Effect of Cross Section Reduction on the Mechanical Properties of Aluminium Tubes Drawn With Variable Wall Thickness
Bibliographic record
Abstract
Variable thickness tube drawing is a new process for the production of high performance tubes. In this study, experiments were conducted to evaluate the effect of cross section reduction on the microstructure and mechanical properties of variable thickness aluminium tubes drawn using two different position controlled mandrel techniques. Various tubes with three different outer diameters were subjected to cold drawing at room temperature from 11% to 41% cross section reduction. The local mechanical properties were determined from tensile tests carried out on specimens cut from different positions in the tubes parallel to their axes. The distributions of the Vickers hardness over the surfaces at 0 deg and 90 deg to the drawing direction were examined. It was found that the microhardness, yield strength, and ultimate tensile of the deformed samples increase and the corresponding elongation decreases with the increase of cross section reduction. Also, the anisotropy in microstructure and mechanical properties is more significant with increasing of cross section reduction. The evolution of mechanical properties of drawn tubes versus cross section reduction depends on the mandrel shapes and initial tube outer diameter. This study helps to further understand the microstructure and mechanical properties evolutions during tube drawing process with variable thickness.
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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 | 0.000 | 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) | 0.001 | 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".