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Record W2081465993 · doi:10.1115/1.1427690

Investigating the Effect of Crack Shape on the Interaction Behavior of Noncoplanar Surface Cracks Using Finite Element Analysis

2002· article· en· W2081465993 on OpenAlexaff
Walied A. Moussa, Robert A. Bell, Chee Leong Tan

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2002
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsCarleton University
Fundersnot available
KeywordsStress intensity factorFinite element methodMaterials scienceCrack closureParametric statisticsCoalescence (physics)Structural engineeringCrack tip opening displacementTension (geology)Position (finance)Stress concentrationIsotropyFracture mechanicsMechanicsGeometryComposite materialCompression (physics)MathematicsEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

In the last two decades, multiple cracks are often found in aging aerospace and mechanical structures. The interaction and coalescence of multiple cracks may significantly affect the service lives of these aging structures. Knowledge of the behavior of interacting cracks is still limited. The calculation of the crack-tip stress intensity factor, SIF, along the interacting crack fronts is considered a major contribution for the application of any linear fracture mechanics model to investigate the growth life of these cracks. In this paper, a parametric study is presented for two parallel surface cracks in an infinite plate subjected to remote tension or to pure bending loads. This study focuses on constructing a finite element (FE) model that combines the submodeling technique with its ability to generate crack submodels of different lengths and depths, and a mesh generator that can build up a mesh grid based on the size, depth, and orientation of the interacting crack sub-models. The stress intensity factors for these cracks are calculated as a function of the crack front position, depth, shape, and plate thickness. In this paper, the values of the studied crack depth to length ratio, a/c, are 0.33, 0.5, 0.67, and 1.0. Where possible, a comparison of the 3-D with 2-D results is also considered.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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 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

Citations22
Published2002
Admission routes1
Has abstractyes

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