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 multiple aerospace-grade aluminium alloys, specimen geometries, material orientations, and load configurations, providing a diverse experimental basis for data-driven fracture mechanics research. Crack tip locations are consistently annotated using an iterative correction procedure applied to all measurements, and fracture mechanical descriptors like stress-intensity factors are provided as additional labels. The dataset comprises 8,794 unique experimentally observed displacement fields and a total of 70,352 supervised samples generated through standardized interpolation and augmentation. DIC data is provided as uniformly interpolated displacement grids at three standardized resolutions 28 x 28, 64 x 64, and 128 x 128 pixels, each available in three dataset sizes to support scalable use cases ranging from educational applications to high-capacity model development. Accompanying metadata and a Python interface facilitate filtering, loading, and integration into reproducible machine learning and fracture mechanics workflows.
@article{arxiv.2602.10930,
title = {Annotated digital image correlation displacement fields from fatigue crack growth experiments},
author = {David Melching and Ferdinand Dömling and Florian Paysan and Erik Schultheis and Eric Dietrich and Eric Breitbarth},
journal= {arXiv preprint arXiv:2602.10930},
year = {2026}
}