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The Effect of Loading History on Unstable Fracture of Austenitic Steel (304)

2012· article· en· W2012407542 on OpenAlexafffund
K. Jendoubi, Nesar Merah, Marie Bernard, Abdelaziz Bazoune

Bibliographic record

VenueAdvanced materials research · 2012
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsPolytechnique Montréal
FundersKing Fahd University of Petroleum and MineralsPolytechnique Montréal
KeywordsMaterials scienceConstant (computer programming)AusteniteFracture mechanicsFracture (geology)Strain energy release rateStress intensity factorStructural engineeringCrack closureSingularityComposite materialRange (aeronautics)Crack growth resistance curveMechanicsMathematicsMathematical analysisEngineeringPhysicsMicrostructureComputer science

Abstract

fetched live from OpenAlex

The present paper presents an analysis of the influence of loading history on unstable fracture of austenitic steel 304 (SS 304) using the J-integral and its applicability in situations where a loading history exists. A CT specimen is employed for the purpose. The loading history effect on the unstable fracture of SS 304 is studied by performing cyclic loading with different load histories at constant load range (ΔP i ) and at constant stress intensity factor range (ΔK j ). The results show that the plastic singularity is well described by the integral (J) for the different types of loadings used. Moreover, the real meaning of (J IC ) as a representative of the maximum energy release rate is quite limited if it ignores the loading history. The experimental results show that the dissipated energy ΔJ is more active when the loading is done at constant ΔP. The evolution of ΔJ can be directly linked to the crack growth rate and to the extent of the plastic zone developed at the crack tip.

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 score0.036
Threshold uncertainty score0.346

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 head0.303
Teacher spread0.276 · 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".

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Citations0
Published2012
Admission routes2
Has abstractyes

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