arXiv subjects

Stephan Wulfinghoff

Publications and source records attributed to Stephan Wulfinghoff.

4 recordsLinked to original sources

arXiv2026

Sequential Subspace Mode Adaptation for the Reduced-Order Homogenization of Dissipative Microstructures using E3C Hyper-Reduction

Three-dimensional inelastic computational homogenization of complex engineering components requires a multitude of nonlinear microstructural simulations, making it computationally expensive. This work investigates a projection-based model order reduction (pMOR) method with 'Sequential Subspace Mode Adaptation', which can be easily integrated into existing codes using linear subspaces. Starting with a 'conventional' linear subspace strain approximation, the dynamic online construction of a second -- lower dimensional -- affine subspace embedded in the linear subspace determined offline leads to a further reduction of the dimensionality. A second novelty is the outline of the E3C hyper-reduction method for non-crystalline dissipative materials with internal variables, introducing a viscous regularization of non-differentiable stress-strain relations. In addition, a theoretical discussion is provided, illustrating that the E3C method aims at satisfaction of a projected and hyper-reduced variant of the classical Hill-Mandel macro-homogeneity condition. The latter theoretically implies equivalence with the high-dimensional model and satisfaction of both the hyper-reduced weak equilibrium and compatibility conditions. The influence of training batch size, material nonlinearity, and microstructure on the performance are evaluated through parameter studies. Three-dimensional elastoplastic two-scale simulations with hundreds of thousands of macroscopic degrees of freedom illustrate the efficiency and accuracy, with computational times approaching those of single scale simulations.

physics.comp-ph↗

arXiv2025

Computational Crystal Plasticity Homogenization using Empirically Corrected Cluster Cubature (E3C) Hyper-Reduction

The computational homogenization of elastoplastic polycrystals is a challenging task due to the huge number of grains required, their complicated interactions and due to the complexity of crystal plasticity models per se. Despite a few successes of reduced order models, mean field and simplified homogenization approaches often remain the preferred choice. In this work, a recently proposed hyper-reduction method (called E3C) for projection-based Reduced Order Models (pROMs) is applied to the problem of computational homogenization of geometrically linearly deforming elastoplastic polycrystals. The main novelty lies in the identification of reduced modes (the 'E3C-modes'), which replace the strain modes of the reduced-order model, leading to a significantly smaller number of integration points. The peculiarity, which distinguishes the method from more conventional hyper-reduction techniques, is that the E3C integration points are not taken from the set of FE integration points. Instead, they can be interpreted as generalized integration points in strain space which are trained such as to satisfy an orthogonality condition, which ensures that the hyper-reduced model matches the equilibrium states and macroscopic stresses of full-field model data as accurately as possible. In addition, the number of grains is reduced, preserving the main features of the original texture of the finite element model. Two macroscopic engineering parts (untextured and textured) are simulated, illustrating the performance of the method in three-dimensional two-scale applications involving hundreds of thousands macroscopic degrees of freedom and millions of grains with computing times in the order of hours (cumulated online and offline effort) on standard laptop hardware.

physics.comp-ph↗

arXiv2025

Computational Homogenization in 3D Magnetostatics using E3C Hyper-Reduction

The recently published hyper-reduction method "Empirically Corrected Cluster Cubature" (E3C) is for the first time applied in three dimensions (here magnetostatics). The method is verified to give accurate results even for a small number of integration points, such as 15 for 3D microstructure simulations. The influence of the number of snapshots and modes, as well as the number of integration points, is investigated and the set with the best performance is selected, showing hyper-reduction errors of less than 1%. Exemplary simulations, including a two-scale simulation are considered illustrating the performance of the E3C method for 3D simulations.

physics.comp-ph↗

arXiv2025

E3C for Computational Homogenization in Nonlinear Mechanics

In computational homogenization, a fast solution of the microscopic problem can be achieved by model order reduction in combination with hyper-reduction. Such a technique, which has recently been proposed in the context of magnetostatics, is applied to nonlinear mechanics in this work. The method is called 'Empirically Corrected Cluster Cubature' (E3C), as it combines clustering techniques with an empirical correction step to compute a novel type of integration points, which does not form a subset of the finite element integration points. The method is adopted to the challenges arising in nonlinear mechanics and is tested in plane strain for different microstructures (porous and reinforced) in dependence of the material nonlinearity. The results show that hyper-reduction errors < 1% can be achieved with a comparably small number of integration points, which is in the order of the number of modes. A two-scale example is provided and the research code can be downloaded.

physics.comp-ph↗