Combustion Emission Measurements With Preheated Jet Fuel
Bibliographic record
Abstract
Jet fuel thermal stability at high temperature is receiving increased attention recently as advanced aero engines are being pushed to high power, high pressure and temperature regimes for improved engine cycle performance and low emissions. This paper describes the rig experimental tests to assess the high fuel temperature effect on combustor emissions. A special test rig facility has been designed and set up for emission measurements with preheated fuel. The purpose of the tests is to evaluate the combustor emission characteristics under nominal and elevated fuel temperatures. The scope of the project is two fold: (1) to design, procure and establish a dedicated hot fuel deoxygenation, fuel preheat facility that can reach temperature up to 600 °F (589 K); (2) to measure combustion emissions, mainly NOx, CO and UHC, at normal and elevated fuel temperature under representative engine operating conditions. The test rig has run for extended duration and proved reliable over the whole test campaign. Measured emission results show that fuel temperature effect on NOx, CO, UHC emissions are marginal, possibly due to the low emission capability of the sector combustor that is less sensitive to fuel inlet condition changes than other combustor designs. These results indicate a manageable risk for engine development with elevated fuel temperature from the emission viewpoint.
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 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".