Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Combustion and Flame 155 (2008) 585604 www.elsevier.com/locate/combustflame
 

Summary: Combustion and Flame 155 (2008) 585604
www.elsevier.com/locate/combustflame
A graph-based approach to developing adaptive
representations of complex reaction mechanisms
Kaiyuan He, Marianthi G. Ierapetritou, Ioannis P. Androulakis
Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey,
Piscataway, NJ 08854, USA
Received 9 January 2008; received in revised form 9 May 2008; accepted 12 May 2008
Available online 13 June 2008
Abstract
An effective adaptive mechanism reduction approach based on flux graph clustering is proposed in this paper.
The instantaneous element flux is quantified and considered as a proxy for describing the reactive propensities
of the system. Our underlying hypothesis is that even though particular conditions may be characterized by a
multitude of combinations of species mass fraction, T , and P, the essential chemistry, and hence the reaction
propensity of the mixture that is active under this family of conditions, is the same. Therefore, we opt to use
the instantaneous fluxes through the active reactions as an intrinsic property of the system. Flux graphs are first
constructed for the chemical reaction system under numerous conditions aiming at capturing the attainable region.
Similarity between flux graphs is quantified through the distances between corresponding vectors, using the cosine
coefficient and a novel graph-distance metric taking into account the magnitude of each flux and the activity
distribution of different fluxes. A hierarchical clustering algorithm is implemented to group similar instantaneous

  

Source: Androulakis, Ioannis (Yannis) - Biomedical Engineering Department & Department of Chemical and Biochemical Engineering, Rutgers University
Rutgers University, Rutgers Center for Operations Research

 

Collections: Biology and Medicine; Engineering