Ratcheting response of nylon fiber reinforced natural rubber/styrene butadiene rubber composites under uniaxial stress cycles: Experimental studies
Bibliographic record
Abstract
Abstract The present study intends to study the ratcheting response of nylon fiber reinforced natural rubber (NR)‐styrene butadiene rubber (SBR) composite samples under asymmetric stress cycles. Uniaxial tests conducted on composite samples have shown how influential the weight fraction of short nylon fibers on the stress‐strain curves/loops under monotonic and cyclic loads is. NR/SBR composite samples with various fiber contents of 0, 10, 20, 30, and 40 per hundred rubber (phr) were tested under asymmetric stress cycles. In these tests, stress‐strain hysteresis loops were progressively shifted over stress cycles resulting in progressive plastic strain accumulation. Over stress cycles, ratcheting strain progressed within the first few cycles with a relatively high rate, and as the number of cycles increased, this rate decayed resulting in a plateau in strain accumulation (shakedown). The ratcheting strain rate and magnitude resulting in shakedown were highly affected by the nylon fiber content. The experimental observations showed that this plateau (shakedown) occurred after a number of cycles in NR/SBR composite samples where the widths of hysteresis loops stayed unchanged. Samples with no fiber and that with 10 phr fiber content possessed high ratcheting rates leading samples to failure after a few stress cycles. Fracture surfaces in these samples were further analyzed through SEM investigation.
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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) | 0.002 | 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".