Thermomechanical transient dynamics of radial rotor–stator contact
Bibliographic record
Abstract
The present paper discusses the numerical investigation of structural interactions initiated radially between a turbine shaft and an annular stator. The rotorshaft is modeled under the rigid bodies assumption while the stator is discretized in space with curved Bernoulli beam elements. The turbomachine is assumed to be driven by two torques: the first one is prescribed from aerodynamics while the second one is induced by sliding friction from Coulomb’s model and must be assessed. The study is motivated by the need to predict the dynamic behavior of the rotorshaft in the presence of radial contact between the labyrinth and the annular stator. If rotordynamics accounting for unilateral and frictional contact is widely developed in literature, the combination with an unknown rotational velocity and thermomechanical coupling must still be investigated. Indeed, heat generation and subsequent thermal expansion is expected to modify the contact interface and the dynamic response. The system is solved in the time domain and contact treatment is achieved though a modified version of the Carpenter algorithm. The identification of the conditions affecting the rotational speed is achieved through a sensitivity analysis on the stator properties, friction coefficient and coefficient of thermal expansion. Results confirm that the higher the friction coefficient and stator stiffness are, the lower the maximum rotational velocity value is. It is also shown that high temperatures are located in specific regions on the stator and that the temperature peaks are amplified with thermal 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".