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Record W2328055803 · doi:10.1107/s0108767311097984

Crystalline texture in Zr-based alloys tubes

2011· article· en· W2328055803 on OpenAlexaboutno aff
Constanza Buioli, A.D. Banchik, P. Vizcaı́no

Bibliographic record

VenueActa Crystallographica Section A Foundations of Crystallography · 2011
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceTexture (cosmology)MetallurgyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Pressure tubes are the most important Zr-base components in the core of CANDU nuclear power reactors.The most important mechanisms defining the service life of pressure tubes are: irradiationenhanced coming with deformation, and the delayed hydride cracking.Both processes are determined by a few metallurgical parameters which must be exhaustively controlled: microstructure, dislocation density and texture [1], [2].Argentina has one CANDU power plant in operation since 1982 (CNE), which is now close to ending its service life.A refurbishment project is underway which will include the replacement of existing fuel channels, composed by Zr-2.5%Nb pressure tubes and Zircaloy2/4 calandria tubes.CNEA is developing a new manufacturing route for Zr-2.5%Nbpressure tubes, using a cold rolling pilger type machine instead of the cold drawing process currently performed in Canada.The new process will be performed at the Planta Piloto de fabricación de aleaciones especiales (PPFAE,CNEA).The extrusion stage produces a strong texture (crystalline preferential orientation) in the material.In this framework, in our laboratory (LMFAE), we calculate the texture factors [3], [4] from x-ray diffraction diagrams obtained from a Bruker D8 FOCUS diffractometer.A qualitative study of the texture was performed using the rocking curve method [5] (figure 1).The collected data was used to build a qualitative direct pole figure.The quantitative study was made through the calculation of Kearns factors (table 1), measuring in the θ/2θ standard way (Bragg-Brentano geometry).The results obtained from the rocking curves were quite satisfactory and they are compatible with the expected texture for the (0002) pole.This pole is essentially oriented in the transverse direction (90%), with small contributions in the radial (8%) and axial directions (2%).The Kearns factors are also in agreement with the these fractions, fulfilling the specified values (0.03≤f axial ≤0.09, 0.27≤f radial ≤0.39, 0.55≤f transversal ≤0.67, and 0.95≤∑f≤1.05[6]) within a dispersion of ±0.02.Table 1.Average Kearns factors of the Zr-2.5%Nbpressure tube.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.234
Teacher spread0.209 · 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 designObservational
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

Citations0
Published2011
Admission routes1
Has abstractyes

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