Enhanced Formability in Sheet Metals Produced by Cladding a High Strain-Rate Sensitive Layer
Bibliographic record
Abstract
The necking behavior of cladding sheets with a rate-sensitive layer cladding on a rate-insensitive core material has been studied. A nonlinear long-wavelength analysis, similar to the one proposed by Hutchinson and Neale (1977, “Influence of Strain-Rate Sensitivity on Necking Under Uniaxial Tension,” Acta Metal., 25, pp. 839–846) for monolithic rate-sensitive materials, is developed to identify the onset of necking in a rate-sensitive clad sheet. This relatively simple analysis is validated by comparing its numerical results with those based on more complicated finite element analysis. It is demonstrated that for monolithic rate-sensitive materials the proposed nonlinear analysis reduces to the one developed by Hutchinson and Neale (1977). For cladding sheets, it is found that the necking strain increases monotonically by increasing the strain-rate sensitivity of the clad layer if the volume fraction of cladding is fixed. It is also revealed that, for fixed strain-rate sensitivity of the clad layer, necking localization is retarded by increasing the volume fraction of the cladding layer.
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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) | 0.000 | 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".