Optimization on the Production of Variable Thickness Aluminium Tubes
Why this work is in the frame
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Bibliographic record
Abstract
The variable thickness tube drawing is a new modification in the tube drawing methods which enables production of axially variable thickness tubes faster and easier in comparison with other similar methods like radial forging or indentation forging. The production of this type of tubes can be used in optimum design of mechanical parts which do not necessarily need constant thickness along the axis of tube and this method can strikingly reduce the overall weight of parts and mechanical assemblies like cars. In this paper, the variable thickness tube drawing were parameterized in a MATLAB code and optimized with the Ls-Opt software as an optimization engine and Ls-Dyna as a FE solver. The final objective of this optimization study is to determine the minimum thickness which can be produced in one step by this method with various tube dimensions (tube thickness and outer diameter). For verification of results, some experiments were performed in the tube drawing machine which was fabricated by this research group and acceptable correspondence was observed between numerical and experimental results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 it