10 citations · 16 across the 10 of their papers we have counts for
10 papers
QUBO-Compatible Active Learning for Inverse Design of High-Entropy Alloys
Giorgio Silvi, Kirsten Bark, Rolando Reiner +5
Machine-learned forward models can rapidly predict alloy properties, but their use for inverse design remains challenging when the search should also retain compatibility with quad…
Data-driven multi-objective optimization for alloy recycling using factorization machines and quantum annealing
Thomas Plehn, Katrin Bugelnig, Silvana Tumminello +2
Quantum annealing has the potential to provide practical quantum advantage for complex optimization tasks. Here, we present a systematic assessment of an integrated factorization-m…
Annotated digital image correlation displacement fields from fatigue crack growth experiments
David Melching, Ferdinand Dömling, Florian Paysan +3
We present a curated dataset of planar displacement fields from eight fatigue crack growth experiments obtained via full-field digital image correlation (DIC). The dataset covers m…
Progress on Data-Driven, Multi-Objective Quantum Optimization
Thomas Plehn, Daniel Barragan-Yani, Eric Breitbarth +2
Here, we present two complementary approaches that advance quadratic unconstrained binary optimization (QUBO) toward practical use in data-driven materials design and other real-va…
Trustworthy AI-based crack-tip segmentation using domain-guided explanations
Jesco Talies, Eric Breitbarth, David Melching
Ensuring the trustworthiness and robustness of deep learning models remains a fundamental challenge, particularly in high-stakes scientific applications. In this study, we present…
Advanced crack tip stress analysis using interaction integrals in high-resolution digital image correlation fields
Florian Paysan, David Melching, Eric Breitbarth
The link between microscopic mechanisms and macroscopic behaviour, represented by the curve, plays an increasingly important role in relating the fatigue crack growth cu…
Plasticity-induced crack closure identification during fatigue crack growth in AA2024-T3 by using high-resolution digital image correlation
Florian Paysan, David Melching, Eric Breibarth
Fatigue crack growth in ductile materials is primarily driven by the interaction between damaging and shielding mechanisms. In the Paris regime, the predominant mechanism for retar…
A universal crack tip correction algorithm discovered by physical deep symbolic regression
David Melching, Florian Paysan, Tobias Strohmann +1
Digital image correlation is a widely used technique in the field of experimental mechanics. In fracture mechanics, determining the precise location of the crack tip is crucial. In…
Generating artificial digital image correlation data using physics-guided adversarial networks
David Melching, Erik Schultheis, Eric Breitbarth
Digital image correlation (DIC) has become a valuable tool to monitor and evaluate mechanical experiments of cracked specimen, but the automatic detection of cracks is often diffic…
Advanced crack tip field characterization using conjugate work integrals
David Melching, Eric Breitbarth
The quantitative characterisation of crack tip loads is fundamental in fracture mechanics. Although the potential influence of higher order terms on crack growth and stability is k…