Optimization of Strengths and Electrical Conductivities of Al-Si-Cu-Ni-Sr Alloys
Bibliographic record
Abstract
The aim of this study is to develop new cast aluminum alloys for the production of rotor bar in the rotor with high as-cast strength and electrical conductivity. A design of experiment (DOE) technique, Taguchi method, was used to develop high as-cast strength and electrical conductivity alloys with various element addition of Si, Cu, Ni and Sr. The optimal combination of chemical composition for maximizing the ultimate tensile strength (UTS), electrical conductivity (σ) and yield strength (YS) was 6 wt.% Si, 3 wt.% Cu, 0.03 wt.% Sr and 0.5 wt.% Ni. The alloy with the optimal composition had an averaged UTS of 247.58 MPa, an averaged electrical conductivity is 38.01%IACS, and an averaged yield strength is 143.47 Mpa.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".