The phrase "convergence acceleration" is correct and usable in written English.
It is most often used in scientific writing to mean a process or phenomenon wherein two or more phenomena rapidly approach one another. For example: The convergence acceleration of the two particles allowed scientists to measure the rate of the reaction.
We introduce the Newton Picard method, a hybrid convergence acceleration method and compare its performance to the performance of existing convergence accelerating techniques.
Convergence acceleration is accomplished by a nonlinear multigrid method.
The use of certain techniques for convergence acceleration is studied.
The scheme combines and truncates the pseudospectral representation of derivative for convergence acceleration.
For convergence acceleration, local time stepping is extended to Lagrangian pdf methods.
We address the issue of convergence acceleration by applying multigrid techniques to the kinetic discretization.
Numerical examples demonstrate effectiveness in handling rank deficiency and efficiency in convergence accelerations in these BCGLS forms.
Strong convergence accelerations are achieved by a local source term-dependent damping of the restricted residual error.
Based on the pattern of eigenvalues distributions for various flow configurations, the feasability of applying existing convergence-acceleration techniques like eigenvalue annihilation and relaxation are discussed.
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The different error types, stopping criterion, recovered orders of convergence, and acceleration rates are illustrated, as well as the effects of the rotational corrections and time-integration schemes.
