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Record W2801397044 · doi:10.1155/2018/5894356

Hole Defects Affect the Dynamic Fracture Behavior of Nearby Running Cracks

2018· article· en· W2801397044 on OpenAlexaff
Renshu Yang, Chenxi Ding, Liyun Yang, Peng Xu, C. L. Philip Chen

Bibliographic record

VenueShock and Vibration · 2018
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsGeomechanica (Canada)
FundersNational Natural Science Foundation of China
KeywordsDeflection (physics)Materials scienceFracture mechanicsStructural engineeringStress intensity factorDynamic stressStress concentrationDynamic loadingComposite materialOpticsEngineeringPhysics

Abstract

fetched live from OpenAlex

Effects of defects on the dynamic fracture behavior of engineering materials cannot be neglected. Using the experimental system of digital laser dynamic caustics, the effects of defects on the dynamic fracture behavior of nearby running cracks are studied. When running cracks propagate near to defects, the crack path deflects toward the defect; the degree of deflection is greater for larger defect diameters. When the running crack propagates away from the defect, the degree of deflection gradually reduces and the original crack path is restored. The intersection between the caustic spot and the defect is the direct cause of the running crack deflection; the intersection area determines the degree of deflection. In addition, the defect locally inhibits the dynamic stress intensity factor of running cracks when they propagate toward the defect and locally promotes the dynamic stress intensity factor of running cracks when they propagate away from the defect.

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.285
Teacher spread0.266 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

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