The Future of Conventional Aircraft Ground Propulsion Systems in Relation to Fuel Consumption and CO2 Emission
Bibliographic record
Abstract
Aircraft spends a minimum of 20 minutes using its main engine to taxi from the airport terminal gate to the runway, where the aircraft takes-off and similarly to the terminal gate after landing. During taxi operation, aircraft burns a lot of fuel, generates large quantity of emissions and the engine in the process of taxiing is exposed to damage due to Foreign Object Damage (FOD). This results in huge operational and maintenance cost as well as carbon emission tax which are all at the expense of the airline. EGTS is a recent technology designed to prevent aircraft from using its main engine for taxi operation and this in turn reduces the rate of fuel consumption, slashes carbon emissions and minimises operational and maintenance cost. This paper examines the viability of using EGTS in single engines for taxi operation rather than the aircraft engine. Block fuel savings was calculated for two engine, single engine and hybrid aircraft and it was observed that two engine aircraft using EGTS saved 110kg block fuel, single engine saved 74kg and for hybrid engine the block fuel savings was 50kg. Block fuel savings was calculated for aircraft such as airbus A320, airbus A380, Cessna 172 and A600ST and it was observed that EGTS is more compatible with airbus A320 but was not recommended for A600ST and A380 due to extra weight implication and for Cessna 172, EGTS was not necessary because the aircraft weight is low and consumes less fuel already. It was observed that the higher the aircraft weight including the extra weight of EGTS, the higher the fuel consumption emission as well as the torque required to overcome drag force when the aircraft operates in air. CO2 emission was also calculated for aircraft with EGTS and aircraft without installation, the result for aircraft with EGTS showed 797.56kg reduction of CO2 emission when compared to aircraft without EGTS. Comparably, EGTS was proven to be viable in terms of fuel savings, CO2 emissions, operational and maintenance cost than its contemporary Ground Propulsion Systems (GPS) for single aircraft engines and therefore, was recommended for aircraft in airbus A320 category to help minimise global warming which results from CO2 emission during taxing operations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".