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SIAMSC

2010

2010

This paper develops a nested iteration algorithm to solve time-dependent nonlinear systems of partial diﬀerential equations. For each time step, Newton’s method is used to form approximate solutions from a sequence of nested spaces, where the resolution of the approximations increases as the algorithm progresses. Nested iteration results in most of the iterations being performed on coarser grids, where minimal work is needed to reduce error to the level of discretization error. The approximate solution on a given coarse grid is interpolated to a reﬁned grid and used as an initial guess for the problem posed there. The approximation is then already close enough to the solution on the current grid that a minimal amount of work is needed to solve the reﬁned problem, due to the rapid convergence of Newton’s method near a solution. The paper develops an algorithm that attempts to optimize accuracy-percomputational-cost on each grid, so that essentially no unnecessary work is done ...

Added |
30 Jan 2011 |

Updated |
30 Jan 2011 |

Type |
Journal |

Year |
2010 |

Where |
SIAMSC |

Authors |
J. H. Adler, Thomas A. Manteuffel, Stephen F. McCormick, John Ruge, G. D. Sanders |

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