On the Elevated Temperature, Tensile Properties of Al-Cu Cast Alloys: Role of Heat Treatment
Bibliographic record
Abstract
The present study aims to investigate the mechanical properties of a newly developed aluminum Al-6.5% Cu-based alloy, coded HT200, as well as to determine how these properties can be further improved using grain refinement and heat treatment. As a result, the effects of different heat treatments and alloying additions on the ambient and high-temperature tensile properties were examined. Three alloys were selected for this study: (i) the base HT200 alloy (coded A), (ii) the base HT200 alloy containing 0.15% Ti + 0.15% Zr (coded B), and (iii) the base HT200 alloy containing 0.15% Ti + 0.15% Zr + 0.5%Ag (coded C). The properties of the three HT200 alloys were compared with those of 319 and 356 alloys (coded D and E, respectively), subjected to the same heat treatment conditions. The results obtained show the optimum high-temperature tensile properties and Q-values for the five alloys of interest, along with the corresponding heat treatment conditions associated with these properties. It was found that the T6 heat-treated alloy B was the optimum alloy in terms of properties obtained, with values comparable to those of commercial B319.0 and A356.0 alloys.
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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) | 0.000 | 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 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".