Comparison of Laminar Flame Speeds, Extinction Stretch Rates and Vapor Pressures of Jet A-1/HRJ Biojet Fuel Blends
Bibliographic record
Abstract
An emerging goal within the aviation industry is to replace conventional jet fuel with biologically-derived alternative fuel sources. However, the combustion properties of these potential fuels must be thoroughly characterized before they can be considered as replacements in turbomachinery applications. In this study, seven candidate alternative fuel blends, derived from two biological feedstocks and blended in different quantities with Jet A-1, are considered. For each blend, the laminar flame speed, non-premixed extinction stretch rate, and vapor pressure are experimentally determined and compared to numerical simulations and to Jet A-1 data. Hydrodynamically-stretched flame speeds are determined by applying particle image velocimetry (PIV) to an atmospheric pressure, preheated jet-wall stagnation flame, and the unstretched laminar flame speed is inferred using a direct comparison method in conjunction with a binary jet-fuel surrogate, with results spanning a wide equivalence ratio range. Extinction stretch rates were measured using particle tracking velocimetry (PTV) in a non-premixed counterflow diffusion flame, over a range of fuel mass fractions diluted in nitrogen carrier gas. Finally, the vapor pressure of the seven biojet/Jet A-1 fuel blends was measured using an isoteniscope over a wide temperature range. The results of this study indicate that moderate blends of hydrotreated renewable jet (HRJ) fuel with Jet A-1 have similar combustion properties to conventional jet fuel, highlighting their suitability as drop-in replacements, while higher blend levels of HRJ fuel, regardless of the crop source, lead to definitive changes in the combustion parameters investigated here.
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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".