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Effect of Pearlite Structure on the Mechanical Properties of Microalloyed Hypereutectoid Steels

2005· article· en· W2001909362 on OpenAlexafffund
A.M. Elwazri, Steve Yue

Bibliographic record

VenueMaterials science forum · 2005
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCementitePearliteMaterials scienceMetallurgyVanadiumMicrostructureGrain boundaryMicroalloyed steelLedeburiteAusteniteNucleationSiliconPrecipitationThermodynamics

Abstract

fetched live from OpenAlex

The relationship between mechanical properties and pearlite microstructure was investigated using various heat treatments on a hypereutectoid steels containing 1% carbon with different levels of vanadium and silicon. Specimens were heat treated at various temperatures ranging from 900 to 1200°C and transferred to salt bath conditions at 550, 580 and 620°C to examine the structural evolution of pearlite. The results show that the thickness of the cementite network increases with increasing reheat temperature. This is likely due to the larger austenite grain size reducing the grain boundary area available for proeutectoid cementite nucleation. It was found that the vanadium and silicon additions increased the strength of hypereutectoid steels through refinement of the microstructure and precipitation strengthening.

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 score0.002
Threshold uncertainty score0.275

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 head0.007
GPT teacher head0.194
Teacher spread0.188 · 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

Citations2
Published2005
Admission routes2
Has abstractyes

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