A New Approach to Determine Tensile Stress-Strain Evolution in Semi-Solid State at Near-Solidus Temperature of Aluminum Alloys
Bibliographic record
Abstract
Accurate determination of the materials’ strength and ductility in the semi-solid state at near-solidus temperatures is essential, but it remains a challenging task. This study aimed to develop a new method to determine the stress-strain evolution in the semi-solid state of aluminum alloys within the Gleeble 3800 unit. Stress evolution was determined by the newly developed “L-gauge” method, which converted the displacement of the “restrained” jaw, measured using an L-gauge, into the force. This method gives the possibility to determine the flow stress more accurately, especially for the very low stress rang (1–10 MPa) in the semi-solid state at near-solidus temperatures. The digital image correlation technique implemented in the Gleeble unit allowed effective measurement of the heterogeneous strain fields evolving within the specimen under tensile loading. Therefore, the stress-strain curves measured in the semi-solid state help to better understand the alloy’s susceptibility to hot tearing. The results of an AA6111 alloy under different liquid fractions (2.8% at 535 °C and 5.8% at 571 °C) were demonstrated. The reliable stress-strain data and heterogenous strain distribution are beneficial to develop the thermomechanical models and hot-tearing criteria.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".