Bibliographic record
Abstract
The mechanical response of a servo-hydraulic testing system is affected by the stiffness of test specimens. An adaptive controller helps in auto-tuning the system by setting the optimal proportional-integral-derivative values for the subsequent test as the stiffness changes. This paper presents the effect of auto-tuning of various channels on the flow response of several commercial Al and Mg alloys and a mild steel. Strain-controlled monotonic tensile tests were performed at a given strain rate of 1 × 10−4 s−1 after auto-tuning of position, load, and strain channels in different combinations. Serrated flow or Portevin–Le Chatelier effect was observed in the Al alloys after auto-tuning of either position channel only or position and load channels. However, the serrations of Al alloys were shielded after further auto-tuning of strain channel. The stress-strain curves of Mg alloys and mild steel were observed to be basically free of serrations under any combinations of auto-tuning, which confirms that the serrated flow is a property of specific materials rather than a machine system noise.
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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 | 0.000 | 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".