activity
20202026
most citedMacroscale fracture surface segmentation via semi-supervised learning considering the structural similarity

21 citations · 21 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CE2026

A Variational Kolosov--Muskhelishvili Network for Elasticity and Fracture

Shuwei Zhou, Christian Häffner, Sophie Stebner +3

Physics-informed neural networks provide a mesh-free framework for solving partial differential equation-governed problems in solid mechanics. However, most existing formulations i…

cs.CE2025

On the impact of geometric variance on the performance of formed parts: A probabilistic approach on the example of airbag pressure bins

Lukas Schnelle, Niklas Fehlemann, Ali O. M. Kilicsoy +6

Scatter in properties resulting from manufacturing is a great challenge in lightweight design, requiring consideration of not only the average mechanical performance but also the v…

cs.LG2024★ 21 cited

Macroscale fracture surface segmentation via semi-supervised learning considering the structural similarity

Johannes Rosenberger, Johannes Tlatlik, Sebastian Münstermann

To this date the safety assessment of materials, used for example in the nuclear power sector, commonly relies on a fracture mechanical analysis utilizing macroscopic concepts, whe…

eess.SY2023

Monitoring the evolution of dimensional accuracy and product properties in property-controlled forming processes

Sophie Charlotte Stebner, Juri Martschin, Bahman Arian +14

As recent trends in manufacturing engineering disciplines show a clear development in the sustainable as well as economically efficient design of forming processes, monitoring tech…

cond-mat.mtrl-sci2020

The differences of damage initiation and accumulation of DP steels: a numerical and experimental analysis

Felix Pütz, Fuhui Shen, Markus Könemann +1

Many studies have examined the damage behaviour of dual-phase steels already. It is a topic of high interest, since understanding the mechanisms of damage during forming processes…