Modeling and Optimizing Ti-6Al-4V Ingot Production
Bibliographic record
Abstract
Control of chemistry and shrinkage void in the final stages of the consolidation processes employed to produce Ti alloy ingots is critical from the standpoint of productivity as there is a direct correlation to the amount of material that must be removed prior to further downstream processing. The application of power to the top surface during this stage allows the raising of the depth of shrinkage voids; however, it can also cause excessive evaporation of volatile elements within the alloy. The balancing of these two factors represents a classic optimization problem. A mathematical model describing the final stage of a commercial consolidation process has been developed to assist in the optimization of the process. The model solves the coupled thermal-fluid flow problem including solute conservation and evaporation. Experimental measurements consisting of the sump depth, pool profile marking, and local composition analysis have been used to validate the model predictions under various casting conditions.
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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 | 0.000 | 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 | 0.001 |
| 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".