Real Time Engine Thrust Calculation For Modern Fighter Aircraft
Bibliographic record
Abstract
In traditional flight test programs, in-flight thrust calculations are processed post flight using a thermodynamically balanced engine cycle model. Many attempts have been made to use the standard gross thrust parameter to calculate engine gross thrust real time during flight to expedite data analysis and performance verification. These methods have required complex engine instrumentation, primarily at the engine inlet station and nozzle exit station, and have addressed only fixed nozzle or choked flow configurations. This paper will address three issues: using a modified gross thrust parameter to account for variable, un-choked nozzle configurations; using parameters correlated from the engine cycle model to minimize instrumentation (using only control sensed data); and using correlated parameters, primarily engine airflow, to calculate net thrust. This paper will show that calculated net thrust based on a correlated and modified gross thrust parameter does yield reasonable accuracy relative to engine cycle model thrust and measured thrust (installed tied-down aircraft) and allows real time display of engine thrust using the latest flight test visualization software.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".