4.7 Article

Space-time formulation, discretization, and computational performance studies for phase-field fracture optimal control problems

Journal

JOURNAL OF COMPUTATIONAL PHYSICS
Volume 470, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2022.111554

Keywords

Space-time; Phase-field fracture; Optimal control; Reduced optimization approach; Galerkin discretization

Funding

  1. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [314067056]
  2. DFG - SFB1463 [434502799]

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The purpose of this work is to develop space-time discretization schemes for phase-field optimal control problems. The forward problem is discretized in time using a discontinuous Galerkin formulation, and the optimal control setting is formulated using the Lagrangian approach. The effectiveness of the method is demonstrated through six numerical experiments.
The purpose of this work is the development of space-time discretization schemes for phase-field optimal control problems. Specifically in the optimal control minimization problem, a tracking-type cost functional is minimized to steer the crack via the phase -field variable into a desired pattern. To achieve such optimal solutions, Neumann type boundary conditions need to be determined. First, a time discretization of the forward problem is derived using a discontinuous Galerkin formulation. Here, a challenge is to include regularization terms and the crack irreversibility constraint. The optimal control setting is formulated by means of the Lagrangian approach from which the primal part, adjoint, tangent and adjoint Hessian are derived. Herein the overall Newton algorithm is based on a reduced approach by eliminating the state constraint, namely the displacement and phase-field unknowns, but keeping the control variable as the only unknown. From the low-order discontinuous Galerkin discretization, adjoint time-stepping schemes are finally obtained. Both our formulation and algorithmic developments are substantiated and illustrated with six numerical experiments. (C) 2022 Elsevier Inc. All rights reserved.

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