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Record W1979090354 · doi:10.1115/omae2002-28220

On the Analysis of Crack Interactions Using Weight Function Method

2002· article· en· W1979090354 on OpenAlexafffund
Vaijayanthi Rangasamy, Xin Wang, Robert A. Bell

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWeight functionMaterials scienceStress intensity factorStress (linguistics)Structural engineeringRange (aeronautics)Function (biology)Composite materialStress concentrationMechanicsFracture mechanicsMathematical analysisMathematicsEngineeringPhysics

Abstract

fetched live from OpenAlex

A method for the analysis of interaction effect on stress intensity factors of two coplanar cracks using weight function method is presented. It provides more insight and understanding of the interaction behavior of cracks. It is demonstrated that the existence of the second crack will affect the first crack on both weight function and uncracked stress distribution. Application of the weight function method to analyze two coplanar through cracks and two coplanar semi-circular surface cracks are conducted. It is shown that for a wide range of distances between neighboring cracks, most of the interaction effect comes from the contribution of the uncracked stress distribution. Therefore, for engineering applications, the interaction effect can be accounted for from the uncracked stress distribution accurately. This provides a simplified method for the crack interaction analysis.

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)0.001
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.259
Teacher spread0.220 · 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

Citations0
Published2002
Admission routes2
Has abstractyes

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