High Energy Density Welding of IN792 Ds Superalloy
Bibliographic record
Abstract
Ni base superalloys are commonly employed in the industrial fields of aerospace, automotive and energy production due to their excellent mechanical properties and corrosion resistance at high temperature. Superficial defects and cracks may occur during both manufacturing process of components and their service life. High energy density welding techniques, electron beam (EBW) and laser beam (LBW) welding, can be used to create efficient repairs. Joints, obtained by EBW and LBW of IN792 directionally solidified (DS) superalloy, have been investigated to determine the presence of defects, and evaluate the mechanical properties related to specific microstructural features. The results showed that a pre-heating temperature (PHT) higher than 200 °C is always necessary to prevent the formation of hot cracks in the molten zone (MZ) and heat affected zone (HAZ). The process parameters have been optimized to get a good quality of the seams (lack of macro-defects, a good penetration depth and width). Some preliminary test of post-welding heat treatments (PWHTs) have been investigated to homogenize as far as possible the microstructure and the mechanical properties across the seams. The results obtained by the two techniques, EBW and LBW, have been compared and discussed.
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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".