Towards efficient spall generation simulation in rolling element bearing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Rolling element bearing prognosis is the process of forecasting the remaining operational life, future condition or probability of failure of the bearing. While operational, bearings are subjected to rolling contact fatigue (RCF), and, as a result, a spall is generated on the raceway of the bearing. Complete understanding of the fatigue process is critical for predictive modelling to estimate bearing remaining useful life, which allows improved scheduling of maintenance actions. This work presents an RCF model that was implemented using abaqus finite element software. The RCF model is based on a damage mechanics approach that relates the accumulated microscopic failure mechanisms to a damage state variable and includes representation of material grain structure by a Poisson–Voronoi tessellation. Different microstructures, with a variety of material properties and grain topologies, were constructed for simulation purposes. The geometry of the simulated spalls and the Weibull slopes of the fatigue lives are in good agreement with published theoretical and experimental data. It can be concluded that the assumptions and the simplifications of the current, convenient to use, RCF model yield a sufficiently accurate tool on the basis of previous publications and experimental data.
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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 it