https://fordatis.fraunhofer.de/handle/fordatis/14 Sat, 17 Oct 2026 09:05:41 GMT 2026-10-17T09:05:41Z https://fordatis.fraunhofer.de/handle/fordatis/519 Titel: Raw Data: Time-resolved Study of CF/PPS and CF/Epoxy Ageing Under Hygrothermal and Irradiative Conditions Datenautorinnen und Datenautoren: Seidel, Sebastian; Rohrmüller, Benedikt; Beckmann, Carla; Findeisen, Claudio; Hohe, Jörg Zusammenfassung: Raw Tensile Test Data for pristine and aged CFRP specimen. Unidirectionally CF reinforced PPS as well as Epoxy/CF Specimen in 0°, 75° as well as 0° were exposed to the combined effects of humidity/temperature (50°C/50%; 80°C/0%; 80°C/50%; 80°C/100%) to dry UV-irradiation, UV wheathering and High-Pressure Hydrogen for 4, 8 and 12 weeks prior to testing. Thu, 01 Oct 2026 00:00:00 GMT https://fordatis.fraunhofer.de/handle/fordatis/519 2026-10-01T00:00:00Z https://fordatis.fraunhofer.de/handle/fordatis/478 Titel: AmalgaMatch: A Correlative Microscopy Dataset for Multimodal Data Fusion and Image Matching in Materials Science Datenautorinnen und Datenautoren: Durmaz, Ali Riza Zusammenfassung: Gaining understanding of process-structure-property relationships in materials at a mechanistic level relies on correlative microscopy workflows. These workflows, in turn, fundamentally depend on image matching, i.e., a computer vision task with the objective of finding point correspondences in pairs of images. Matching models are difficult to evaluate quantitatively in the materials field due to a shortage of representative benchmark datasets. Nonetheless, a few small-scale studies indicate that traditional rule-based image matching techniques such as surface-invariant feature transform currently fall short on such matching tasks. We present a dataset for cross-modal image matching and data fusion in the materials microscopy domain, which we coin AmalgaMatch, to support model benchmarking and fine-tuning efforts. All images are micrographs captured using the most widely applied imaging techniques in materials science including light-optical, scanning electron, and transmission electron microscopy, as well as electron backscatter diffraction. Therein, various detectors and imaging modes are employed to capture micrographs of diverse materials. While the majority of images are raw images, some underwent typical processing routes using digital image correlation or EBSD indexing. Common regions in image pairs are populated with hand-annotated keypoint correspondences. While mutual information is limited in cross-modal, multi-scale image pairs, we relied on characteristic defects such as dislocations, grain boundaries, triple junctions, inclusions, pores or surface features for annotation. Furthermore, the dataset is divided into groups and subsets with distinct registration tasks, materials, and/or, imaging configurations representing splitting criteria. The dataset covers many typical use cases for image matching in materials science. In total, it comprises 19 subsets with 35 scenes and 187 annotated image pairs to support autonomous multi-modal materials data fusion. For each image, we provide metadata to facilitate training of hybrid matching models which process textual alongside image-based inputs to improve the matching quality and robustness. Sun, 01 Feb 2026 00:00:00 GMT https://fordatis.fraunhofer.de/handle/fordatis/478 2026-02-01T00:00:00Z https://fordatis.fraunhofer.de/handle/fordatis/443 Titel: Daten zur Dämpfung im Stahl-Aluminium-Kontakt unter vibrierender Belastung für die Nutzung in einer Heckklappe Datenautorinnen und Datenautoren: Kugler, Marion; Koschnik, Frank; Marx, David Sebastian; Weber, Dennis; Dienwiebel, Martin Zusammenfassung: The information on how the data was obtained is explained in the Paper "Potential of friction to damp vibrations in the use case of a car tailgate" by Marion Kugler, Frank Koschnick, David Marx, Dennis Weber, Martin Dienwiebel. Wed, 28 May 2025 00:00:00 GMT https://fordatis.fraunhofer.de/handle/fordatis/443 2025-05-28T00:00:00Z https://fordatis.fraunhofer.de/handle/fordatis/442 Titel: Discrete element simulation datasets of particle flow in representative unit cells Datenautorinnen und Datenautoren: Morand, Lukas; Bierwisch, Claas; Setty, Abhishek Zusammenfassung: This publication contains two datasets of particle flow within representative unit cells, generated using the simulation software SimPARTIX (https://www.simpartix.com/). The datasets are used for evaluating a graph-based interaction-aware particle trajectory prediction model, as detailed in the paper available at https://arxiv.org/pdf/2503.00215. The first dataset, "raw_data_simple_periodic_BC.tgz", includes a unit cell calculation with simple periodic boundary conditions and a sinusoidal velocity profile. The second dataset, "raw_data_Lees-Edwards_BC.tgz", includes a unit cell calculation utilizing Lees-Edwards boundary conditions. Wed, 01 Jan 2025 00:00:00 GMT https://fordatis.fraunhofer.de/handle/fordatis/442 2025-01-01T00:00:00Z