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- W2130756427 abstract "Inexact Newton algorithms are commonly used for solving large sparse nonlinear system of equations $F(u^{ast})=0$ arising, for example, from the discretization of partial differential equations. Even with global strategies such as linesearch or trust region, the methods often stagnate at local minima of $|F|$, especially for problems with unbalanced nonlinearities, because the methods do not have built-in machinery to deal with the unbalanced nonlinearities. To find the same solution $u^{ast}$, one may want to solve instead an equivalent nonlinearly preconditioned system ${cal F}(u^{ast})=0$ whose nonlinearities are more balanced. In this paper, we propose and study a nonlinear additive Schwarz-based parallel nonlinear preconditioner and show numerically that the new method converges well even for some difficult problems, such as high Reynolds number flows, where a traditional inexact Newton method fails." @default.
- W2130756427 created "2016-06-24" @default.
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- W2130756427 date "2002-01-01" @default.
- W2130756427 modified "2023-09-23" @default.
- W2130756427 title "Nonlinearly Preconditioned Inexact Newton Algorithms" @default.
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- W2130756427 doi "https://doi.org/10.1137/s106482750037620x" @default.
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