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compression-dilatometer-analysis-ZrNb: a python script for analysing Zr-2.5Nb compression dilatometer data

Authors: Daniel, Christopher Stuart; Peyton, Christian J.; Quinta da Fonseca, João;

compression-dilatometer-analysis-ZrNb: a python script for analysing Zr-2.5Nb compression dilatometer data

Abstract

A python script for analysing compression dilatometer data, allowing the user to plot the stress-strain data and for generating 'processing maps' of a material. The script was used to analyse data recorded in uniaxial 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 and 1 s-1, to 50% height reduction, using TA Instruments DIL 805 A/D/T Quenching and Deformation Dilatometer. The data for this experiment can be downloaded from; Daniel, Christopher Stuart, Peyton, Christian J., & Quinta da Fonseca, João. (2019). High Temperature Compression Studies of a Zr-2.5Nb Alloy using Deformation Dilatometer [Data set]. Zenodo. 10.5281/zenodo.3374512 A critical assessment of the application of 'processing maps' is included in the accompanying paper; C. S. Daniel, P. Jedrasiak, C. J. Peyton, J. Quinta da Fonseca, H. R. Shercliff, L. Bradley, and P. D.Honniball, “Quantifying Processing Map Uncertainties by Modeling the Hot-Compression Behavior of a Zr-2.5Nb Alloy,” in Zirconium in the Nuclear Industry: 19th International Symposium, ed. A. T. Motta and S. K. Yagnik (West Conshohocken, PA: ASTM International, 2021), 93–122. 10.1520/STP162220190031

Related Organizations
Keywords

processing maps, zirconium, alpha beta processing, compression testing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average