A Review on Porosity Formation in Aluminum-Based Alloys
Bibliographic record
Abstract
The main objective of this review is to analyze the equations proposed for expressing the effect of various parameters on porosity formation in aluminum-based alloys. These parameters include alloying elements, solidification rate, grain refining, modification, hydrogen content, as well as the applied pressure on porosity formation in such alloys. They are used to establish as precisely as possible a statistical model to describe the resulting porosity characteristics such as the percentage porosity and pore characteristics, as controlled by the chemical composition of the alloy, modification, grain refining, and the casting conditions. The measured parameters of percentage porosity, maximum pore area, average pore area, maximum pore length, and average pore length, which were obtained from statistical analysis, are discussed, and they are supported using optical micrographs, electron microscopic images of fractured tensile bars, as well as radiography. In addition, an analysis of the statistical data is presented. It should be noted that all alloys described were well degassed and filtered prior to casting.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".