Assessment of the Influence of Additives on the Mechanical Properties and Machinability of Al-11%Si Cast Alloys: Application of DOE and ANOVA Methods
Bibliographic record
Abstract
In the present study, the statistical design of experiments (DOE) method was applied to study and control the properties of near-eutectic Al-11%Si alloys. In this study, we developed regression equations between response variables, including hardness, yield stress, ultimate tensile stress, elongation, total cutting force, cutting power, and tool life, and varying factors which included the percentage of the alloying element in the composition and the modification level. These equations may be analyzed quantitatively to acquire an understating of the effects of the main variables and their interactions on the mechanical behavior and the machinability of the alloy under investigation. Analysis of variance (ANOVA) was performed to verify the fit and adequacy of the developed mathematical models. The results show that increasing the levels of Cu and Fe results in an increase in hardness, yield stress and ultimate tensile strength in both modified and non-modified alloys. On the other hand, both Cu and Fe appear to affect the elongation adversely, whereas the Sr level shows a positive effect on the elongation percentage. We found that the Sr level had the most significant effect on the cutting forces and cutting power, followed by Fe and Cu contents.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".