# Mechanical testing dataset of cast copper alloys for the purpose of digitalization

**Authors:** Hossein Beygi Nasrabadi, Felix Bauer, Patrick Uhlemann, Steffen Thärig, Birgit Rehmer, Birgit Skrotzki

PMC · DOI: 10.1016/j.dib.2024.110687 · 2024-06-26

## TL;DR

This paper provides a digitalized dataset of mechanical tests on nine copper alloys to support materials research and selection.

## Contribution

The novel contribution is the digitalization of primary and secondary mechanical testing data using semantic descriptions for open-linked data.

## Key findings

- Primary datasets include raw mechanical test data and metadata for nine copper alloys.
- Secondary datasets summarize key mechanical properties like hardness, strength, and fatigue life.
- Digitalized data enable semantic querying for advanced materials research.

## Abstract

This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled “Toward a digital materials mechanical testing lab” [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11268113/full.md

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Source: https://tomesphere.com/paper/PMC11268113