Dynamic pressure as a measure of gas turbine engine (GTE) performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Utilizing in situ dynamic pressure measurement is a promising novel approach with applications for both control and condition monitoring of gas turbine-based propulsion systems. The dynamic pressure created by rotating components within the engine presents a unique opportunity for controlling the operation of the engine and for evaluating the condition of a specific component through interpretation of the dynamic pressure signal. Preliminary bench-top experiments are conducted with dc axial fans for measuring fan RPM, blade condition, surge and dynamic temperature variation. Also, a method, based on standing wave physics, is presented for measuring the dynamic temperature simultaneously with the dynamic pressure. These tests are implemented in order to demonstrate the versatility of dynamic pressure-based diagnostics for monitoring several different parameters, and two physical quantities, dynamic pressure and dynamic temperature, with a single sensor. In this work, the development of a dynamic pressure sensor based on micro-electro-mechanical system technology for in situ gas turbine engine condition monitoring is presented. The dynamic pressure sensor performance is evaluated on two different gas turbine engines, one having a fan and the other without.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it