CDS Method for Casting Aluminium-Based Wrought Alloy Compositions: Theoretical Framework
Bibliographic record
Abstract
A novel process named Controlled Diffusion Solidification (CDS) has been developed to circumvent problems that are typically associated with casting wrought aluminum alloy compositions into near net shaped components. The process involves bringing two precursor alloys of precisely controlled composition, temperature, and quantity into intimate contact, and then casting the resultant alloy using a conventional casting process to yield a component of predetermined composition with a microstructure that is similar to that of semi-solid processed alloys. Describing the many interactions that occur during solidification of aluminum alloys in a consistent manner is virtually impossible without the use of computational tools that are based on thermodynamic models. In this paper, we describe how the CALPHAD method, which allows calculating all the necessary data from thermodynamic model parameters, was used along with theoretical calculations and empirical rules to allow describing the Gibbs free energy of each phase in the alloy system and yield quantitative data that guided the development and optimization of the CDS method.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".