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Motivated by the inability of classical computational plasticity to fully exploit modern scientific computing, a multifield formulation for finite strain plasticity is presented. This avoids a local integration of the elastoplastic model. In the multifield approach, the balance of linear momentum, the flow relation and the Karush–Kuhn–Tucker constraints are collectively cast in a variational format. In addition to the deformation, both the plastic strain and the consistency parameter are global degrees of freedom in the resulting spatially discrete problem. The ensuing proliferation of global degrees of freedom in the multifield approach is addressed by exploiting the block sparse structure of the algebraic system together with a tailored block matrix solver which can utilise emerging hardware architectures. A series of numerical problems demonstrate the validity, capability and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

The aggregated unfitted finite element method (AgFEM) is a methodology recently introduced in order to address conditioning and stability problems associated with embedded, unfitted, or extended finite element methods. The method is based on removal of basis functions associated with badly cut cells by introducing carefully designed constraints, which results in well-posed systems of linear algebraic equations, while preserving the optimal approximation order of the underlying finite element spaces. The specific goal of this work is to present the implementation and performance of the method on distributed-memory platforms aiming at the efficient solution of large-scale problems. In particular, we show that, by considering AgFEM, the resulting systems of linear algebraic equations can be effectively solved using standard algebraic multigrid preconditioners. This is in contrast with previous works that consider highly customized preconditioners in order to allow one the usage of iterative solvers in combination with unfitted techniques. Another novelty with respect to the methods available in the literature is the problem sizes that can be handled with the proposed approach. While most of previous references discussing linear solvers for unfitted methods are based on serial non-scalable algorithms, we propose a parallel distributed-memory method able to efficiently solve problems at large scales. This is demonstrated by means of a weak scaling test defined on complex 3D domains up to 300M degrees of freedom and one billion cells on 16K CPU cores in the Marenostrum-IV platform. The parallel implementation of the AgFEM method is available in the large-scale finite element package FEMPAR. [ABSTRACT FROM AUTHOR]