GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems
SIAM Journal on Scientific and Statistical Computing
SIAM Journal on Scientific and Statistical Computing
Monotone multigrid methods for elliptic variational inequalities I
Numerische Mathematik
Finite Element Approximation of the Cahn--Hilliard Equation with Degenerate Mobility
SIAM Journal on Numerical Analysis
A Note on Preconditioning for Indefinite Linear Systems
SIAM Journal on Scientific Computing
Semismooth Newton Methods for Operator Equations in Function Spaces
SIAM Journal on Optimization
The Primal-Dual Active Set Strategy as a Semismooth Newton Method
SIAM Journal on Optimization
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Conservative multigrid methods for Cahn-Hilliard fluids
Journal of Computational Physics
A multigrid finite element solver for the Cahn-Hilliard equation
Journal of Computational Physics
An Introduction to Algebraic Multigrid
Computing in Science and Engineering
deal.II—A general-purpose object-oriented finite element library
ACM Transactions on Mathematical Software (TOMS)
An adaptive finite-element Moreau-Yosida-based solver for a non-smooth Cahn-Hilliard problem
Optimization Methods & Software - Advances in Shape and Topology Optimization: Theory, Numerics and New Applications Areas
Preconditioning for Allen-Cahn variational inequalities with non-local constraints
Journal of Computational Physics
Inpainting of Binary Images Using the Cahn–Hilliard Equation
IEEE Transactions on Image Processing
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We consider the efficient solution of the Cahn-Hilliard variational inequality using an implicit time discretization, which is formulated as an optimal control problem with pointwise constraints on the control. By applying a semi-smooth Newton method combined with a Moreau-Yosida regularization technique for handling the control constraints we show superlinear convergence in function space. At the heart of this method lies the solution of large and sparse linear systems for which we propose the use of preconditioned Krylov subspace solvers using an effective Schur complement approximation. Numerical results illustrate the competitiveness of this approach.