Nonlinear support effects on the aeroelastic stability of multi-stage turbine rotors
Bibliographic record
Abstract
This study presents a comprehensive analysis of aeroelastic stability in multi-stage turbine rotors mounted on nonlinear supports. A high-fidelity dynamic model is developed by coupling the structural behavior of a rotating shaft–disk–blade assembly with quasi-steady aerodynamic forces. The system incorporates nonlinear stiffness and damping in the bearing supports, and the governing equations of motion are derived using the Lagrangian method. Aerodynamic forces are modeled using cascade theory for incompressible subsonic flow and integrated with structural dynamics through coordinate transformation. The resulting nonlinear system is solved using the Runge-Kutta method, and its stability characteristics are investigated via bifurcation diagrams and Poincaré maps. A detailed parametric study is conducted to examine the influence of aerodynamic parameters, structural parameters and support characteristics on rotor response. Results show that nonlinear supports significantly alter stability boundaries, reduce critical flutter speeds, and introduce multi-periodic dynamic behavior. These findings provide valuable insights into the design and tuning of support systems to enhance the dynamic robustness of turbomachinery.
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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 | 0.000 | 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".