Dwell Fatigue of a Fully Lamellar Ti6242 Alloy: Deformation Mechanisms at Different Scales
Bibliographic record
Abstract
Ti6242 alloy is used for high pressure compressor disks in jet engines due to its good fatigue resistance at low and moderate temperatures. These parts undergo complex in-service thermo-mechanical loading that can be simulated on laboratory samples by introducing a dwell time at maximum stress in cyclic loading tests. The use of such trapezoidal signal appears more realistic than pure fatigue to simulate flights. Under these conditions, this alloy is well-known to present an important decrease of its lifetime when compared to standard fatigue. This phenomenon is commonly observed in metallic materials for high temperatures when viscoplasticity mechanisms are active. The fact that this decrease of the fatigue life resistance appears at room temperature for the Ti6242 has led the scientific community to name it “cold dwell effect”. The present work aims at studying the micro-structure configurations favoring micro-plasticity mechanisms during dwell cycling. Instrumented micro-samples are tested in situ in a SEM under tensile, creep and dwell conditions. Microstructure and deformation are analyzed at the scale of lamellae and colonies taking into account the local crystalline orientation (EBSD) and the morphological orientation (image processing). The appearance of micro-relief at large scale is also considered and quantified using white light interferometry. Relationships between microstructure, micro-texture and mechanical deformation are established.
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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".