Metallographic and OIM study of weld cracking in GTA weld build-up of polycrystalline, directionally solidified and single crystal Ni based superalloys
Bibliographic record
Abstract
The repair of gas turbine components is of importance both commercially and scientifically to ensure cost effective repair schemes that will extend the lives of hot end components such as blades and stators. The present communication reports the results of a metallographic and orientation imaging microscopy study of weld cracking observed in the gas tungsten arc repair welds of a polycrystalline (IN738LC), a directionally solidified (Rene 80) and a proprietary single crystal (SX) alloy. The three alloys were welded with low, intermediate and high strength weld fillers, using a weld build-up approach rather than a conventional weld repair of a through thickness crack. This procedure would be applicable for example to worn area on the tips of turbine blades. Inhomogeneous initial microstructures and those from solidification processes led to extensive heat affected zone microfissuring in the IN738LC alloy, associated with MC carbide liquation, liquation of gamma prime ( γ′), segregation of boron and strain effects from precipitation of γ′ in both single and double pass welds. As observed previously in a V shaped weld preparation, the extent of microfissuring in alloy IN738LC increased substantially from the use of the low and intermediate strength weld fillers, to extensive heat affected zone microfissuring by using the high strength IN738 filler. In the directionally solidified Rene 80 welds, due to the reduction in grain boundary area per unit volume, only minor heat affected zone cracking was observed, while the SX alloy did not crack at all. The absence of any cracks in the SX alloy welds despite the presence of stray grains in the fusion zone appears to be related to reduced stress levels in the welds due to the choice of welding technique and the welding parameters.
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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".