Improvement of Silicon Nitride Turbine Blade Impact Resistance Under Uniaxial Compression Loading
Bibliographic record
Abstract
Abstract The inside-out ceramic turbine (ICT), a novel microturbine rotor architecture, uses monolithic ceramic turbine blades held in compression by a rotating structural shroud instead of traditional superalloy turbine blades in order to increase its maximum turbine inlet temperature (TIT) and cycle efficiency. Previous work has shown that this microturbine architecture has potential to be viable for long-term operation in normal operating conditions. However, foreign object damage (FOD) has been a major concern for ceramic turbine rotor past development efforts, and its effects on the ICT ceramic turbine blades lifespan have not been studied thus far. An experimental approach was used to characterize the effect of the ICT configuration on ceramic turbine blade impact resistance: spherical steel impactors were fired towards silicon nitride specimens simulating blade boundary conditions for both traditional and inside-out turbine layouts. Preload levels ranging from 100 MPa to 400 MPa were applied on the inside-out layout specimens to determine its effect on impact resistance. Results indicate that the inside-out turbine configuration increases the resistance to FOD over a traditional turbine configuration. For the specific conditions of this study, the specimens resisted to over five times the impactor energy when fixed at both ends. Also, results show that applying a higher compression preload on the specimens helps to resist higher energy impacts by about 50% when far from the buckling limit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".