The TMF Life Assessment of First-Stage W501F Turbine Blade Under Different Operating Temperatures
Bibliographic record
Abstract
Thermal Mechanical Fatigue (TMF) is emerging to be a major damage accumulation mode in the first-stage turbine blades of the F class industrial turbines. In this work, the effect of engine operating temperatures on the TMF life of the first-stage W501F turbine blade has been studied. The turbine inlet temperature (TIT) for the base load engine operation is predicted using thermodynamics based engine analysis. A computational fluid dynamics (CFD) based cascade analysis of the gas path was performed to predict the metal temperatures and temperature gradients. A higher average TIT with a sharper gradient compared to the TIT profile for the base load was also assumed to numerically represent a more severe engine operating test case. A material physics based TMF life prediction approach was adopted to identify the fracture critical locations (FCL). The cyclic life to crack nucleation under different engine operating conditions was also predicted. The predicted FCL and life matched with field experience. A FCL was also predicted inside the cooling channels of the blade, suggesting the need to develop suitable inspection techniques.
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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 | 0.001 |
| 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 | 0.001 | 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".