Containment and Arrest of Blade Shedding in Gas Turbine Engines Using Novel Dual-Ring Design
Bibliographic record
Abstract
Abstract In this paper, we examine the energy absorption and containment capabilities of a newly proposed dual-ring design accounting for interactions between a released blade and fully bladed fan disk using three-dimensional finite element analysis. The components of this dual-ring design are strategically selected to ensure high energy absorption and high impact resistance, thus leading to reduced damage of the disk and increased safety. Three containment ring designs are examined: (i) conventional single-ring design composed of one of titanium, aluminum, or Kevlar; (ii) a newly proposed aluminum-Kevlar dual-ring arrangement; and (iii) dual-ring arrangement with an interfacial gap between them to arrest and contain the released blade and ensure free passage of the trailing blades. The results of our numerical simulations indicate that although the single-ring design resists penetration and contains the released blade within the confines of the disk, it does not remove the released blade from the path of the trailing blades leading to severe damage to the fan disk. On the contrary, our new dual-ring design, which contains an interfacial gap, has potential to successfully arrest the released blade within the confines of the ring and out of the path of the trailing blades. This design can significantly reduce the impact damage to the fan disk and reduce kinetic energy of the released blade to near zero in less than half a rotation of the fan disk.
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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 | 0.000 |
| 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 | 0.001 | 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".