Thermomechanical transient dynamics of radial rotor–stator contact
Bibliographic record
Abstract
The present paper discusses the numerical investigation of structural interactions initiated radially betweena turbine shaft and an annular stator. The rotorshaft is modeled under the rigid bodies assumption whilethe stator is discretized in space with curved Bernoulli beam elements. The turbomachine is assumed tobe driven by two torques: the first one is prescribed from aerodynamics while the second one is inducedby sliding friction from Coulomb’s model and must be assessed. The study is motivated by the need topredict the dynamic behavior of the rotorshaft in the presence of radial contact between the labyrinth andthe annular stator. If rotordynamics accounting for unilateral and frictional contact is widely developed inliterature, the combination with an unknown rotational velocity and thermomechanical coupling muststill be investigated. Indeed, heat generation and subsequent thermal expansion is expected to modify thecontact interface and the dynamic response. The system is solved in the time domain and contact treatmentis achieved though a modified version of the Carpenter algorithm. The identification of the conditionsaffecting the rotational speed is achieved through a sensitivity analysis on the stator properties, frictioncoefficient and coefficient of thermal expansion. Results confirm that the higher the friction coefficientand stator stiffness are, the lower the maximum rotational velocity value is. It is also shown that hightemperatures are located in specific regions on the stator and that the temperature peaks are amplified withthermal expansion.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".