On the Effect of SiC Content and Processing Temperature on Relative Density and Hardness of Hot Compacted Aluminum AA6061 Composite – Mathematical Empirical and Response Surface Approach
Bibliographic record
Abstract
The AA6061 is reinforced by adding SiC at various volume fractions and, the mixture is hot compacted at different processing temperatures. The influences of such parameters are investigated on the product relative density along with its relevant Vickers hardness using quantitative and qualitative formulation approach. Empirical relationships are established to relate each of the controlling (independent) parameters (SiC% and hot compaction (HC) temperature), to the composites relative density and the hardness, as dependent variables. The developed models are examined for its adequacy and significance using several statistical criteria. Response surface and contour graphs are established to reflect the relevant function interrelations and, to provide a data base source for the prior design stage. Within the specified experimental domain, first order and nonlinear models are found independently adequate and significant to grasp the functional dependence between the relative density and both SiC and HC temperature. However, second order multiple model with quadratic components of SiC percent is found to best suit the hardness-SiC%-temperature functional relationship. Increasing SiC content is found to reduce the relative density of the composites regardless the hot compaction temperature while, up to about 18 vol.% SiCp relative ratio, it enormously and nonlinearly increases the composite hardness. Further increase in SiC% addition seems not to affect the composite hardness. Relative density of the resulting composite is decreased by increasing HC temperature.
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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 | 0.011 | 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 | 0.002 |
| 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".