The Effects of Hole Size and Eccentricity on the Reliability of Notched Laminates
Bibliographic record
Abstract
Most of the practical engineering structures contain holes and cutouts of different sizes designed as parts of basic design, as in joints and assemblies, and for maintenance purposes. It is well known that holes and cutouts cause serious problems of stress concentrations due to the geometry discontinuity. These problems are even more serious in structures made of composite materials since the materials exhibit anisotropic behavior, and the structures are more sensitive to stress concentrations due to their brittle behavior. Because of its importance, engineers want to determine the effects of stress concentration, predict the failure and strength, and develop methods to reduce these effects. The stress distribution in the notched composite laminate is very sensitive to the size of the hole and the eccentricity of the hole from its desired location. In practice, many times during manufacturing the drilled hole is slightly offset from the desired location, and further there is variability in the size of the hole. These variations have a random distribution over the ensemble of laminates. In addition, composite materials display significant variability in their mechanical properties. As a result of the above-mentioned variabilities, the stress distribution in the laminate becomes stochastic in nature. In this circumstance, it becomes appropriate that the analysis of the notched laminates be carried out based on a stochastic approach and that the design is performed based on reliability requirement.
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| 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".