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Record W4280606876 · doi:10.1115/1.4054557

Joining of Zirconium Alloys to Nickel Bearing Alloys for In-Core Components

2022· article· en· W4280606876 on OpenAlexaffabout
M. Gaudet, Anne McLellan, A.P. Gerlich, Bruce W. Williams

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsNatural Resources CanadaUniversity of WaterlooCanadian Nuclear Laboratories
Fundersnot available
KeywordsMaterials scienceMetallurgyZirconiumZirconium alloyWeldingDuctility (Earth science)IntermetallicAlloyUltimate tensile strengthComposite materialCreep

Abstract

fetched live from OpenAlex

Abstract Zirconium alloys are well-positioned as the material of choice for nuclear in-core structures since they have a low neutron absorption cross section and possess good material properties under elevated neutron flux and high-temperature operating conditions. The Canadian supercritical water-cooled reactor (SCWR) concept pressure tube includes a transition from zirconium-tin alloy (Excel) to a yet to be selected stainless steel to allow it to be seal welded to the inlet plenum. Thus, a method to join zirconium and its alloys to ferrous and nickel-bearing alloys is desired. To this end, a series of experiments were carried out to demonstrate the feasibility of this method. A joint approaching the strength of the parent material was achieved using both rotary friction welding and co-extrusion methods, although the joints exhibited lower ductility than that of the parent material. Microstructural examination of the joint revealed a ∼200 nm to ∼1 μm intermetallic layer at the transition zone, which was the location of failure in the tensile specimen.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.230

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)0.0000.000

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes2
Has abstractyes

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