2 citations · 2 across the 2 of their papers we have counts for
5 papers
Machine Learning Inference Limits of Routine Cement Characterization for CEM I Performance: Evidence From a Multi-Producer Dataset
Marchellino Ghorayeb, Christiane Rößler, Horst-Michael Ludwig +2
Routine cement performance characterization provides continuous quality control data, but its information content for performance inference and transferability across independent p…
Lightweight return-mapping surrogates for multiscale plasticity: a practical guide
Alireza Daneshyar, Leon Herrmann, Stefan Kollmannsberger
This paper presents a practical guide to building lightweight neural-network surrogates for the plastic return-mapping process in concurrent multiscale (FE2) simulations. Rather th…
A Memory Efficient Adjoint Method to Enable Billion Parameter Optimization on a Single GPU in Dynamic Problems
Leon Herrmann, Tim Bürchner, László Kudela +1
Dynamic optimization is currently limited by sensitivity computations that require information from full forward and adjoint wave fields. Since the forward and adjoint solutions ar…
Accelerating Full Waveform Inversion By Transfer Learning
Divya Shyam Singh, Leon Herrmann, Qing Sun +3
Full waveform inversion (FWI) is a powerful tool for reconstructing material fields based on sparsely measured data obtained by wave propagation. For specific problems, discretizin…
Neural Networks for Generating Better Local Optima in Topology Optimization
Leon Herrmann, Ole Sigmund, Viola Muning Li +2
Neural networks have recently been employed as material discretizations within adjoint optimization frameworks for inverse problems and topology optimization. While advantageous re…