Evolution of Crack Propagation Rate in Notched Specimens Using XFEM Method under Bending Load Condition
Bibliographic record
Abstract
The crack initiation and propagation often occur in structures subjected to fatigue loads and their privileged sites it is the geometric discontinuity in particular the notches. The geometric configuration of the notches always leads to disturbances of stress fields in the vicinity of the notch end as a consequence of the effects on the crack initiation site and on the crack rate. The present study is interested to the evolution of crack speed propagation in the notched specimens subjected to bending. The specimens chosen are made of PMMA material containing two opposite notches U or V that presented two different parameters, a radius for U-notch and angle for V-notch. The variations taken into account for the sharp notches (V-notch) going from the small angle to the large angle, which are 30°; 45°, 90°, and 140°, and for blunt notches (U-notch) the radius takes the different values 0.5, 1, 1.5, and 2 mm. The fracture brittle behavior adapted to this material led to predict the Fatigue crack growth using a modified form of Paris’s law with the equivalent stress intensity factor (ΔKeq) relying on extended finite element method (XFEM) in order to follow the interaction between the notch and the crack on one side and study the evolution of crack growth rate to another side. The variations, which brought to these parameters entailed an influence on the crack propagation speed, which was born at the end of notch of component as well as the variations of equivalent notch intensity stress factors (ΔKeq). The variations made to the parameters of notches have a huge influence on the crack propagation rate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".