Bibliographic record
Abstract
The literature in Vacuum Induction Melting is briefly reviewed, with especial emphasis on refractory practices and refractory-metal interactions. Since it was determined that in both steel and superalloy vacuum melting in large furnaces lining failures are associated with attack on the cement joints, tests were performed to characterize this attack and determine the most suitable cements from this standpoint. The presence of low-stability oxides (SiO₂, P₂O₅,...) was shown to be the main reason for the cement's low resistance to metal attack. It is suggested that in the case of steels, diffusion of the less stable oxides may be the rate controlling step in the corrosion process. In the case of superalloys, the high interaction between oxygen and the elements present in the alloy (Ti, Al, Cr) causes an extreme depression of the oxygen activity in the melt, hence enhancing the dissolution of all refractory oxides. In order to produce cements with a very small content of the low-stability oxides, the use of fluorides as fluxes was attempted. The cements so produced performed well, as far as resistance to attack, adherence to bricks and technological properties were concerned. To verify the validity (on a large scale) of the mechanisms observed and proposed in the tests, samples from industrial Vacuum Furnaces were examined. It was concluded that the processes occurring in a large furnace can be rationalized based on the test observations. Also comments were made on the need for improved pouring facilities, if the products of the metal-refractory interaction are to be kept out of the final material produced. This is because in the present state of the refractory technology and practice, these interactions cannot be avoided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".