Turbine Blade Tip Repair by Laser Directed Energy Deposition Additive Manufacturing Using a Rene 142–MERL 72 Powder Blend
Bibliographic record
Abstract
Laser directed energy deposition (LDED) was used with a powder blend comprising 75 wt.% Rene 142 and 25 wt.% of Merl 72 (4275M72) for turbine blade tip repair applications. Sound samples could be deposited at ambient temperature on Haynes 230. The microstructural analyses showed the presence of fine gamma prime precipitates in the as-deposited samples, while after aging, the alloy possessed around 40 vol.% with a bimodal precipitate size distribution. Also, the alloy contained Ta-Hf-W carbides in different sizes and shapes. Tensile testing from room temperature up to 1366 K was performed. The 4275M72 deposits possessed higher tensile properties compared to Rene 80 in this temperature range but lower elongations at the elevated temperatures. The creep properties of 4275M72 samples at 1255 K were superior to Rene 80. Also, the oxidation resistance of deposited 4275M72 was similar to Rene 142. The combination of high mechanical properties, creep behavior, and oxidation resistance of LDEDed 4275M72 makes it a suitable alloy for tip repair of turbine blades.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".