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Related papers: Method of invariant manifold for chemical kinetics

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In this paper, we review the construction of low-dimensional manifolds of reduced description for equations of chemical kinetics from the standpoint of the method of invariant manifold (MIM). MIM is based on a formulation of the condition…

Materials Science · Physics 2016-08-31 A. N. Gorban , I. V. Karlin , A. Yu. Zinovyev

We present the Constructive Methods of Invariant Manifolds for model reduction in physical and chemical kinetics, developed during last two decades. The problem of reduced description is studied as a problem of constructing the slow…

Condensed Matter · Physics 2007-05-23 A. N. Gorban , I. V. Karlin , A. Yu. Zinovyev

The Method of Invariant Grid (MIG) is a model reduction technique based on the concept of slow invariant manifold (SIM), which approximates the SIM by a set of nodes in the concentration space (invariant grid). In the present work, the MIG…

Statistical Mechanics · Physics 2007-12-17 E. Chiavazzo , I. V. Karlin , C. E. Frouzakis , K. B. Boulouchos

The Method of Invariant Grid (MIG) is an iterative procedure for model reduction in chemical kinetics which is based on the notion of Slow Invariant Manifold (SIM) [1-4]. Important role, in that method, is played by the initial grid which,…

Statistical Mechanics · Physics 2008-06-03 E. Chiavazzo , I. V. Karlin

The adoption of detailed mechanisms for chemical kinetics often poses two types of severe challenges: First, the number of degrees of freedom is large; and second, the dynamics is characterized by widely disparate time scales. As a result,…

Dynamical Systems · Mathematics 2025-10-01 Eliodoro Chiavazzo , C. William Gear , Carmeline J. Dsilva , Neta Rabin , Ioannis G. Kevrekidis

Reaction rates of chemical reactions under nonequilibrium conditions can be determined through the construction of the normally hyperbolic invariant manifold (NHIM) [and moving dividing surface (DS)] associated with the transition state…

This article concerns two methods for reducing large systems of chemical kinetics equations, namely, the method of intrinsic low-dimensional manifolds (ILDMs) due to Maas and Pope and an iterative method due to Fraser and further developed…

Dynamical Systems · Mathematics 2009-11-07 Hans G. Kaper , Tasso J. Kaper

Chemical kinetic models in terms of ordinary differential equations correspond to finite dimensional dissipative dynamical systems involving a multiple time scale structure. Most dimension reduction approaches aimed at a slow…

Dynamical Systems · Mathematics 2014-10-27 Dirk Lebiedz , Jonas Unger

The paper has two goals: It presents basic ideas, notions, and methods for reduction of reaction kinetics models: quasi-steady-state, quasi-equilibrium, slow invariant manifolds, and limiting steps. It describes briefly the current state of…

Chemical Physics · Physics 2022-05-17 A. N. Gorban

The theory of slow invariant manifolds (SIMs) is the foundation of various model-order reduction techniques for dissipative dynamical systems with multiple time-scales, e.g. in chemical kinetic models. The construction of SIMs and many…

Dynamical Systems · Mathematics 2022-01-19 Johannes Poppe , Dirk Lebiedz

Some model reduction techniques for multiple time-scale dynamical systems make use of the identification of low dimensional slow invariant attracting manifolds (SIAM) in order to reduce the dimensionality of the phase space by restriction…

Dynamical Systems · Mathematics 2017-07-11 Pascal Heiter , Dirk Lebiedz

Invariant manifolds are important constructs for the quantitative and qualitative understanding of nonlinear phenomena in dynamical systems. In nonlinear damped mechanical systems, for instance, spectral submanifolds have emerged as useful…

Computational Engineering, Finance, and Science · Computer Science 2021-10-15 Shobhit Jain , George Haller

This paper presents a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduced-order models (ROMs) by embedding a high-dimensional system…

Numerical Analysis · Mathematics 2026-01-09 Jiaming Guo , Dunhui Xiao

We present a physics-informed neural network (PINN) approach for the discovery of slow invariant manifolds (SIMs), for the most general class of fast/slow dynamical systems of ODEs. In contrast to other machine learning (ML) approaches that…

Numerical Analysis · Mathematics 2025-06-24 Dimitrios G. Patsatzis , Lucia Russo , Constantinos Siettos

Model reduction methods are relevant when the computation time of a full convection-diffusion-reaction simulation based on detailed chemical reaction mechanisms is too large. In this article, we review a model reduction approach based on…

Computational Physics · Physics 2014-05-20 Dirk Lebiedz , Jochen Siehr

We propose a hybrid physics-informed machine learning framework to approximate invariant manifolds (IMs) of discrete-time dynamical systems driven by exogenous autonomous dynamics (exosystems). Such systems appear in applications ranging…

In this paper, we introduce a fictitious dynamics for describing the only fast relaxation of a stiff ordinary differential equation (ODE) system towards a stable low-dimensional invariant manifold in the phase-space (slow invariant manifold…

Statistical Mechanics · Physics 2025-10-01 Eliodoro Chiavazzo

In dissipative ordinary differential equation systems different time scales cause anisotropic phase volume contraction along solution trajectories. Model reduction methods exploit this for simplifying chemical kinetics via a time scale…

Dynamical Systems · Mathematics 2011-01-13 Dirk Lebiedz , Volkmar Reinhardt , Jochen Siehr

This paper aims at reviewing nonlinear methods for model order reduction of structures with geometric nonlinearity, with a special emphasis on the techniques based on invariant manifold theory. Nonlinear methods differ from linear based…

Numerical Analysis · Mathematics 2022-05-26 Cyril Touzé , Alessandra Vizzaccaro , Olivier Thomas

Chemical reactions modeled by ordinary differential equations are finite-dimensional dissipative dynamical systems with multiple time-scales. They are numerically hard to tackle -- especially when they enter an optimal control problem as…

Optimization and Control · Mathematics 2017-03-27 Marcus Heitel , Dirk Lebiedz
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