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On convergence of waveform relaxation for nonlinear systems of ordinary differential equations
On convergence of waveform relaxation for nonlinear systems of ordinary differential equations
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On convergence of waveform relaxation for nonlinear systems of ordinary differential equations
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On convergence of waveform relaxation for nonlinear systems of ordinary differential equations
On convergence of waveform relaxation for nonlinear systems of ordinary differential equations
Journal Article

On convergence of waveform relaxation for nonlinear systems of ordinary differential equations

2024
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Overview
To integrate large systems of nonlinear differential equations in time, we consider a variant of nonlinear waveform relaxation (also known as dynamic iteration or Picard–Lindelöf iteration), where at each iteration a linear inhomogeneous system of differential equations has to be solved. This is done by the exponential block Krylov subspace (EBK) method. Thus, we have an inner-outer iterative method, where iterative approximations are determined over a certain time interval, with no time stepping involved. This approach has recently been shown to be efficient as a time-parallel integrator within the PARAEXP framework. In this paper, convergence behavior of this method is assessed theoretically and practically. We examine efficiency of the method by testing it on nonlinear Burgers, Liouville–Bratu–Gelfand, and nonlinear heat conduction equations and comparing its performance with that of conventional time-stepping integrators.

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