Effect of microcracking on electric-field-induced stress intensity factors in dielectric ceramics
Bibliographic record
Abstract
This paper gives a quantitative analysis of the effect of near-tip microcracks on electric-field-induced stress intensity factors in isotropic elastic dielectrics. Nucleation of the microcracks is assumed to be governed by the electric-field-induced mean stress or the maximum normal stress. Based on the solutions for the effect of a single microcrack on the local electric field at the main crack, simple formulae are derived for the electric-field-induced stress intensity factors in the presence of the microcracks. It is found that the relative change in the stress intensity factor due to the microcracks for a conducting crack is equal and opposite to that for an insulating crack provided that the distribution of microcrack orientations is random. In particular, the microcracking zone is found to amplify the electric-field-induced stress intensity factor in some cases, especially for stationary insulating cracks, while the microcracking zone wake has an antishielding effect for sufficiently grown conducting cracks. These results are in sharp contrast with the well-known toughening effects of microcracks in elastic media under pure mechanical loads. This is attributed to the fact that the interaction between the microcracks and the main crack in elastic dielectrics under electrical loading is governed essentially by electrostatics, while the shape of the microcracking zone is determined by the electric field induced elastic stress field.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".