NDLI: Efficient calculation of intrinsic low-dimensional manifolds for the simplification of chemical kinetics

Content Provider	Springer Nature Link
Author	Maas, Ulrich
Copyright Year	1998
Abstract	During the last years the interest in the numerical simulation of reacting flows has grown considerably and numerical methods are available, which allow to couple chemical kinetics with flow and molecular transport. The use of detailed physical and chemical models, involving several hundred species, is restricted to very simple flow configurations like one-dimensional systems or two-dimensional systems with very simple geometries, and models are required, which simplify chemistry without sacrificing accuracy. One method to simplify the chemical kinetics is based on Intrinsic Low-Dimensional Manifolds (ILDM). They represent attractors for the chemical kinetics, i.e. fast chemical processes relax towards them, and slow chemical processes represent movements within the manifolds. Thus the identification of the ILDMs allows a decoupling of the fast time scales. The concept has been verified by many different reacting flow calculations. However, one remaining problem of the method is the efficient calculation of the low-dimensional manifolds. This problem is addressed in this paper. We present an efficient, robust method, which allows to calculate intrinsic low-dimensional manifolds of chemical reaction systems. It is based on a multi-dimensional continuation process. Examples are shown for a typical combustion system. The method is not restricted to this problem class, but can be applied to other reacting flows or dynamic systems provided that a large number of decaying components can be eliminated from the system.
Starting Page	69
Ending Page	81
Page Count	13
File Format	PDF
ISSN	14329360
Journal	Computing and Visualization in Science
Volume Number	1
Issue Number	2
Language	English
Publisher	Springer-Verlag
Publisher Date	1998-04-01
Publisher Place	Berlin Heidelberg
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Engineering Computational Theory and Mathematics Computer Vision and Pattern Recognition Modeling and Simulation Software

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