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Record W6931287278 · doi:10.5281/zenodo.4632038

Dataset for: Effective structural unit analysis in hexagonal close packed alloys – reconstruction of prior beta microstructures & crystal orientation post processing analysis

2021· article· en· W6931287278 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOrientation (vector space)MicrostructurePhase (matter)Crystal (programming language)Plane (geometry)Grain boundaryPole figureCode (set theory)

Abstract

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Data for "Effective structural unit analysis in hexagonal close packed alloys – reconstruction of prior beta microstructures & crystal orientation post processing analysis" by R.Birch and T.B.Britton Ruth Birch (1),Ben Britton (1,2) 1. Department of Materials, Imperial College London 2. Now also, Department of Materials Engineering, University of British Columbia For more information please contact: ruth.birch07@imperial.ac.uk --- Reconstruction code The reconstruction code is available on GitHub: https://github.com/ExpMicroMech/ParentBOR MTEX version: 5.4 The main file to run this code is: Reconstruct_Main --- Figure data provided: Figure 1 12 unique α variants (V1-12) for a fixed β orientation of (0,30,15) showing the corresponding planes and directions between the BCC and HCP orientations via prisms and pole figures. For the prisms: shared planes between variants are indicated by the colour of the plane and shared directions between variants are indicated by the coloured + dashed directions. For the pole figures, the shared plane or direction is shown by the coloured dot, the other HCP points by the larger grey dots and the BCC orientation is shown by the smaller black dots The folder 'figure 1' contains the scripts used to create figure 1 in the paper - (to run use Combined_Figures_V2.m) Figure 5 Simulated dataset in (A) β phase (IPF-Z) and (B) α phase (IPF-Z). (C) Grain boundaries identified by type on a greyscale variant number background – red = parent grain boundary, blue = α/α grain boundary. (D) The reconstructed parent grain microstructure (IPF-Z) – where there are multiple β grain orientation options, the alternative orientations are shown in the circles overlaid on the grains. The grain numbers on (D) correspond with the previous table. The folder 'SimulatedDataset' contains the scripts to create the a simulated dataset equivalent to the one in figure 5, along with PaperSimulatedDataset.m which can be used with the reconstruction code to output the plots for figure 5. Figures 6,7,8 6: Reconstruction of an EBSD map from a β quenched Zircaloy-4 sample showing [1] Initial α microstructure (IPF-Z) [2] Pattern quality map with overlaid grain boundaries, identified by type: RED = parent grain boundaries; Blue = α-α (or BOR) grain boundaries [3] Initial reconstruction output – β phase (IPF-Z ) [4] Reprocessed parent β grains (IPF-Z) with an arrow showing the location of the grain selected for further analysis. The dashed circle indicates an interesting grain discussed below. 7: Example showing how the β orientation certainty is affected by the number unique α variants present. There are three potential β variants (shown by the coloured & linked boxes) with just α grains 1 and 2, whereas with all three grains this reduces to one orientation (β variant 6 for all grains). α grain orientations are shown by the coloured dots in the pole figures, whilst the 6 potential β orientations for each of these are shown by the black dots in the pole figures. 8: Post processing outputs for β quenched Zircaloy-4 samples [A] β orientation certainty map showing the number of potential β variants for each parent β grain [B] α variant map – all 12 variants shown [C] α variant map coloured by α variants with shared (c) planes [D] α variant map coloured by α variants with shared directions. Note: for [B]-[D] comparisons can only be made directly within the grains as it is calculated on a grain by grain basis. The folder 'PaperDataset' contains the input file 'BCWQ10min2.h5' which can be used along with the settings file 'Settings_BCWQ10min2.txt' to create the plots used for figures 6,7&8. Figures 9 & 10 9: Reconstruction of smaller region into one or two (main) parent β grains - effect with changing inflation power from 1.2 to 1.6. In this figure, the upper row shows the reconstructions as coloured using the IPF-Z colourmap, and the bottom row shows the calculated misorientation of the (as measured) α grains from the ideal α orientations determined from the parent β grain orientation. 10:(A) Comparison of the two beta grain orientations, showing the shared planes for each using solid colour (corresponding to the IPFZ map colours for each grain). (B) alpha grains for this region coloured by parent grain orientation β1, β2 or ambiguous (β1/β2). (C) manually sorted alpha grains, coloured by parent beta grain assigned (IPFZ colouring) – along with the pole figures for each parent beta grain region, with the alpha orientations the coloured dots and the beta orientations the black dots in each case. The folder Appendix_Figs contains the script Appendix_Figs.m along with splitGrain.mat. splitGrain.mat contains the cutdown EBSD map required to create figures 9 and 10 - this needs to be put through the reconstruction code with the required inflation power. The script Appendix_Figs.m can then be used to create the plots required to create the figures. An example of the other settings used is found in 'Settings_Example.txt'.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.099
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0990.092

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.169
GPT teacher head0.441
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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