The Cyclic Deformation Behavior of Severe Plastic Deformation (SPD) Metals and the Influential Factors
Bibliographic record
Abstract
A deeper understanding of the mechanical behavior of ultra-fine (UF) and nanocrystalline (NC) grained metals is necessary with the growing interest in using UF and NC grained metals for structural applications. The cyclic deformation response and behavior of UF and NC grained metals is one aspect that has been gaining momentum as a major research topic for the past ten years. Severe Plastic Deformation (SPD) materials are often in the spotlight for cyclic deformation studies as they are usually in the form of bulk work pieces and have UF and NC grains. Some well known techniques in the category of SPD processing are High Pressure Torsion (HPT), Equal Channel Angular Pressing (ECAP), and Accumulative Roll-Bonding (ARB). In this report, the literature on the cyclic deformation response and behavior of SPDed metals will be reviewed. The cyclic response of such materials is found to range from cyclic hardening to cyclic softening depending on various factors. Specifically, for SPDed UF grained metals, their behavior has often been associated with the observation of grain coarsening during cycling. Consequently, the many factors that affect the cyclic deformation response of SPDed metals can be summarized into three major aspects: (1) the microstructure stability; (2) the limitation of the cyclic lifespan; and lastly (3) the imposed plastic strain amplitude.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".