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Generalized initialization for the dynamic simulation and optimization of grade transition processes using two‐dimensional collocation
Author(s) -
Lin Xiaowen,
Chen Xi,
Biegler Lorenz T.
Publication year - 2021
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.17053
Subject(s) - initialization , collocation (remote sensing) , mathematical optimization , computer science , orthogonal collocation , dynamic simulation , state variable , scale (ratio) , collocation method , mathematics , simulation , mathematical analysis , ordinary differential equation , physics , quantum mechanics , machine learning , differential equation , thermodynamics , programming language
Optimization modeling tools are essential to determine optimal design specifications and operation conditions of polymerization processes, especially when quality indices based on molecular weight distributions (MWDs) must be enforced. This study proposes a generalized MWD‐based optimization strategy using orthogonal collocation in two dimensions, which can capture the dynamic features of MWDs accurately. To enable the strategy, this study considers generalized initialization methods for large‐scale simulation and optimization. Here, a homotopy method based on intermediate solutions is adopted to generate initial values for general steady‐state simulation models, starting from an arbitrary known solution for any steady‐state simulation model. For dynamic simulation models, the response of a first‐order linear system is adopted to initialize the state variables. Case studies show the effectiveness of this procedure to enable systematic, reliable, and efficient solution of the optimization problem.