Characterization of linear friction welded in-service Inconel 718 superalloy
Bibliographic record
Abstract
The focus of this thesis was to study the suitability of the linear friction welding (LFWing) process to manufacture or repair of Inconel® 718 superalloy (IN 718) aero engine BLISKs. This was achieved by simulating a LFW joint made of virgin (V) and in-service (IS) (from samples extracted from an actual turbine disk) IN 718 material. An in-depth microstructural characterization of the V and IS material in the as-received, as-welded and post weld heat treated (PWHT) conditions was carried out. Quantitative analysis of the phase constituents, such as the δ phase, MC-type carbides, MN-type nitrides and the γ grain size of the as-welded and PWHT samples was performed using electron backscattered diffraction (EBSD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analyses. Mechanical testing also revealed that variation in the γ grain size, as well as the distribution and the volume fraction of the precipitates had a significant impact on the alloy’s hardness and tensile properties. Defect analysis of the as-welded samples revealed that the weld interface was free of oxides, voids, contamination and liquation of secondary phases (e.g., carbides and Laves phases). Grain refinement of the γ grains was observed at the weld interface and was related to the occurrence of dynamic recrystallization during the LFWing process. Quantitative analysis of the residual strains and stresses in the as-received, as-welded and PWHT samples was achieved using the neutron diffraction technique. The results revealed that careful selection of the beam gauge volume and stress-free lattice spacing were essential for accurate stress analysis. The results suggested the residual stress increased in magnitude from the base metal and reached a peak at the weld interface. The peak magnitudes of the residual stresses were below the yield strength of IN 718. The results of this work are of significant importance when developing manufacturing and repair processes for IN 718 material components.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".