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I analyse a generalised Burger's equation to develop an accurate finite difference approximation to its dynamics. The analysis is based upon centre manifold theory so we are assured that the finite difference model accurately models the…

chao-dyn · Physics 2007-05-23 A. J. Roberts

We analyse the nonlinear Kuramoto-Sivashinsky equation to develop an accurate finite difference approximation to its dynamics. The analysis is based upon centre manifold theory so we are assured that the finite difference model accurately…

Numerical Analysis · Mathematics 2025-10-20 T. MacKenzie , A. J. Roberts

We analyse the nonlinear Kuramoto--Sivashinsky equation to develop accurate discretisations modeling its dynamics on coarse grids. The analysis is based upon centre manifold theory so we are assured that the discretisation accurately models…

Dynamical Systems · Mathematics 2007-05-23 T. MacKenzie , A. J. Roberts

I previously used Burgers' equation to introduce a new method of numerical discretisation of \pde{}s. The analysis is based upon centre manifold theory so we are assured that the discretisation accurately models all the processes and their…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

Developments in dynamical systems theory provides new support for the discretisation of \pde{}s and other microscale systems. By systematically resolving subgrid microscale dynamics the new approach constructs asymptotically accurate,…

Numerical Analysis · Mathematics 2009-04-07 Tony MacKenzie , A. J. Roberts

I prove that a centre manifold approach to creating finite difference models will consistently model linear dynamics as the grid spacing becomes small. Using such tools of dynamical systems theory gives new assurances about the quality of…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

Coarse grained, macroscale, spatial discretisations of nonlinear nonautonomous partial differential\difference equations are given novel support by centre manifold theory. Dividing the physical domain into overlapping macroscale elements…

Dynamical Systems · Mathematics 2013-12-31 J. E. Bunder , A. J. Roberts

Constructing discrete models of stochastic partial differential equations is very delicate. Stochastic centre manifold theory provides novel support for coarse grained, macroscale, spatial discretisations of nonlinear stochastic partial…

Dynamical Systems · Mathematics 2010-03-09 A. J. Roberts

The long term aim is to use modern dynamical systems theory to derive discretisations of noisy, dissipative partial differential equations. As a first step we here consider a small domain and apply stochastic centre manifold techniques to…

Dynamical Systems · Mathematics 2025-10-20 A. J. Roberts

I introduce an innovative methodology for deriving numerical models of systems of partial differential equations which exhibit the evolution of spatial patterns. The new approach directly produces a discretisation for the evolution of the…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

Consider briefly the equations of fluid dynamics-they describe the enormous wealth of detail in all the interacting physical elements of a fluid flow-whereas in applications we want to deal with a description of just that which is…

chao-dyn · Physics 2016-08-31 A. J. Roberts

Partial differential equations (PDEs) describing thermodynamically isolated systems typically possess conserved quantities (like mass, momentum, and energy) and dissipated quantities (like entropy). Preserving these conservation and…

Numerical Analysis · Mathematics 2025-12-01 Boris D. Andrews , Patrick E. Farrell

In applications of centre manifold theory we need more flexible error estimates than that provided by, for example, the Approximation Theorem~3 by Carr (1981,1983). Here we extend the theory to cover the case where the order of…

Dynamical Systems · Mathematics 2007-05-23 Zhenquan Li , A. J. Roberts

Developments in dynamical systems theory provides new support for the macroscale modelling of pdes and other microscale systems such as Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators. By systematically resolving subgrid…

Numerical Analysis · Mathematics 2012-01-18 A. J. Roberts , Tony MacKenzie , J. E. Bunder

Finite difference/element/volume methods of discretising PDEs impose a subgrid scale interpolation on the dynamics. In contrast, the holistic discretisation approach developed herein constructs a natural subgrid scale field adapted to the…

Numerical Analysis · Mathematics 2016-02-04 G. A. Jarrad , A. J. Roberts

We investigate a fully discrete finite element approximation for the stochastic Kuramoto-Sivashinsky equation, combining the standard finite element methods in spatial discretization with the implicit Euler-Maruyama scheme in time. Rigorous…

Numerical Analysis · Mathematics 2025-10-08 Hung D. Nguyen , Liet Vo

The long-term dynamics of many dynamical systems evolve on an attracting, invariant "slow manifold" that can be parameterized by a few observable variables. Yet a simulation using the full model of the problem requires initial values for…

Computational Physics · Physics 2007-05-23 C. W. Gear , T. J. Kaper , I. G. Kevrekidis , A. Zagaris

Symmetry-preserving (mimetic) discretization aims to preserve certain properties of a continuous differential operator in its discrete counterpart. For these discretizations, stability and (discrete) conservation of mass, momentum and…

Numerical Analysis · Mathematics 2019-09-25 B. van 't Hof , M. J. Vuik

We present a new topological method for the study of the dynamics of dissipative PDE's. The method is based on the concept of the self-consistent apriori bounds, which allows to justify rigorously the Galerkin projection. As a result we…

Analysis of PDEs · Mathematics 2025-10-20 P. Zgliczynski , K. Mischaikow

Partial differential equations with discrete (concentrated) state-dependent delays are studied. The existence and uniqueness of solutions with initial data from a wider linear space is proven first and then a subset of the space of…

Analysis of PDEs · Mathematics 2010-11-11 Alexander V. Rezounenko , Petr Zagalak
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