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Record W2156102381 · doi:10.1177/1081286514534871

The effect of surface stress on an interface crack in linearly elastic materials

2014· article· en· W2156102381 on OpenAlexafffund
Taisiya Sigaeva, Peter Schiavone

Bibliographic record

VenueMathematics and Mechanics of Solids · 2014
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSingularityElasticity (physics)Materials scienceCrack tip opening displacementStress fieldLinear elasticityDisplacement fieldComposite materialDisplacement (psychology)Plane (geometry)Stress intensity factorFissureCrack closureStress (linguistics)MechanicsStructural engineeringFracture mechanicsMathematical analysisGeometryMathematicsPhysicsFinite element methodEngineering

Abstract

fetched live from OpenAlex

We consider an interface crack whose crack faces are coated with a thin reinforcing film of separate elastic material. We obtain asymptotic solutions, which, in the case of plane elasticity, demonstrate that the addition of the thin film effectively eliminates the well-known oscillatory behavior of the displacement and stress fields in the vicinity of the crack tip leading to a strong square-root stress singularity. In the case of anti-plane elasticity, the effect of the reinforcement is to reduce the order of the stress singularity at the crack tip. In addition, we demonstrate that the reinforcement induces a displacement field which is smooth locally and bounded 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 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.008
GPT teacher head0.258
Teacher spread0.250 · 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 designSimulation or modeling
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

Citations16
Published2014
Admission routes2
Has abstractyes

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