Ratcheting prediction of Al 6061/SiC <sub>P</sub> composite samples under asymmetric stress cycles by means of the Ahmadzadeh–Varvani hardening rule
Bibliographic record
Abstract
The present study intends to examine ratcheting response of SiC P particle-reinforced Al 6061 matrix (Al 6061/SiC P ) composite samples over asymmetric load cycles based on the kinematic hardening rule of Ahmadzadeh–Varvani. The Ahmadzadeh–Varvani hardening rule offered a simple framework by taking into account of both material and stress level dependent coefficients to predict the quasi-shakedown of ratcheting of composite samples with various volume fractions under single- and multi-step loading conditions. The coefficients in the Ahmadzadeh–Varvani rule were estimated by means of mathematical expressions involving material properties, mean stress, and stress amplitude for any given stress levels. Ratcheting strain progressively increased as composite materials experienced low–high loading sequences when stress level increased over steps of loading histories. Ratcheting strain curves of low-high and high-low loading histories were successfully predicted. The predicted ratcheting curves with high–low loading sequences have shown change in ratcheting direction consistent with the experimental data.
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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 | 0.000 | 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".