Probabilistic Creep Life Prediction of Turbine Discs
Bibliographic record
Abstract
The paper presents the results of a probabilistic creep life study on F5001P turbine discs and demonstrates the importance of using physics based probabilistic damage modeling techniques to deal with life prediction uncertainty in forged components. In physics based modeling, the influence of individual microstructural or thermal-mechanical loading factors on metallurgical crack initiation can also be studied with relative ease. In a previous study, Life Prediction Technologies Inc.’s (LPTi’s) prognosis tool known as XactLIFE™ was successfully used to conduct deterministic analysis to establish the fracture critical location of F5001P first stage discs under steady state loads. In this paper, the variability in life is further established as a function of prior austenite grain size. The analysis used typical engine operating data from the field in terms of engine speed and average exhaust gas temperature (EGT). The primary objectives of the case study are to show how prognosis can allow a user to assess fleet reliability for engine specific operating conditions. The lower bound deterministic creep life and probabilistic creep life at 0.1% cumulative probability of failure are very close in magnitude.
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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 | 0.000 |
| 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".