Substrate Creep on The Fatigue Life of A Model Dental Multilayer Structure
Bibliographic record
Abstract
In this paper, we investigated the effects of substrate creep on the fatigue behavior of a model dental multilayer structure, in which a top glass layer was bonded to a polycarbonate substrate through a dental adhesive. The top glass layers were ground using 120 grit or 600 grit sand papers before bonding to create different sub-surface crack sizes and morphologies. The multilayer structures were tested under cyclic Hertzian contact loading to study crack growth and obtain fatigue life curves. The experiment results showed that the fatigue lives of the multilayer structures were impaired by increasing crack sizes in the sub-surfaces. They were also significantly reduced by the substrate creep when tested at relatively low load levels i.e. P{sub m} < 60 N (Pm is the maximum magnitude of cyclic load). But at relatively high load levels i.e. P{sub m} > 65 N, slow crack growth (SCG) was the major failure mechanisms. A modeling study was then carried out to explore the possible failure mechanisms over a range of load levels. It is found that fatigue life at relatively low load levels can be better estimated by considering the substrate creep effect (SCE).
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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 | 0.001 |
| 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 | 0.000 | 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".