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From inexact active set strategies to nonlinear multigrid methods

机译:从不精确的活动集策略到非线性多重态方法

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1 Introduction Due to their efficiency and robustness, linear multigrid methods lend themselves to be a starting point for the development of nonlinear iterative strategies for the solution of nonlinear contact problems, see, e.g., [3, 1, 10, 5]. One nonlinear strategy is to reduce the contact problem to a sequence of linear problems and to solve each of these by a linear multigrid method. This approach is often connected to active set strategies or semismooth Newton methods [6]. To avoid solving the linear problems exactly, one can use inexact active set strategies, see [7, 8]. The convergence of this inexact strategy depends on the accuracy the inner problem is solved with, see [7], as well as on algorithmic parameters [8]. A second strategy is to deal directly with the nonlinearity within the multigrid method by using, e.g., nonlinear smoothers and nonlinear interpolation operators, see [10, 9, 1]. Using the convex energy for controlling the iteration process, globally convergent nonlinear multigrid methods can be constructed which allow for solving contact problems with the speed of a linear multigrid method [10]. A third possibility is to employ a saddle point approach [3] and to solve for the primal and dual variables simultaneously using an algebraic multigrid method.
机译:1引言由于它们的效率和鲁棒性,线性多重型方法为非线性接触问题解决非线性迭代策略的起点,例如[3,1,1,10,5]。一个非线性策略是将接触问题降低到线性问题的序列并通过线性多字节方法来解决这些问题。这种方法通常与活动集策略或半导体牛顿方法连接[6]。为避免精确解决线性问题,可以使用不精确的活动集策略,参见[7,8]。这种不精确策略的收敛取决于内部问题解决的准确性,参见[7],以及算法参数[8]。第二种策略是通过使用,例如非线性SmoIrons和非线性插值运算符直接处理多重型方法内的非线性,参见[10,9,1]。使用用于控制迭代过程的凸能量,可以构建全局收敛非线性多重格引线方法,其允许用线性多字节方法的速度求解接触问题[10]。第三种可能性是采用鞍点方法[3]并使用代数多重资源方法同时求解原始和双变量。

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