TY - GEN A1 - Schilling, Markus A1 - Skrotzki, Birgit T1 - Full dataset of several mechanical tests on an S355 steel sheet as reference data for digital representations N2 - The dataset provided in this repository comprises data obtained from a series of characterization tests performed to a sheet of typical S355 (material number: 1.0577) structural steel (designation of steel according to DIN EN 10025-2:2019). The tests include methods for the determination of mechanical properties such as, e.g., tensile test, Charpy test and sonic resonance test. This dataset is intended to be extended by the inclusion of data obtained from further test methods. Therefore, the entire dataset (concept DOI) comprises several parts (versions), each of which is addressed by a unique version DOI. The data were generated in the frame of the digitization project Innovationplatform MaterialDigital (PMD) which, amongst other activities, aims to store data in a semantically and machine understandable way. Therefore, data structuring and data formats are focused in addition to aspects in the field of material science and engineering (MSE). Hence, this data is supposed to provide reference data as basis for experimental data inclusion, conversion and structuring (data management and processing) that leads to semantical expressivity as well as for MSE experts being generally interested in the material properties and knowledge. KW - S355 steel sheet KW - Mechanical testing KW - Tensile test KW - Charpy test KW - Microstructure analysis KW - Digital representation KW - Data management KW - Data format PY - 2022 DO - https://doi.org/10.5281/zenodo.6778336 PB - Zenodo CY - Geneva AN - OPUS4-55141 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Skrotzki, Birgit T1 - Improving the Reproducibility of Characterization and Quantification of Precipitates through Automated Image Processing and Digital Representation of Processing Steps N2 - The strength of age-hardenable aluminum alloys is based on the controlled formation of nm-sized precipitates, which represent obstacles to dislocation movement. Transmission electron microscopy (TEM) is generally used to identify precipitate types and orientations and to determine their size. This geometric quantification (e.g., length, diameter) is often performed by manual image analysis, which is very time consuming and sometimes poses reproducibility problems. The present work aims at the digital representation of this characterization method by proposing an automatable digital approach. Based on DF-TEM images of different precipitation states of alloy EN AW-2618A, a modularizable digital workflow is described for the quantitative analysis of precipitate dimensions. The integration of this workflow into a data pipeline concept is also presented. The semantic structuring of data allows data to be shared and reused for other applications and purposes, which enables interoperability. T2 - ICAA19 International Conference on Aluminum Alloys CY - Atlanta, GA, USA DA - 23.06.2024 KW - Digital representation KW - Automatable digital approach KW - Digital workflow KW - Quantitative image analysis KW - Data pipeline concept KW - Semantic structuring KW - Interoperability KW - FAIR data management PY - 2024 AN - OPUS4-60427 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -