Full-field displacements and strains obtained by digital image correlation during fatigue crack growth experiments

<p>This data publication contains&nbsp;full-field displacements and strains&nbsp;obtained by 3D digital image correlation (DIC)&nbsp;using a GOM Aramis 12M system including&nbsp;three fatigue crack propagation (fcp)&nbsp;experiments of AA2024-T3 aluminium sheet material.</p> <p>The repository consists of three datasets of different experiments named&nbsp;</p> <ul> <li>S_{950,1.6&nbsp;}- MT950 specimen, 1.6 mm sheet thickness, load ratios R=0.3, 1.0</li> <li>S_{160,2.0&nbsp;}-&nbsp;MT160 specimen, 2.0 mm sheet thickness, load ratios R=0.1, 0.25, 0.5, 0.75, 1.0</li> <li>S_{160,4.7&nbsp;}- MT160 specimen, 4.7&nbsp;mm sheet thickness, load ratios R=0.1, 0.25, 0.5, 0.75, 1.0</li> </ul> <p>where S_w,t&nbsp;denotes a middle tension (MT) specimen with width w and thickness t. The&nbsp;nodal DIC measurements at different times during the experiments are provided&nbsp;as&nbsp;.txt files we call <em>&quot;nodemaps&quot;&nbsp;</em>and stored in&nbsp;subfolders &quot;<strong>Nodemaps</strong>&quot;. Each <em>nodemap</em> consists of a header containing meta data information like a running number (current stage index)&nbsp;or the&nbsp;applied force, followed by the nodal displacements and strains in tabular form.&nbsp;Additionally, the dataset S_160,4.7&nbsp;contains crack path and crack tip labels for each nodemap in the subfolder &quot;<strong>GroundTruth</strong>&quot;. The ground truth is provided as arrays of size 256x256. Each pixel of the array contains the label &quot;2&quot; for the class &quot;crack tip&quot;, &quot;1&quot; for the class &quot;crack path&quot;, or &quot;0&quot; for the class &quot;background&quot;.&nbsp;These labels were created in a semi-manual fashion and can be&nbsp;used for machine learned crack detection using supervised training.</p> <p>These datasets were recently&nbsp;used to evaluate neural attention of convolutional neural networks&nbsp;trained on fatigue crack tip detection&nbsp;in&nbsp;<a href="https://www.nature.com/articles/s41598-022-13275-1">Melching et al. (Sci Rep,&nbsp;2022)</a>. Additional guidance on data loading and usage can also be found at&nbsp;<a href="https://github.com/dlr-wf/explainable-crack-tip-detection">https://github.com/dlr-wf/explainable-crack-tip-detection</a>.</p> <p>The experiments S_160,2.0&nbsp;and&nbsp;S_{160,4.7&nbsp;}were conducted and analysed by <a href="https://doi.org/10.1111/ffe.13433">Strohmann et al. (FFEMS, 2021)</a>.</p> <p>The experiment&nbsp;S_950,1.6&nbsp;was conducted and analysed by&nbsp;<a href="https://doi.org/10.1111/ffe.13335">Breitbarth et al. (FFEMS, 2020)</a>.</p>