Abstract
The formulation of a kinetic model for a complex reaction network typically yields reaction rates which vary over orders of magnitude. This results in time scale separation that makes the model inherently stiff. In this work, a graph-theoretic framework is developed for time scale decomposition of complex reaction networks to separate the slow and fast time scales, and to identify pseudo-species that evolve only in the slow time scale. The reaction network is represented using a directed bi-partite graph and cycles that correspond to closed walks are used to identify interactions between species participating in fast/equilibrated reactions. Subsequently, an algorithm which connects the cycles to form the pseudo-species is utilized to eliminate the fast rate terms. These pseudo-species are used to formulate reduced, non-stiff kinetic models of the reaction system. Two reaction systems are considered to show the efficacy of this framework in the context of thermochemical and biochemical processing.
Original language | English (US) |
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Pages (from-to) | 170-181 |
Number of pages | 12 |
Journal | Computers and Chemical Engineering |
Volume | 95 |
DOIs | |
State | Published - Dec 5 2016 |
Bibliographical note
Publisher Copyright:© 2016 Elsevier Ltd
Keywords
- Bi-partite graph
- Graph theory
- Lumping
- Model reduction