61 citations · 64 across the 4 of their papers we have counts for
6 papers
Hybrid machine-learned homogenization: Bayesian data mining and convolutional neural networks
Julian Lißner, Felix Fritzen
Beyond the generally deployed features for microstructure property prediction this study aims to improve the machine learned prediction by developing novel feature descriptors. The…
FFT-based Homogenization at Finite Strains using Composite Boxels (ComBo)
Sanath Keshav, Felix Fritzen, Matthias Kabel
Computational homogenization is the gold standard for concurrent multi-scale simulations (e.g., FE2) in scale-bridging applications. Experimental and synthetic material microstruct…
Finite Strain Homogenization Using a Reduced Basis and Efficient Sampling
Oliver Kunc, Felix Fritzen
The computational homogenization of hyperelastic solids in the geometrically nonlinear context has yet to be treated with sufficient efficiency in order to allow for real-world app…
Data-Driven Microstructure Property Relations
Julian Lißner, Felix Fritzen
An image based prediction of the effective heat conductivity for highly heterogeneous microstructured materials is presented. The synthetic materials under consideration show diffe…
On-the-fly adaptivity for nonlinear twoscale simulations using artificial neural networks and reduced order modeling
Felix Fritzen, Mauricio Fernández, Fredrik Larsson
A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. It is based on the introduction of two different surrogate models and an adaptive on-the-fly…
An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem
Felix Fritzen, Bernhard Haasdonk, David Ryckelynck +1
A novel algorithmic discussion of the methodological and numerical differences of competing parametric model reduction techniques for nonlinear problems are presented. First, the G…