal solution of 2.13 M$/year within 58 CPU seconds. Significant reduction in computational efforts by 85% and improvement in solution quality by 5% are achieved compared to the existing approach.
AB - Simultaneous synthesis and design of integrated reaction-separation processes using rigorous models is highly desirable to improve process performance. However, it often leads to a large-scale highly nonlinear nonconvex mixed-integer nonlinear programming model, which is difficult to solve. In this work, we propose a computationally-efficient optimization framework for simultaneous synthesis and design using rigorous models. The reactor and separation network are modelled using generalized disjunctive programming (GDP), which is reformulated into a mixed-integer nonlinear programming model using the convex-hull method. The activeness and inactiveness of a tray in a distillation column is modelled using the bypass efficiency method without introduction of integer variables, leading to significant reduction in the number of integer variables. To solve the model to local optimality, a systematic solution approach is proposed in which the pseudo-transient continuation model is used to generate a good starting point for optimization. The complementary conditions are added step by step to avoid infeasibility and ensure bypass efficiency variables be 0 or 1 only. An example from literature is solved to illustrate the capacity of the proposed optimization framework. The computational results demonstrate that the proposed optimization framework generates the local optimal solution of 2.13 M$/year within 58 CPU seconds. Significant reduction in computational efforts by 85% and improvement in solution quality by 5% are achieved compared to the existing approach.
KW - disjunctive programming
KW - Integrated reaction-separation system
KW - mixed-integer nonlinear programming
KW - process synthesis and design
KW - rigorous models
UR - http://www.scopus.com/inward/record.url?scp=85069939445&partnerID=8YFLogxK
U2 - 10.1016/B978-0-12-818597-1.50059-X
DO - 10.1016/B978-0-12-818597-1.50059-X
M3 - Chapter
AN - SCOPUS:85069939445
T3 - Computer Aided Chemical Engineering
SP - 371
EP - 376
BT - Computer Aided Chemical Engineering
PB - Elsevier BV
ER -