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Dyanmic compartmental models for separation processes
Author(s) -
Benallou A.,
Seborg D. E.,
Mellichamp D. A.
Publication year - 1986
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.690320703
Subject(s) - robustness (evolution) , orthogonal collocation , linearization , control theory (sociology) , reduction (mathematics) , state variable , mathematics , steady state (chemistry) , computer science , separation (statistics) , mathematical optimization , algorithm , nonlinear system , collocation method , chemistry , differential equation , control (management) , thermodynamics , physics , mathematical analysis , statistics , ordinary differential equation , biochemistry , geometry , quantum mechanics , artificial intelligence , gene
A low‐order modeling technique for separation processes is developed by considering a staged column as a compartment system in which a number of stage are lumped to form an equivalent stage. This method leads to low‐order models of separation processes directly and without linearization. Moreover, the resulting models have state variables and parameters that are physically significant. In contrast to alternative model reduction methods, compartmental analysis guarantees preservation of both material balances and steady states for arbitrary changes in the input variables. A comparison of compartmental analysis to a recently proposed technique based on orthogonal collocation, both methods incorporating an equimolal overflow assumption, shows the efficiency and robustness of the compartmental method.