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Effect of Interactive Periods to Corrosion-Fatigue Life on LY12CZ Alloy

2011· article· en· W2049792971 on OpenAlexfundno aff
Hai Wei Zhang, Yu He, Chao Liu, Li Ming Wu, Hua Ding

Bibliographic record

VenueApplied Mechanics and Materials · 2011
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsnot available
FundersNational Research Council CanadaNational Natural Science Foundation of China
KeywordsCorrosion fatigueCorrosionStructural engineeringMaterials scienceAluminium alloyTest (biology)AluminiumAlloyMetallurgyEngineering

Abstract

fetched live from OpenAlex

To study life differences between pre-corrosion fatigue and corrosion-fatigue test, LY12CZ standard specimens are selected in pre-corrosion fatigue test to get the C(t) curve at first. Then, combining with Miner linear cumulative damage theory, theoretical fatigue life is calculated by simulated corrosion-fatigue interactive process. Compared with actual corrosion-fatigue interactive test, theoretical life is rather conservative. Afterwards, a modified model based on C(t) curve method and actual interactive test at different periods of specific flight strength is established. The result shows that the modified C(t) curve method is in good agreement with corrosion-fatigue interactive test.

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)0.000
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 score0.094
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.013
GPT teacher head0.222
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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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