Emissions Assessment of Alternative Aviation Fuel at Simulated Altitudes
Bibliographic record
Abstract
To address the global fuel challenges of energy security, economic sustainability and climate change the stakeholders of aviation industry are actively pursuing the development and qualification of alternative ‘drop-in’ fuels. New standards will be required to regulate the use of these new fuels, which requires not only fuel specification and rig/engine and flight testing but also an emission life cycle impact assessment of these fuels. This paper reports on emission data measured at various simulated altitudes and engine speeds from a jet engine operated on conventional and alternative aviation fuels. The work was conducted as part of on-going efforts by departments within the Government of Canada to systematically assess regulated as well as non-regulated emissions from the use of alternative aviation fuels. The measurements were performed on an instrumented 1000 N-thrust turbojet engine using a baseline conventional Jet A-1 fuel and a semi-synthetic (50/50) blend with Camelina based Hydroprocessed Renewable Jet (JP8-HRJ8) fuel. Emission results reported here include carbon dioxide, carbon monoxide, nitrogen oxides and particulate matter measured at several simulated altitudes and power settings. In order to ensure that the assessments have a common baseline, relevant engine performance and operability data were also recorded.
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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".