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Record W2155018816 · doi:10.3139/147.110304

Typical Zirconium Alloys Microstructures in Nuclear Components

2014· article· en· W2155018816 on OpenAlexaboutno aff
A. V. Flores, A. Gomez, G. A. Juarez, Nuria Carballo Loureiro, R. I. Samper, J.R. Santisteban, M.A. Vicente Álvarez, A. Tolley, A.M. Condó, Roberto Bianchi, A.D. Banchik, P. Vizcaı́no

Bibliographic record

VenuePractical Metallography · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMicrostructureMaterials scienceZirconium alloyZirconiumScanning electron microscopeTransmission electron microscopyOptical microscopePhase (matter)MetallurgyComposite materialNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Abstract The different microstructures typically found in nuclear components made of zirconium alloys are discussed in this paper. These include material in a variety of thermo-mechanical conditions, e. g., cold rolled, stress relieved, recrystallized, welded, biphasic, together with minority second phases belonging to the original material or incorporated due to in-service conditions. The anisotropic crystalline structure of zirconium is exploited in microscopical observations by means of polarizer filters that enhance the contrast between different grains, and greatly aid the identification in most microstructures. Most microstructural variations across a wide range of length-scales, such as those produced by welding processes, can be effectively resolved by traditional optical microscopy (OM). However, some finer microstructures like those found in CANDU 1 (CANada Deuterium Uranium) reactor pressure tube material, or some minority second phase particles like the Zr(Fe, Cr) 2 precipitates in Zircaloy-4 cannot be completely resolved by this technique. Thus, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) are required in such cases. For SEM observations we show the valuable issue of the scale in specific microstructural studies, which allows quantifying microstructural parameters using image analysis. For TEM observations, we have greatly benefited from the electron diffraction diagrams, which have allowed us to investigate the crystalline structure of irradiated second phase particles, which would remain unnoticed to both, OM or SEM observations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.258
Teacher spread0.235 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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