Interactions between Superalloys and Mould Materials for Investment Casting of Turbine Blades
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The need of increased efficiency of industrial gas turbines comes also through the improvement of the composition of superalloys (addition of new solutes) and of the manufacturing technologies involved in the investment casting process of the turbine blades. Thus, the knowledge of the interactions between the ceramic materials used for casting and the molten superalloys must be deepened in order to minimize the formation of internal defects, to improve the casting surface and to optimize finishing and casting operations. In this work, a study of the wetting behaviour of some Ni- or Co -based superalloys, used for the fabrication of turbine blades, has been performed with reference to the interactions of these alloys in the molten state with the silica-aluminate based ceramic materials forming the shell or the core in the casting process. Wettability tests have been performed by means of the sessile drop method at 1500°C; the characterization of the interfaces between the molten drop and the substrates has been made on solidified sessile drop samples by SEM/EDS analysis to check the final characteristics of the interfaces. The results are discussed in terms of chemical interactions in relation to the processing parameters and as a function of the surface and interfacial energetic properties of the systems.
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.
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 | 0.000 |
| 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 it