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Mechanical testing dataset of cast copper alloys for the purpose of digitalization.
Nasrabadi, Hossein Beygi; Bauer, Felix; Uhlemann, Patrick; Thärig, Steffen; Rehmer, Birgit; Skrotzki, Birgit.
Afiliación
  • Nasrabadi HB; Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany.
  • Bauer F; fem Research Institute (fem), Schwäbisch Gmünd, Germany.
  • Uhlemann P; Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany.
  • Thärig S; Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany.
  • Rehmer B; Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany.
  • Skrotzki B; Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin, Germany.
Data Brief ; 55: 110687, 2024 Aug.
Article en En | MEDLINE | ID: mdl-39049974
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.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Data Brief Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Data Brief Año: 2024 Tipo del documento: Article