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High Temperature Compression Studies of a Zr-2.5Nb Alloy using Deformation Dilatometer

<p>Data recorded in uniaxial&nbsp;compression for a Zr-2.5Nb alloy deformed at temperatures of 650C, 675C, 700C, 725C, 750C, 775C, 800C, 825C and 850C, at strain rates of 10-2.5, 10-2, 10-1.5, 10-1, 10-0.5&nbsp;and 1 s-1, to 50% height reduction, using TA Instruments DIL 805 A/D/T Quenching and Deformation&nbsp;Dilatometer. The cylindrical samples measured 5 mm diameter and 10 mm height. The Zr-2.5Nb specimens were machined from the centre of an as-received&nbsp;forged plate&nbsp;manufactured at&nbsp;Wah Chang, with a beta-transformed starting microstructure.&nbsp;Si3N43 platens were used for all tests, with graphite lubricant applied at the ends of the sample to minimise friction.&nbsp;Tests were conducted&nbsp;in an inert He gas atmosphere.&nbsp;Temperature was controlled using an S-Type thermocouple spot-welded to the centre of the samples.</p> <p>Data recorded at high acquisition frequency&nbsp;during deformation is&nbsp;stored&nbsp;in the &#39;deformation_files&#39; folder and saved with the format: &#39; test&nbsp;number (001 to 191)_temperature_log(strain rate)_repeat number (01 or 02)&#39;.&nbsp;&nbsp;Data in the &#39;basic_files&#39; folder is recorded at a&nbsp;lower acquisition&nbsp;frequency, but&nbsp;includes recording of the entire themomechanical cycle, including&nbsp;both heating and cooling stages, as well as deformation.&nbsp;The &#39;software_files&#39; folder includes&nbsp;metadata stored in the form of a parameter file (.par and .pad), along with a Windows data file (.D5D) that can be loaded and analysed within the&nbsp;dilatometer user interface.</p> <p>An <a href="https://doi.org/10.5281/zenodo.3673105">accompanying python script</a>&nbsp;will allow the user to plot the stress-strain&nbsp;data&nbsp;using the&nbsp;Jupyter Notebook application, along with&nbsp;generating&nbsp;&#39;processing maps&#39; of&nbsp;the material. A&nbsp;critical assessment of the application of&nbsp;&#39;processing maps&#39; is included in the accompanying paper;</p> <p>C. S. Daniel, P. Jedrasiak, C. J. Peyton, J. Quinta da Fonseca, H. R. Shercliff, L. Bradley, and P. D.Honniball, &ldquo;Quantifying Processing Map Uncertainties by Modeling the Hot-Compression Behavior of a Zr-2.5Nb Alloy,&rdquo; in Zirconium in the Nuclear Industry: 19th International Symposium, ed. A. T. Motta and S. K. Yagnik (West Conshohocken, PA: ASTM International, 2021), 93&ndash;122.&nbsp;<a href="https://doi.org/10.1520/STP162220190031">10.1520/STP162220190031</a></p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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