Aircraft fuel thermal management system and flight thermal endurance
Bibliographic record
Abstract
An aircraft thermal management model was created in which fuel is circulated through the heat dissipating components for cooling purposes. A fraction of this fuel is then fed to the engine for combustion, while the excess is cooled by rejecting heat to the ambient environment and returned to the tank. The thermal management system was designed to control the temperature of the heat dissipating surface, ensuring a certain heat removal rate while safeguarding the physical integrity of the fuel. The changes in fuel temperature and heat transfer rates with time were calculated. We observed that for a constant heat dissipating surface temperature, the temperature of the heated fuel increased, and the heat removal capacity degraded over time. Conversely, for a specified heat removal rate, the temperatures of both the heat-dissipating surface and heated fuel increased during the flight. Lastly, when the maximum fuel temperature was specified, both the temperature of the heat-dissipating surface and heat removal rate decreased over time. In all cases, the time taken for these variables to hit the user-defined threshold values was recorded. We present a detailed sensitivity analysis highlighting the importance of the fuel recirculation rate on the performance of an aircraft’s thermal management system.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".