Ratcheting Examination of 1045 Notched Steel Plates under Low-High and High-Low Sequences
Bibliographic record
Abstract
Abstract The present study examines the ratcheting response of 1045 notched steel plates undergoing uniaxial step-loading cycles. Loading steps were applied with different Low-High and High-Low sequences. Ratcheting tests were conducted on notched samples, and average local strains were measured with the use of strain gauges mounted in the vicinity of notch roots. Measured ratcheting strains near notch roots were found as high as 10 times those of tests conducted on unnotched samples. The magnitude of applied cyclic load as well as notch diameter influenced local ratcheting strain at the vicinity of the notch root. The lower nominal load level over the first step in the Low-High sequence substantially promoted ratcheting magnitude over subsequent loading steps with higher load magnitudes. In the High-Low loading sequence, the previous load step with higher magnitude retarded the local accumulated plastic strain of the subsequent step with a lower load level. The plastic zone at the notch root was affected over the loading steps. Microhardness tests were conducted at several positions within a small area of 1.5 by 4 mm near the notch root to map the plastic zone and its progress after each loading step. Microhardness data collected at the notch region verified an enlarged plastic zone over the Low-High loading sequence, while the plastic zone for the High-Low loading sequence was estimated about 50 % smaller in size. Cracking at the notch root and fracture surface taken within the plastic zone were examined through optical and scanning electron microscopies.
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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) | 0.003 | 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".