Dyanmic compartmental models for separation processes

TLDR

Compartmental analysis preserves material balances and steady states for arbitrary input changes, unlike alternative model reduction methods. The study develops a low‑order modeling technique for separation processes by treating a staged column as a lumped compartment system. By lumping stages into equivalent compartments, the method yields low‑order models of separation processes directly and without linearization. The resulting models have physically significant state variables and parameters, and a comparison with orthogonal collocation demonstrates the compartmental method’s efficiency and robustness.

Abstract

Abstract 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.