Rotordynamics of a Highly Flexible Hub for Inside-Out Ceramic Turbine Application: Finite Element Modeling and Experimental Validation
Bibliographic record
Abstract
The inside-out ceramic turbine (ICT) is a promising concept to increase turbine inlet temperatures in microturbines by integrating individual monolithic ceramic. This architecture uses a carbon–polymer composite rim to support the blades mainly in compression. High tangential velocities lead to elevated radial displacement of the rim, and therefore, the rotor hub needs to have sufficient compliance to follow this radial displacement. However, the rotordynamics of a flexible hub is not widely understood. This paper presents the rotordynamic analysis of a highly flexible hub for an ICT architecture. Finite element modeling (FEM) is used to design a simplified turbine prototype that maximizes the hub flexibility to explore the limits of the concept. The rotordynamics behavior of the highly flexible hub is measured by spinning a 171-mm diameter prototype up to 49 krpm. This paper highlights three principal challenges of this particular rotordynamics. First, critical speeds mode shape becomes highly coupled with bearings displacement, shaft bending, and hub deformation. At high-speed, the hub deforms out of phase with the shaft, which can cause high stresses in the hub. Second, the angular position between unbalance masses of the flexible hub and the composite rim changes the unbalance response significantly. Finally, vibration causes high stresses in the hub, due to the relative displacement between the composite rim and the shaft, which could lead to failure of the hub. Nevertheless, the rotordynamics of an ICT configuration is manageable as long as the vibration-induced stress in the hub is kept under its limit.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".