The Use of Microelectromechanical Systems for Surge Detection in Gas Turbine Engines
Bibliographic record
Abstract
Compressor surge results from the instability of highly undesirable oscillations occurring at specific frequencies and at low compressor flow rates in the system. Research has shown that by stabilizing the small-perturbation dynamics, the large-amplitude surge event can be prevented in these systems. In order to completely avoid the initiations of conditions that will lead to surge or stall, engine designs conservatively determine operational stability margins that are far from the stability limit of the compression system. Advanced turbine engines operate with reduced stability margins to increase performance. This reduction in stability margin must be limited to such an extent that does not compromise the operational capability of the engine. Pressure probes equipped with fast-response transducers have been successfully used in axial-flow compressors and turbines but have been rarely used in centrifugal compressors. The harsh thermal environment of operation has limited the use of pressure transducers to operational ranges below 250/spl deg/C effectively precluding measurement at the final stage exit where temperatures are typically in excess 280/spl deg/C depending on the turbine. This paper proposes a hybrid processing method in which a piezoresistive chromium strain gauge is embedded between two thin film silicon carbide (SiC-MEMS) or silicon carbon nitride microelectromechanical (SiCN-MEMS) membranes as an enhanced technique for the design of high temperature pressure transducers. The hybrid process technology, which enables fabrication of such structure, along with the novel packaging principles represents the main contribution of the present report.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".